Search Results (391)

Clusterin plays an important role in carcinogenesis and serves as an important diagnostic biomarker of various clinical conditions. This work describes an application of a surface-enhanced Raman scattering (SERS)-based immunoassay using Al foil substrate that has the potential for the detection of clusterin. We first optimized the parameters of the assay using anti-human IgG/human IgG (hIgG) as a model antibody/antigen system using various substrates based on Au film, Si, Al tape and Al foil. Among the tested substrates, Al foil exhibited better performance, when assay of human IgG on Al foil demonstrated a detection limit of 2 pM and a semi logarithmic trend range from 10 pM to 1000 pM. Afterwards, the same SERS immunoassay method was implemented for detection of clusterin and resulted in a good semi-logarithmic calibration line with a high R² value of 0.99, which was obtained in the range from 1 ng/mL to 1000 ng/mL. The low detection limit for clusterin antigen was found to be 3 ng/mL, which is better than most LODs for clusterin reported in the literature and also nearly 4 orders of magnitude lower than possible concentrations of clusterin in human blood. Moreover, the assay requires a relatively low volume of sample (10 μL). Overall, the assay performance demonstrates the significant potential of SERS on Al foil as a low-cost/high-availability substrate for sensing and biosensing, including detection of cancer biomarkers. Full article

A novel, cost-effective, label-free biosensing strategy has been established for real-time quantification of alkaline phosphatase (ALP) activity, integrating the Tyndall effect with smartphone imaging technology. This method utilizes a handheld laser diode to probe the enzyme-triggered in situ assembly of Cu-guanosine monophosphate (Cu-GMP) coordination polymers, which exhibit tunable Tyndall scattering properties. In the absence of ALP, Cu²⁺ ions chelate with GMP to form Cu-GMP coordination polymers, generating an intense Tyndall effect. Conversely, ALP-mediated hydrolysis of GMP disrupts the formation of Cu-GMP coordination polymers, resulting in diminished light scattering. The intensity of the Tyndall effect is directly proportional to the concentration of Cu-GMP coordination polymers, which in turn correlates with ALP activity levels. A comprehensive investigation of experimental parameters was conducted, including pH, incubation temperature, GMP concentration, incubation time, synthesis duration, and CuSO₄ concentration. Under optimized conditions, the developed smartphone-assisted colorimetric assay enables the detection of ALP activity within the range of 0.375–3.75 U/mL, with a limit of detection of 0.184 U/mL. The application of this method to serum samples yielded recovery rates ranging from 102.6% to 109.0%. In summary, this smartphone-based colorimetric platform offers a portable and versatile approach for instrument-free detection of ALP activity, with potential applications in point-of-care diagnostics and resource-limited settings. Full article

Organismal biosensing leverages the olfactory acuity of living systems to detect volatile organic compounds (VOCs) associated with cancer, offering a low-cost and non-invasive complement to conventional diagnostics. Early studies demonstrate its feasibility across diverse platforms. In C. elegans, chemotaxis assays on urine samples achieved sensitivities of 87–96% and specificities of 90–95% in case–control cohorts (n up to 242), while calcium imaging of AWC neurons distinguished breast cancer urine with ~97% accuracy in a small pilot cohort (n ≈ 40). Trained canines have identified prostate cancer from urine with sensitivities of ~71% and specificities of 70–76% (n ≈ 50), and AI-augmented canine breath platforms have reported accuracies of ~94–95% across ~1400 participants. Insects such as locusts and honeybees enable ultrafast neural decoding of VOCs, achieving 82–100% classification accuracy within 250 ms in pilot studies (n ≈ 20–30). Collectively, these platforms validate the principle that organismal behavior and neural activity encode cancer-related VOC signatures. However, limitations remain, including small cohorts, methodological heterogeneity, and reliance on binary outputs. This review proposes a Dual-Pathway Framework, where Pathway 1 leverages validated indices (e.g., the Chemotaxis Index) for high-throughput screening, and Pathway 2 applies machine learning to high-dimensional behavioral vectors for cancer subtyping, staging, and monitoring. By integrating these approaches, organismal biosensing could evolve from proof-of-concept assays into clinically scalable precision diagnostics. Full article

Diabetes has become a global health challenge, driving the demand for innovative, non-invasive diagnostic technologies to improve glucose monitoring. Urinary glucose concentration, a reliable indicator of metabolic changes, provides a practical alternative for frequent monitoring without the discomfort of invasive methods. In this simulation-based study, we propose a novel asymmetric photonic structure that integrates Tamm plasmon polariton (TPP) modes and a cavity mode for high-precision refractive index sensing, with a conceptual focus on the potential detection of urinary glucose. The structure supports three distinct resonance modes, each with unique field localization. Both the TPP modes, confined at the metallic–dielectric interfaces, serve as stable references whose wavelengths are unaffected by refractive-index variations in human urine, whereas the cavity mode exhibits a redshift with increasing refractive index, enabling high responsiveness to analyte changes. The evaluation of sensing performance employs a sensitivity formulation that leverages either TPP mode as a reference and the cavity mode as a probe, thereby achieving dependable measurement and spectral stability. The optimized design achieves a sensitivity of 693 nm·RIU⁻¹ and a maximum figure of merit of 935 RIU⁻¹, indicating high detection resolution and spectral sharpness. The device allows both reflectance and transmittance measurements to ensure enhanced versatility. Moreover, the coupling between TPP and cavity modes demonstrates hybrid resonance, empowering applications such as polarization-sensitive or angle-dependent filtering. The figure of merit is analyzed further, considering resonance wavelength shifts and spectral sharpness, thus manifesting the structure’s robustness. Although this study does not provide experimental data such as calibration curves, recovery rates, or specificity validation, the proposed structure offers a promising conceptual framework for refractive index-based biosensing in human urine. The findings position the structure as a versatile platform for advanced photonic systems, offering precision, tunability, and multifunctionality beyond the demonstrated optical sensing capabilities. Full article

Among the many nanomaterials studied for biomedical uses, silica and gold nanoparticles have gained significant attention because of their unique physical and chemical properties and their compatibility with living tissues. Mesoporous silica nanoparticles (MSNs) have great stability and a large surface area, while gold nanoparticles (AuNPs) display remarkable optical features. Both types of nanoparticles have been widely researched for their individual roles in drug delivery, imaging, biosensing, and therapy. When combined with gadolinium (Gd), a common contrast agent, these nanostructures provide improved imaging due to gadolinium’s strong paramagnetic properties. This study focuses on incorporating gold nanoparticles and gadolinium into a silica matrix to develop a theranostic system. Various analytical techniques were used to characterize the nanocomposites, including infrared spectroscopy (FTIR), ultraviolet-visible spectroscopy (UV-Vis), thermogravimetric analysis (TGA), nitrogen adsorption, scanning electron microscopy (SEM), dynamic light scattering (DLS), X-ray fluorescence (XRF), X-ray diffraction (XRD), vibrating sample magnetometry (VSM), and neutron activation analysis (NAA). Techniques like XRF mapping, XANES, nitrogen adsorption, SEM, and VSM were crucial in confirming the presence of gadolinium and gold within the silica network. VSM and EPR analyses confirmed the attenuation of the saturation magnetization for all nanocomposites. This validates their potential for biomedical applications in diagnostics. Moreover, activating gold nanoparticles in a nuclear reactor generated a promising radioisotope for cancer treatment. These results indicate the potential of using a theranostic nanoplatform that employs mesoporous silica as a carrier, gold nanoparticles for radioisotopes, and gadolinium for imaging purposes. Full article

Recent advances in computational tools, particularly machine learning (ML), deep learning (DL), and structure-based modeling, are transforming aptamer research by accelerating discovery and enhancing biosensor development. This review synthesizes progress in predictive algorithms that model aptamer–target interactions, guide in silico sequence optimization, and streamline design workflows for both laboratory and point-of-care diagnostic platforms. We examine how these approaches improve key aspects of aptasensor development, such as aptamer selection, sensing surface immobilization, signal transduction, and molecular architecture, which contribute to greater sensitivity, specificity, and real-time diagnostic capabilities. Particular attention is given to illuminating the technological and experimental advances in structure-switching aptamers, dual-aptamer systems, and applications in electrochemical, optical, and lateral flow platforms. We also discuss current challenges such as the standardization of datasets and interpretability of ML models and highlight future directions that will support the translation of aptamer-based biosensors into scalable, point-of-care and clinically deployable diagnostic solutions. Full article

Smartphone-based biosensors are emerging as transformative tools for personalized medicine and real-time health monitoring. This study critically examines recent advancements in mass-sensitive, optical, and electrochemical biosensing technologies, highlighting their application in detecting disease biomarkers. Beyond a summary of technological progress, this paper presents a strategic roadmap that addresses persistent barriers to clinical deployment, including sensor calibration inconsistencies, lack of interoperability, and limited scalability. The proposed framework leverages explainable artificial intelligence (AI) for enhanced diagnostic interpretation and outlines pathways for low-cost, scalable manufacturing using advanced nanomaterials. By bridging technical innovation with practical implementation, this work contributes a replicable model for developing equitable, reliable smartphone biosensors capable of expanding access to preventive and individualized healthcare worldwide. Full article

Matrix metalloproteinases (MMPs) are a class of extracellular Zn²⁺ peptidases involved in various physiological and pathological processes. These enzymes serve as excellent biomarkers for diagnosing various diseases, including cancer and periodontitis, to name a few. MMP levels also serve as a prognostic marker, which helps determine how much the disease has progressed. However, the current methods used to detect MMPs need a large sample volume, carry a high cost, and are not widely accessible to the public due to these challenges. Biosensing techniques tackle these problems by providing an efficient, cost-effective sensor with great sensitivity. This review provides a comprehensive overview of the latest developments and advancements in detecting MMPs using biosensors that employ various detection mechanisms such as electrochemical, colorimetric, and fluorescence methods. Furthermore, we have discussed the challenges and prospects of using MMPs as diagnostic tools. Full article

Alzheimer’s disease (AD) is the neurodegenerative condition with the outmost future challenges, with timely diagnosis and treatment being the most urgent. Discovery of more and more biomarkers is widely attempted; however, current diagnostic methods often lack sensitivity, specificity, and accessibility. Nucleotide aptamers—short, highly specific oligonucleotide or ligands—are now recognized as highly promising molecular agents for both measuring and targeting key AD biomarkers, with the most notorious being amyloid-beta (Aβ), tau protein, and disease-associated microRNAs (miRNAs). This review provides a comprehensive analysis of nucleotide aptamers related to AD, detailing their mechanisms of selection, recent advances in biosensing applications, and therapeutic potential. Aptamers, targeting the most significant biomarkers of AD, are mainly discussed, as well as ones interacting with novel, promising biomarkers, with a special aim on miRNAs. Additionally, aptamers are compared with conventional antibody-based approaches, highlighting their advantages in terms of stability, cost-effectiveness, and ease of modification. By elucidating the role of aptamers in AD diagnosis and treatment, this review underscores their promise as next-generation tools for precision medicine and neurodegenerative disease management. Full article

Optimal sensing devices exhibit a combination of key performance attributes, including an extensive detection limit, exceptional selectivity, high sensitivity, consistent repeatability, precise measurement, and rapid response times with efficient analyte flow. In recent years, biosensing platforms incorporating nanoscale materials have garnered considerable attention due to their diverse applications across various scientific and technological domains. The integration of nanoparticles (NPs) in biosensor design primarily bridges the dimensional gap between the signal transduction element and the biological recognition component, both of which operate at nanometer scales. The synergistic combination of NPs with electrochemical techniques has facilitated the development of biosensors characterized by enhanced sensitivity and superior analyte discrimination capabilities. This comprehensive analysis examines the evolution and recent advancements in nanomaterial (NM)-based biosensors, encompassing an extensive array of nanostructures. These consists of one-dimensional nanostructures including carbon nanotubes (CNTs), nanowires (NWs), nanorods (NRs), and quantum dots (QDs), as well as noble metal and metal and metal oxide nanoparticles (NPs). The article examines how advancements in biosensing techniques across a range of applications have been fueled by the growth of nanotechnology. Researchers have significantly improved biosensor performance parameters by utilizing the distinct physiochemical properties of these NMs. The developments have increased the potential uses of nanobiosensors in a wide range of fields, from food safety and biodefense to medical diagnostics and environmental monitoring. The continuous developments in NM-based biosensors are the result of the integration of several scientific areas, such as analytical chemistry, materials science, and biotechnology. This interdisciplinary approach continues to drive innovations in sensor design, signal amplification strategies, and data analysis techniques, ultimately leading to more sophisticated and capable biosensing platforms. As the field progresses, challenges related to the scalability, reproducibility, and long-term stability of nanobiosensors are being addressed through innovative fabrication methods and surface modification techniques. These efforts aim to translate the promising results observed in laboratory settings into practical, commercially viable biosensing devices that can address real-world analytical challenges across various sectors. Full article

The rapid evolution of CRISPR technology has revolutionized molecular biology, and among the various systems, CRISPR/Cas12a stands out for its high specificity and efficient collateral cleavage activity. This review article focuses on the recent advancements and applications of split technology within the CRISPR/Cas12a framework, highlighting its transformative role in molecular diagnostics and biosensing. Split technology innovatively divides functional nucleic acid components into modular segments that are activated by specific targets, significantly enhancing the specificity and sensitivity of biosensors. This design addresses the inherent limitations of traditional sensor systems, enabling the direct detection of ultrashort nucleic acids and improved discrimination of single-nucleotide variants, thereby facilitating the simultaneous detection of multiple biomolecules. The versatility of split-enabled biosensors extends beyond genetic testing, making them valuable tools in diagnostics, therapeutics, and environmental science. Despite challenges such as crRNA degradation and reassembly kinetics, ongoing research and engineering solutions continue to enhance the stability and performance of these systems. This review synthesizes the foundational principles, recent advancements, and potential applications of split technology while also identifying challenges and opportunities for future exploration. Ultimately, our insights provide a comprehensive resource to leverage the full potential of CRISPR/Cas12a-based split technology in advancing biosensing methodologies and clinical applications. Full article

AuQDs (Au quantum dots) are ultrasmall nanostructures that combine the size-tunable fluorescence and photostability of semiconductor quantum dots with the chemical stability, low toxicity, and versatile surface chemistry of gold nanoparticles. This unique combination endows AuQDs with exceptional biocompatibility and multifunctionality, making them ideal for biomedical applications such as cellular imaging, real-time tracking, targeted drug delivery, diagnostics, therapeutic monitoring, and biosensing. Various synthesis methods—including chemical reduction, hydrothermal, laser ablation, and microwave-assisted techniques—allow for precise control over size and surface properties, optimizing fluorescence and electronic behavior for high-resolution imaging and sensitive detection. Compared to traditional quantum dots, AuQDs offer enhanced safety and biocompatibility, while surpassing larger gold nanoparticles by enabling fluorescence-based imaging. Their surfaces can be functionalized with diverse ligands for targeted delivery and specific biological interactions. In summary, AuQDs are multifunctional nanoprobes that combine superior optical properties, chemical stability, and biocompatibility, making them powerful tools for advanced biomedical diagnostics, therapy, and biosensing. 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

Background: Chronic kidney disease (CKD) is a progressive global health burden often diagnosed in late stages due to reliance on invasive and centralized blood and urine tests. Saliva, as a non-invasive diagnostic fluid, has emerged as a promising alternative for assessing renal function. This scoping review aims to evaluate the diagnostic accuracy of salivary biomarkers compared to traditional methods, and to explore the potential of emerging biosensing technologies for CKD detection and monitoring. Methods: A comprehensive literature search was conducted in PubMed/MEDLINE, Scopus, Web of Science, and Cochrane Library up to 1 July 2025, following the PRISMA-ScR guidelines. Studies involving adult CKD patients and healthy controls that assessed the diagnostic performance of salivary biomarkers against validated reference standards (e.g., serum creatinine, eGFR) were included. A total of 29 eligible studies were selected after applying predefined inclusion and exclusion criteria. Results: Salivary creatinine and urea were the most frequently assessed biomarkers and demonstrated strong correlations with serum levels (AUCs up to 1.00; sensitivity and specificity frequently >85%). Several studies reported high diagnostic potential for novel salivary markers such as Trimethylamine N-oxide (TMAO), cystatin C, and amino acids. Technological innovations, including electrochemical biosensors and ATR-FTIR spectroscopy, showed promise for enhancing sensitivity and enabling point-of-care testing. However, heterogeneity in sampling protocols and limited data for early-stage CKD were notable limitations. Conclusions: Salivary diagnostics, supported by biosensor technologies, offer a feasible and non-invasive alternative for CKD screening and monitoring. Standardization, broader clinical validation, and integration into dental workflows are key to clinical implementation. Full article

The integration of deep learning (DL) and nanozyme-based biosensing has emerged as a transformative strategy for next-generation medical diagnostics. This review explores how DL architectures enhance nanozyme design, functional optimization, and predictive modeling by elucidating catalytic mechanisms such as dual-atom active sites and substrate-surface interactions. Key applications include disease biomarker detection, medical imaging enhancement, and point-of-care diagnostics aligned with the ASSURED criteria. In clinical contexts, advances such as wearable biosensors and smart diagnostic platforms leverage DL for real-time signal processing, pattern recognition, and adaptive decision-making. Despite significant progress, challenges remain—particularly the need for standardized biomedical datasets, improved model robustness across diverse populations, and the clinical translation of artificial intelligence (AI)-enhanced nanozyme systems. Future directions include integration with the Internet of Medical Things, personalized medicine frameworks, and sustainable sensor development. The convergence of nanozymes and DL offers unprecedented opportunities to advance intelligent biosensing and reshape precision diagnostics in healthcare. Full article