Search Results (104)

Osteoarthritis (OA) and osteochondral degeneration present a significant clinical burden characterized by the complex interplay of extracellular matrix degradation and chronic inflammation. While biochemical profiling has matured, a critical translational gap remains in transitioning from benchtop assays to systems capable of continuous, intra-articular monitoring. This review provides a comprehensive synthesis of experimentally validated biosensing technologies, including optical, electrochemical, and piezoelectric Quartz Crystal Microbalance (QCM) platforms, evaluated through the lens of sensing architecture, biomarker specificity, and matrix compatibility. Our analysis reveals that while optical sensors offer superior sensitivity, electrochemical platforms show the greatest promise for miniaturized, implantable integration. However, a pivot in the field is identified: the primary bottleneck has shifted from analytical detection limits to operational stability within the hostile synovial environment. Current research is largely restricted to single-analyte detection in simplified media, failing to address the multifactorial nature of OA. We propose that the next generation of osteochondral diagnostics must prioritize multiplexed arrays, mechanically compliant architectures, and machine-learning-assisted signal processing. By bridging these engineering frontiers, biosensors will evolve from passive diagnostic tools into intelligent, personalized platforms for real-time disease management. Full article

Long-chain aldehydes, particularly nonanal, are recognized as potential volatile biomarkers of lung cancer in exhaled breath. This study investigates the influence of peptide counter-ions on the performance of QCM-based biosensors using two odorant-binding protein-derived peptides (OBPP4 and OBPP4 GSGSGS) for the selective gas-phase detection of these aldehydes. Exchanging the counter-ion from trifluoroacetate to chloride improves biosensor sensitivity and lowers the limit of detection within the set of biosensors investigated in this study. The OBPP4 GSGSGS with chloride exhibited the highest sensitivity to nonanal (0.153 Hz/ppm) and the lowest LOD (9.8 ppm), with excellent selectivity over other groups of volatiles. The novelty of this work lies in demonstrating, for the first time, that simple counter-ion exchange in synthetic peptides can significantly enhance the gas-phase binding of volatile aldehydes, classified as lung cancer biomarkers, without altering the peptide sequence, offering a straightforward and effective optimization strategy for peptide-based piezoelectric biosensors. Full article

Avian influenza (AI), particularly highly pathogenic avian influenza (HPAI), represents a serious and growing threat to global poultry production, international trade, and human health security. Control of AI is complicated by the high evolutionary rate of influenza A viruses, which drives antigenic diversity and ongoing emergence of novel strains. Effective surveillance and disease management therefore depend on timely and accurate diagnostics. While conventional methods—including virus isolation, reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and enzyme-linked immunosorbent assays (ELISAs)—remain effective and widely used, they are limited by long turnaround times, the need for specialized equipment, and reliance on highly trained personnel. In addition, strict state and federal regulatory requirements restrict testing to a limited number of authorized laboratories. Although these regulations are essential for maintaining diagnostic accuracy and quality assurance, they place substantial strain on laboratory capacity during outbreaks and delay actionable results. The need for rapid, on-site decision making has driven interest in alternative diagnostic approaches, including biosensor technologies. A major limitation of current diagnostic strategies is the lack of robust DIVA (Differentiating Infected from Vaccinated Animals) capability. In countries such as the United States, where poultry vaccination against AI is not routinely practiced, the absence of DIVA-compatible diagnostics has hindered adoption of vaccination as a disease management tool, as seropositive birds and products face significant trade restrictions. Biosensor platforms capable of enabling DIVA strategies offer a potential pathway to support vaccination while preserving surveillance integrity. This review examines the current landscape of AI and HPAI diagnostics, emphasizing the limitations of traditional approaches and the opportunities presented by biosensor platforms. We evaluate electrochemical, optical, piezoelectric, and nucleic-acid-based biosensors, with particular attention to biorecognition strategies, performance metrics, field deployability, and applications supporting subtype discrimination, DIVA implementation, and One Health surveillance. Full article

Current liquid-phase resonant biosensors, such as Quartz Crystal Microbalance, Surface Acoustic Wave, or Surface Plasmon Resonance, typically rely on specialized piezoelectric substrates or complex optical setups. These requirements often necessitate cleanroom fabrication, thereby limiting cost-effective scalability. This study presents a high-integration sensing platform based on standard Printed Circuit Board (PCB) technology, incorporating an embedded inductor within a fluidic system for real-time monitoring. This design leverages industrial manufacturing standards to achieve a compact, low-cost, and scalable architecture. Detection is governed by shifts in the resonance frequency of an LC tank circuit; specifically, increases in bulk ionic strength induce a frequency decrease, whereas biomolecular adsorption at the sensor surface leads to a frequency increase. This phenomenon can be explained by the modulation of the inter-turn capacitance, which is modeled as a combination of capacitive elements accounting for contributions from the bulk electrolyte and the surface-bound dielectric layer. Such divergent responses provide an intrinsic self-discriminating capability, allowing for the analytical differentiation between surface interactions and bulk effects. To the best of our knowledge, this is the first demonstration of an inductor-based resonant sensor fully embedded in a PCB fluidic architecture for continuous liquid-phase analyte monitoring. Validated through a protein-antibody model (Bovine Serum Albumin-anti-Bovine Serum Albumin), the sensor demonstrated a limit of detection of 1.7 ppm (0.026 mM) and a linear dynamic range of 31–211 ppm (0.47–3.2 mM). These performance metrics, combined with a reproducibility of 4 ± 3%, indicate that the platform meets the requirements for robust analytical applications. Its inherent simplicity and potential for miniaturization position this technology as a viable candidate for point-of-care diagnostics in diverse environments. Full article

Colorectal cancer (CRC) remains a major cause of morbidity and mortality worldwide, with its incidence and biological behavior influenced by both genetic and environmental factors. Emerging evidence highlights notable sex differences in CRC, with men generally exhibiting higher incidence rates and poorer prognoses, while women often display stronger immune responses and distinct molecular profiles. Traditional screening tools, such as colonoscopy and fecal-based tests, have improved survival through early detection but are limited by invasiveness, cost, and adherence issues. In this context, biosensors have emerged as innovative diagnostic platforms capable of rapid, sensitive, and non-invasive detection of CRC-associated biomarkers, including genetic, epigenetic, and metabolic alterations. These technologies integrate biological recognition elements with nanomaterials, microfluidics, and digital systems, enabling the analysis of biomarkers such as proteins, nucleic acids, autoantibodies, epigenetic marks, and metabolic or VOC signatures from blood, stool, or breath and supporting point-of-care applications. Electrochemical, optical, piezoelectric, and FET platforms enable label-free or ultrasensitive multiplexed readouts and align with liquid biopsy workflows. Despite challenges related to standardization, robustness in complex matrices, and clinical validation, advances in nanotechnology, multi-analyte biosensing with artificial intelligence are enhancing biosensor performance. Integrating biosensor-based diagnostics with knowledge of sex-specific molecular and hormonal pathways may lead to more precise and equitable approaches in CRC detection, selection of therapeutic regimes and management. Full article

A piezoelectric ultrasonic transducer has been developed to detect flow rate, occlusion, and bubble formation in a portable peritoneal dialysis system. This transducer works by utilizing the piezoelectric effect to convert electrical energy into ultrasonic waves and detect the reflected waves through the tube wall. In addition, organic thin film transistors (OTFTs) were tested at annealing temperatures of 75 °C, 100 °C, and 125 °C to evaluate the effect of temperature on mobility and on/off ratio. The best results were obtained at 100 °C with a mobility of 0.816 cm²/Vs and an on/off ratio of 1.4 × 10³ correlated with grain size. This study aims to report the fabrication process and initial characterization of the OTFT device as a first step towards the development of a portable biosensor that can be integrated into a point-of-care system. The transducer is designed for use in PeritoCare^® (Bangi, Malaysia), a portable peritoneal dialysis system developed by Universiti Kebangsaan Malaysia (UKM). The integration of piezoelectric transducers and OTFTs into the PeritoCare^® system enables the development of a more flexible, efficient, and mobile peritoneal dialysis system for young, active end-stage renal disease (ESRD) patients. Full article

Detecting small molecules in biological fluids is essential for diagnosing diseases, monitoring therapy, and studying how the body works. Traditional biosensing methods—such as amperometric, optical, or piezoelectric systems—offer excellent sensitivity but often rely on complex instruments, additional reagents, or time-consuming sample preparation. Potentiometric biosensors, by contrast, provide a simpler, low-power, and label-free alternative that can operate directly in biological environments. This review explores the latest progress in potentiometric biosensing for small-molecule detection, focusing on new solid-contact materials and advanced sensing membranes and compact device designs. We also discuss key challenges, including biofouling, matrix effects, and signal drift, together with promising strategies such as antifouling coatings, nanostructured interfaces, and calibration-free operation. Finally, we highlight how combining potentiometric sensors with artificial intelligence, digital data processing, and flexible electronics is shaping the future of personalized and point-of-care diagnostics. By summarizing recent advances and identifying remaining barriers, this review aims to show why potentiometric biosensors are becoming a powerful and versatile platform for next-generation biomedical analysis. Full article

Foodborne pathogens remain a significant public health concern, necessitating the development of rapid, sensitive, and reliable detection methods for various food matrices. Traditional biosensors, while effective in many contexts, often face limitations related to complex sample environments, signal interpretation, and on-site usability. The integration of artificial intelligence (AI) into biosensing platforms offers a transformative approach to address these challenges. This review critically examines recent advancements in AI-assisted biosensors for detecting foodborne pathogens in various food samples, including meat, dairy products, fresh produce, and ready-to-eat foods. Emphasis is placed on the application of machine learning and deep learning to improve biosensor accuracy, reduce detection time, and automate data interpretation. AI models have demonstrated capabilities in enhancing sensitivity, minimizing false results, and enabling real-time, on-site analysis through innovative interfaces. Additionally, the review highlights the types of biosensing mechanisms employed, such as electrochemical, optical, and piezoelectric, and how AI optimizes their performance. While these developments show promising outcomes, challenges remain in terms of data quality, algorithm transparency, and regulatory acceptance. The future integration of standardized datasets, explainable AI models, and robust validation protocols will be essential to fully harness the potential of AI-enhanced biosensors for next-generation food safety monitoring. Full article

Graphene, a two-dimensional carbon material with a hexagonal lattice structure, possesses remarkable properties. Exceptional electrical conductivity, mechanical strength, and high surface area that make it a powerful platform for biosensing applications. Its sp²-hybridised network facilitates efficient electron mobility and enables diverse surface functionalisation through bio-interfacing. This review highlights the core detection mechanisms in graphene-based biosensors. Optical sensing techniques, such as surface plasmon resonance (SPR) and surface-enhanced Raman scattering (SERS), benefit significantly from graphene’s strong light–matter interaction, which enhances signal sensitivity. Although graphene itself lacks intrinsic piezoelectricity, its integration with piezoelectric substrates can augment the performance of piezoelectric biosensors. In electrochemical sensing, graphene-based electrodes support rapid electron transfer, enabling fast response times across a range of techniques, including impedance spectroscopy, amperometry, and voltammetry. Graphene field-effect transistors (GFETs), which leverage graphene’s high carrier mobility, offer real-time, label-free, and highly sensitive detection of biomolecules. In addition, the review also explores multiplexed detection strategies vital for point-of-care diagnostics. Graphene’s nanoscale dimensions and tunable surface chemistry facilitate both array-based configurations and the simultaneous detection of multiple biomarkers. This adaptability makes graphene an ideal material for compact, scalable, and accurate biosensor platforms. Continued advancements in graphene biofunctionalisation, sensing modalities, and integrated multiplexing are driving the development of next-generation biosensors with superior sensitivity, selectivity, and diagnostic reliability. Full article

Foodborne pathogenic bacteria critically threaten public health and food industry sustainability, serving as a predominant trigger of food contamination incidents. To mitigate these risks, the development of rapid, sensitive, and highly specific detection technologies is essential for early warning and effective control of foodborne diseases. In recent years, biosensors have gained prominence as a cutting-edge tool for detecting foodborne pathogens, owing to their operational simplicity, rapid response, high sensitivity, and suitability for on-site applications. This review provides a comprehensive evaluation of critical biorecognition elements, such as antibodies, aptamers, nucleic acids, enzymes, cell receptors, molecularly imprinted polymers (MIPs), and bacteriophages. We highlight their design strategies, recent advancements, and pivotal contributions to improving detection specificity and sensitivity. Additionally, we systematically examine mainstream biosensor-based detection technologies, with a focus on three dominant types: electrochemical biosensors, optical biosensors, and piezoelectric biosensors. For each category, we analyze its fundamental principles, structural features, and practical applications in food safety monitoring. Finally, this review identifies future research priorities, including multiplex target detection, enhanced processing of complex samples, commercialization, and scalable deployment of biosensors. These advancements are expected to bridge the gap between laboratory research and real-world food safety surveillance, fostering more robust and practical solutions. Full article

Microorganisms play a crucial role in food processes, safety, and quality through their dynamic interactions with other organisms. In recent years, biosensors have become essential tools for monitoring these processes in the dairy, meat, and fresh produce industries. This review highlights how microbial diversity, starter cultures, and interactions, such as competition and quorum sensing, shape food ecosystems. Diverse biosensor platforms, including electrochemical, optical, piezoelectric, thermal, field-effect transistor-based, and lateral flow assays, offer distinct advantages tailored to specific food matrices and microbial targets, enabling rapid and sensitive detection. Biosensors have been developed for detecting pathogens in real-time monitoring of fermentation and tracking spoilage. Control strategies, including bacteriocins, probiotics, and biofilm management, support food safety, while decontamination methods provide an additional layer of protection. The integration of new techniques, such as nanotechnology, CRISPR, and artificial intelligence, into Internet of Things systems is enhancing precision, particularly in addressing regional food safety challenges. However, their adoption is still hindered by complex food matrices, high costs, and the growing challenge of antimicrobial resistance. Looking ahead, intelligent systems and wearable sensors may help overcome these barriers. Although gaps in standardization and accessibility remain, biosensors are well-positioned to revolutionize food microbiology, linking ecological insights to practical solutions and paving the way for safer, high-quality food worldwide. Full article

This work presents the theoretical design and finite element modeling of high-sensitivity microcantilevers for biosensing applications, integrating piezoelectric actuation with novel ultrananocrystalline diamond (UNCD) structures. Microcantilevers were designed based on projections to grow a multilayer metal/AlN/metal/UNCD stack on silicon substrates, optimized to detect adsorption of biomolecules on the surface of exposed UNCD microcantilevers at the picogram scale. A central design criterion was to match the microcantilever’s eigenfrequency with the resonant frequency of the AlN-based piezoelectric actuator, enabling efficient dynamic excitation. The beam length was tuned to ensure a ≥2 kHz resonant frequency shift upon adsorption of 1 pg of mass distributed on the exposed surface of a UNCD-based microcantilever. Subsequently, a Gaussian distribution mass function with a variance of 5 µm was implemented to evaluate the resonant frequency shift upon mass addition at a certain point on the microcantilever where a variation from 600 Hz to 100 Hz was observed when the mass distribution center was located at the tip of the microcantilever and the piezoelectric borderline, respectively. Both frequency and time domain analyses were performed to predict the resonance behavior, oscillation amplitude, and quality factor. To ensure the reliability of the simulations, the model was first validated using experimental results reported in the literature for an AlN/nanocrystalline diamond (NCD) microcantilever. The results confirmed that the AlN/UNCD architecture exhibits higher resonant frequencies and enhanced sensitivity compared to equivalent AlN/Si structures. The findings demonstrate that using a UNCD-based microcantilever not only improves biocompatibility but also significantly enhances the mechanical performance of the biosensor, offering a robust foundation for the development of next-generation MEMS-based biochemical detection platforms. The research reported here introduces a novel design methodology that integrates piezoelectric actuation with UNCD microcantilevers through eigenfrequency matching, enabling efficient picogram-scale mass detection. Unlike previous approaches, it combines actuator and cantilever optimization within a unified finite element framework, validated against experimental data published in the literature for similar piezo-actuated sensors using materials with inferior biocompatibility compared with the novel UNCD. The dual-domain simulation strategy offers accurate prediction of key performance metrics, establishing a robust and scalable path for next-generation MEMS biosensors. Full article

Electroactive polymers (EAPs) have emerged as versatile materials for self-powered actuators and biosensors, revolutionizing biomedical diagnostics and healthcare technologies. These materials harness various energy harvesting mechanisms, including piezoelectricity, triboelectricity, and ionic conductivity, to enable real-time, energy-efficient, and autonomous sensing and actuation without external power sources. This review explores recent advancements in EAP-based self-powered systems, focusing on their applications in biosensing, soft robotics, and biomedical actuation. The integration of nanomaterials, flexible electronics, and wireless communication technologies has significantly enhanced their sensitivity, durability, and multifunctionality, making them ideal for next-generation wearable and implantable medical devices. Additionally, this review discusses key challenges, including material stability, biocompatibility, and optimization strategies for enhanced performance. Future perspectives on the clinical translation of EAP-based actuators and biosensors are also highlighted, emphasizing their potential to transform smart healthcare and bioelectronic applications. Full article

Various high-throughput screening methods have been developed to explore plant phenotypes, primarily at the organ and whole plant levels. There is a need to develop phenomics methods at the cellular level to narrow down the genotype to phenotype gap. This study used double-resonator piezoelectric cytometry biosensors to capture the dynamic changes in mechanical phenotypes of living cells of two rice species, drought-resistant Lvhan No. 1 and drought-sensitive 6527, under PEG6000 drought stress. In rice cells of Lvhan No. 1 and 6527, mechanomics parameters, including cell-generated surface stress (ΔS) and viscoelastic parameters (G′, G″, G″/G′), were measured and compared under 5–25% PEG6000. Lvhan No. 1 showed larger viscoelastic but smaller surface stress changes with the same concentration of PEG6000. Moreover, Lvhan No. 1 cells showed better wall–plasma membrane–cytoskeleton continuum structure maintaining ability under drought stress, as proven by transient tension stress (ΔS > 0) and linear G′~ΔS, G″~ΔS relations at higher 15–25% PEG6000, but not for 6527 cells. Additionally, two distinct defense and drought resistance mechanisms were identified through dynamic G″/G′ responses: (i) transient hardening followed by softening recovery under weak drought, and (ii) transient softening followed by hardening recovery under strong drought. The abilities of Lvhan No. 1 cells to both recover from transient hardening to softening and to recover from transient softening to hardening are better than those of 6527 cells. Overall, the dynamic mechanomics phenotypic patterns (ΔS, G′, G″, G″/G′, G′~ΔS, G″~ΔS) verified that Lvhan No. 1 has better drought resistance than that of 6527, which is consistent with the field data. Full article

This article explores the development and application of innovative piezoelectric sensors in point-of-care diagnostics. It highlights the significance of bedside tests, such as lateral flow and electrochemical tests, in providing rapid and accurate results directly at the patient’s location. This paper delves into the principles of piezoelectric assays, emphasizing their ability to detect disease-related biomarkers through mechanical stress-induced electrical signals. Various applications of piezoelectric chemosensors and biosensors are discussed, including their use in the detection of cancer biomarkers, pathogens, and other health-related analytes. This article also addresses the integration of piezoelectric materials with advanced sensing technologies to improve diagnostic accuracy and efficiency, offering a comprehensive overview of current advances and future directions in medical diagnostics. Full article