Search Results (96)

Quantum biosensors offer a promising route to overcome the sensitivity and specificity limitations of conventional biosensing technologies. Their ability to detect biochemical signals at extremely low concentrations makes them strong candidates for next-generation sensing systems. This paper reviews the current state of quantum biosensors and discusses their future implementation in chip-scale platforms that combine microelectronic and photonic technologies. It covers key quantum biosensing approaches including quantum dots (QDs), and nitrogen-vacancy (NV) centers. This paper also considers their potential compatibility with electronic integrated circuits (EICs), photonic integrated circuits (PICs) and integrated quantum photonic (IQP) systems for future biosensing applications. To our knowledge, this is the first review to systematically connect quantum biosensing technologies with the development of microelectronic and photonic chip-based devices. The goal is to clarify the technological trajectory toward compact, scalable, and high-performance quantum biosensing systems. Full article

A novel airborne pathogen detection method, based on Flashing Ratchet Potential (FRP) and Electric Current Spectroscopy (ECS), is presented. The system employs a precisely engineered asymmetric electrode array to generate controlled directional transport of oxygen ions (O₂⁻•), produced via thermionic emission and three-body electron attachment. As these ions interact with airborne particles in the detection zone, measurable perturbations in the ECS profile emerge, yielding distinct spectral signatures that indicate particle presence. Proof-of-concept experiments, using standardized talcum powder aerosols as surrogates for viral-scale particles, established optimal operating parameters of 6 V potential and 600 kHz modulation frequency, with reproducible detection signals showing a relative shift of 4.5–13.4% compared to filtered-air controls. The system’s design concept incorporates humidity-resilient features, intended to maintain stability under varying environmental conditions. Together with the proposed size selectivity (50–150 nm), this highlights its potential robustness for real-world applications. To the best of our knowledge, this is the first demonstration of an open-air electro-ratchet transport system coupled with electric current spectroscopy for bioaerosol monitoring, distinct from prior optical or electrochemical airborne biosensors, highlighting its promise as a tool for continuous environmental surveillance in high-risk settings such as hospitals, airports, and public transit systems. Full article

With the increase in contamination by microbial agents (bacteria, viruses, etc.) in the fields of agri-food, healthcare, and environment, it is necessary to detect and quantify these biological elements present in complex fluids in a short time with high selectivity, high sensitivity, and, if possible, moderate cost. Acoustic wave biosensors, based on immuno-detection, appear to meet a certain number of these criteria. In this context, we are developing a generic antibody-based biointerface that can detect a wide range of pathogenic bacterial agents using a specific bioreceptor. Based on the silane–oxide chemistry, the process is transferable to any kind of surface that can be either oxidized in surface or activated with O₂-plasma, for instance. For this proof of concept, we have chosen to develop our biointerface on titanium and lithium niobate surfaces. The development of the biointerface consists of grafting antibodies via a self-assembled monolayer (SAM) composed of an aminopropyltriethoxysilane (APTES) and a linker (phenylene diisothiocyanate, PDITC). Two functionalization routes were tested for grafting APTES: in anhydrous toluene followed by a heating step at 110 °C or in chloroform at room temperature. The results obtained on titanium show comparable grafting efficiency between these two routes, allowing us to consider the transposition of the route at room temperature on lithium niobate. The latest route was chosen for fragile materials that do not require the heating steps necessary when using toluene for grafting aminopropyltriethoxysilane. Different surface characterization techniques were used, such as IR spectroscopy (FTIR-ATR), X-ray photoelectron spectroscopy (XPS), and contact angle (WCA), to verify the successful grafting of each layer. Biodetection experiments in static conditions were also carried out to demonstrate the specificity of pathogenic detection, testing an ideal medium with solely bacteria, with no other food sampling nutrients. This paper demonstrates the successful elaboration of a biointerface using APTES as the first anchoring layer, with chloroform as a mild solvent. The process is easily transferable to any kind of fragile surface. Moreover, following anti-L. monocytogenes antibodies, our biointerface shows a specificity of capture in static mode (at a concentration of 10⁷ CFU/mL for an incubation time of 4 h at 37 °C) of up to 98% compared to a species negative control (E. coli) and up to 85% in terms of strain specificity (L. innocua). Full article

Printed flexible materials have garnered considerable attention as next-generation materials for bioelectronic applications, particularly hydrogels and elastomers, owing to their intrinsic softness, tissue-like mechanical compliance, and electrical conductivity. In contrast to conventional fabrication approaches, printing technologies enable precise spatial control, design versatility, and seamless integration with complex biological interfaces. This review provides a comprehensive overview of the progress in printable soft conductive materials, with a particular emphasis on the composition, processing, and functional roles of conductive hydrogels and elastomers. This review first introduces traditional fabrication methods for conductive materials and explains the motivation for using printing techniques. We then introduce two major classes of soft conductive materials, hydrogels and elastomers, and describe their applications in both in vitro systems, such as biosensors and soft stimulators, and in vivo settings, including neural interfaces and implantable devices. Finally, we discuss current challenges and propose future directions for advancing printed soft bioelectronics toward clinical translation. Full article

This work describes a non-enzymatic electrochemical glucose biosensor combining for the first time molecularly imprinted polymers (MIPs) for glucose concentration and gold nanoparticles (AuNPs) on screen-printed carbon electrodes (SPEs), where both MIPs and AuNPs were assembled in situ. Electrochemical impedance spectroscopy (EIS) was used to evaluate the analytical performance of the sensor, which has a linear range between 1.0 µM and 1.0 mM when standard solutions are prepared in buffer. Direct measurement of glucose was performed by chronoamperometry, measuring the oxidation current generated during direct glucose oxidation. The selectivity was tested against ascorbic acid and the results confirmed a selective discrimination of the electrode for glucose. Overall, the work presented here represents a promising tool for tracking glucose levels in serum. The use of glucose MIP on the electrode surface allows the concentration of glucose, resulting in lower detection limits, and the use of AuNPs reduces the potential required for the oxidation of glucose, which increases selectivity. In addition, this possible combination of two analytical measurements following different theoretical concepts can contribute to the accuracy of the analytical measurements. This combination can also be extended to other biomolecules that can be electrochemically oxidised at lower potentials. Full article

The COVID-19 pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), catalyzed unprecedented innovation in molecular diagnostics to address critical gaps in rapid pathogen detection. Over the past five years, CRISPR-based systems, isothermal amplification techniques, and portable biosensors have emerged as transformative tools for nucleic acid detection, offering improvements in speed, sensitivity, and point-of-care applicability compared to conventional PCR. While numerous reviews have cataloged the technical specifications of these platforms, a critical gap remains in understanding the strategic and economic hurdles to their real-world implementation. This review provides a forward-looking analysis of the feasibility, scalability, and economic benefits of integrating these next-generation technologies into future pandemic-response pipelines. We synthesize advances in coronavirus-specific diagnostic platforms and attempt to highlight the need for their implementation as a cost-saving measure during surges in clinical demand. We evaluate the feasibility of translating these technologies—particularly CRISPR-Cas integration with recombinase polymerase amplification (RPA)—into robust first-line diagnostic pipelines for novel viral threats. By analyzing the evolution of diagnostic strategies during the COVID-19 era, we aim to provide strategic insights and new directions for developing and deploying effective detection platforms to better confront future viral pandemics. Full article

Artificial intelligence (AI) techniques have propelled biomedical sensors beyond measuring physiological markers to interpreting subjective states like stress, pain, or emotions. Despite these technological advances, user trust is not guaranteed and is inadequately addressed in extant research. This review proposes the Cognition–Context–Contrast (CCC) conceptual framework to explain the trust and acceptance of AI-enabled sensors. First, we map cognition, comprising the expectations and stereotypes that humans have about machines. Second, we integrate task context by situating sensor applications along an intellective-to-judgmental continuum and showing how demonstrability predicts tolerance for sensor uncertainty and/or errors. Third, we analyze contrast effects that arise when automated sensing displaces familiar human routines, heightening scrutiny and accelerating rejection if roll-out is abrupt. We then derive practical implications such as enhancing interpretability, tailoring data presentations to task demonstrability, and implementing transitional introduction phases. The framework offers researchers, engineers, and clinicians a structured conceptual framework for designing and implementing the next generation of AI biosensors. Full article

Rapid screening of foodborne pathogens is critical for food safety, yet current detection techniques often suffer from low efficiency and complexity. In this study, we developed a sliding microfluidic colorimetric biosensor for the fast, sensitive, and multiplex detection of Salmonella. First, the target bacteria were specifically captured by antibody-functionalized magnetic nanoparticles in the microfluidic chip, forming magnetic bead–bacteria complexes. Then, through motor-assisted sliding of the chip, manganese dioxide (MnO₂) nanoflowers conjugated with secondary antibodies were introduced to bind the captured bacteria, generating a dual-antibody sandwich structure. Finally, a second sliding step brought the complexes into contact with a chromogenic substrate, where the MnO₂ nanoflowers catalyzed a colorimetric reaction, and the resulting signal was used to quantify the Salmonella concentration. Under optimized conditions, the biosensor achieved a detection limit of 10 CFU/mL within 20 min. In spiked pork samples, the average recovery rate of Salmonella ranged from 94.9% to 125.4%, with a coefficient of variation between 4.0% and 6.8%. By integrating mixing, separation, washing, catalysis, and detection into a single chip, this microfluidic biosensor offers a user-friendly, time-efficient, and highly sensitive platform, showing great potential for the on-site detection of foodborne pathogens. 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

The COVID-19 pandemic highlighted the need for rapid, cost-effective tools to monitor transmission and immune response. We developed two novel paper-based colorimetric biosensors using glutaraldehyde as a protein dye—its first use in this context. Glutaraldehyde reacts with amino groups to generate a brown color, enabling detection of SARS-CoV-2 antibodies. Wathman filter paper was functionalized with (3-aminopropyl)triethoxysilane (APTES) to immobilize virus-like particles (VLPs) and nucleocapsid protein (N-protein) as biorecognition elements. Upon incubation with antibody-containing samples, glutaraldehyde enabled colorimetric detection using RGB analysis in ImageJ software. Both sensors showed a linear correlation between antibody concentration and RGB values in buffer and serum. The VLP sensor responded linearly within the range of 1.0–20 µg/mL (green coordinate) in 500-fold diluted serum and the N-protein sensor from 1.0–40 µg/mL (blue coordinate) in 250-fold diluted serum. Both sensors demonstrated good selectivity, with glucose causing up to 18% interference. These biosensors represent a paradigm shift, as they provide a sensitive, user-friendly, and cost-effective option for semi-quantitative serological analysis. Furthermore, their versatility goes beyond the detection of SARS-CoV-2 antibodies and suggests broader applicability for various molecular targets. Full article

B Cell Maturation Antigen (BCMA) has gained considerable attention as a target in directed therapies for multiple myeloma (MM) treatment, via immunoglobulin-based bispecific T cell engagers or CAR T cell strategies. We describe the development of alternative, non-immunoglobulin BCMA-recognising affinity proteins, based on the small (58 aa) three-helix bundle affibody scaffold. A first selection campaign using a naïve affibody phage library resulted in the isolation of several BCMA-binding clones with different kinetic profiles. One clone showing the slowest dissociation kinetics was chosen as the template for the construction of two second-generation libraries. Characterization of output clones from selections using these libraries led to the identification of clone 1-E6, which demonstrated low nM affinity to BCMA and high thermal stability. Biosensor experiments showed that 1-E6 interfered with the binding of BCMA to both its natural ligand APRIL and to the clinically evaluated anti-BCMA monoclonal antibody belantamab, suggesting overlapping epitopes. A fluorescently labelled head-to-tail homodimer construct of 1-E6 showed specific binding to the BCMA⁺ MM.1s cell line in both flow cytometry and fluorescence microscopy. Taken together, the results suggest that the small anti-BCMA affibody 1-E6 could be an interesting alternative to antibody-based affinity units in the development of BCMA-targeted therapies and diagnostics. Full article

Brain glioma is one of the most common malignant tumors of brain tissue. It is characterized by rich vascularization, which indicates the significant participation of angiogenesis in its growth and development. In its first stages, the disease is very often asymptomatic, and late diagnosis significantly limits possibilities of treatment. Tumor angiogenesis, i.e., the formation of new vessels, requires the presence of angiogenic compounds that will enable tumor progression by creating a path for the supply of nutrients. The proangiogenic compounds involved in the development of glioma include hypoxia-inducible factor 1α (HIF-1α), angiopoietin-2 (ANG-2), and interleukin-1β (IL-1β). The aim of this study was to analyze changes in the levels of these proteins in plasma samples of patients diagnosed with brain glioma in stages G1 to G4, and in a control group, using SPRi biosensors. The results obtained in plasma were compared with the concentrations obtained during the analysis of tissue homogenates from patients with glioma in stages G2 to G4. A statistically significant difference in plasma concentrations was obtained between the patient group and the control group. The concentrations of the markers in tissue homogenate samples were statistically higher than in blood plasma. There was no significant effect of gender, diet, smoking, or the patient’s general health condition (Karnofsky score) on the course of the disease. These factors do not directly increase the risk of developing brain glioma. Full article

Medical biosensors have set the basis of medical diagnostics, and Artificial Intelligence (AI) has boosted diagnostics to a great extent. However, false results are evident in every method, so it is crucial to identify the reasons behind a possible false result in order to control its occurrence. This is the first critical state-of-the-art review article to discuss all the commonly used biosensor types and the reasons that can give rise to potential false results. Furthermore, AI is discussed in parallel with biosensors and their misdiagnoses, and again some reasons for possible false results are discussed. Finally, an expert opinion with further future perspectives is presented based on general expert insights, in order for some false diagnostic results of biosensors and AI biosensors to be surpassed. Full article

A personal glucose meter (PGM) is a medical device that measures blood glucose levels and can be found worldwide. Owing to their sensitivity, simplicity, portability, and low cost, PGMs stand as one of the most frequently utilized analytical methods. This work reviews the different applied methodologies for detecting analytes other than glucose employing a PGM and how it can be incorporated for point-of-care diagnosis needs. To visualize the variants, first, a classification is made according to the biorecognition elements used (aptamers, antibodies, etc.), and where the determination of different analytes is done through the glucose signal using different glucose-generating enzymes such as invertase or glucosidase. Transduction can also be based on the use of nanocarriers that generally encapsulate glucose, although it is also possible to find a combination of the two aforementioned strategies. The PGM can also be used for the direct detection of interfering substances of the biosensor, such as NADH or paracetamol. Lastly, we discuss how a PGM might have been implemented to detect COVID-19 and how it could be used on a massive scale for the point-of-care diagnosis of a pandemic. Full article

Accurate human cerebrospinal fluid (CSF) dielectric parameters are critical for biological electromagnetic applications such as the electromagnetic field modelling of the human brain, the localization and intensity assessment of electrical generators in the brain, and electromagnetic protection. To detect brain damage signals during temperature changes by electrical impedance tomography (EIT), the change in CSF dielectric parameters with frequency (10 Hz–100 MHz) and temperature (17–39 °C) was investigated. A Debye model was first established to capture the complex impedance frequency and temperature characteristics. Furthermore, the receiver operating characteristic (ROC) analysis based on the dielectric parameters of normal and diseased CSF was carried out to identify lesions. The Debye model’s characteristic f_c parameters linearly increased with increasing temperature (R² = 0.989), and R₀ and R₁ linearly decreased (R² = 0.990). The final established formula can calculate the complex impedivity of CSF with a maximum fitting error of 3.79%. Furthermore, the ROC based on the real part of impedivity at 10 Hz and 17 °C yielded an area under the curve (AUC) of 0.898 with a specificity of 0.889 and a sensitivity of 0.944. These findings are expected to facilitate the application of electromagnetic technology, such as disease diagnosis, specific absorption rate calculation, and biosensor design. Full article