Sensor Surface Research Articles

Visible light enhanced selective benzene response of hexagonal atomic structured CuS microcloves

We have reported CuS microcloves (MCs) for highly selective detection of benzene using scanning kelvin probe (SKP) technique. The electron microscopy investigations revealed the formation of clove shaped CuS with a size of about 1–2 µm at 180 °C and 6 h. The time of reaction significantly affected the crystallinity as well as the morphology of resulting CuS materials. The investigations on adsorption behavior of different types of common volatile organic compounds (VOCs) with varying charge and nature revealed an outstanding selectivity towards benzene when compared to other VOCs. The difference in work function between gold tip and sensor surface modified with CuS MCs was decreased under the exposure of light, most likely caused by transfer of electrons to conduction band of CuS under illumination of light. As a result, the CuS MCs showed enhanced photo response in visible light exposure in the presence of benzene. A chemiresistive type sensor device was fabricated using CuS MCs and exposed to benzene vapor in a concentration ranging from 2.8 to 11.2 ppm. The sensitivity was found to be 1.63 × 10-3 ppm−1. Notably, a rapid response time of ∼6 s and recovery time of ∼ 16 s was achieved for the sensor at a benzene concentration of 5.6 ppm at room temperature. Also, considerable and repeatable sensor response was observed for 560 ppb of benzene vapor at 70 °C. Hence, these results suggested that the CuS MCs have huge potential as novel material for selective benzene detection in gas phase towards breath analysis and other environmental monitoring.

Characterization of a perfect sinusoidal grating profile using an artificial neural network for plasmonic-based sensors

In this paper, we present a system intended to detect a targeted perfect sinusoidal profile of a diffraction grating during its manufactured process. Indeed, the sinusoidal nature of the periodic structure is essential to ensure optimal efficiency of specific applications as plasmonic sensors (surface plasmon resonance -based sensors). A neural network is implemented to characterize the geometrical shape of the structure under testing at the end of the laser interference lithography process. This decision tool operates in classifier mode prior to further processing. Then, the geometrical parameters of the structure can be reliably determined if necessary. Two solutions can be considered: the detection of a fixed geometrical shape operating on a binary mode and the identification of a geometrical shape from a limited number of profiles. These methods are validated in the context of plasmonic sensors on experimental sinusoidal grating structures with a grating period of 627 nm.

A highly stable electrochemical sensor with antifouling and antibacterial capabilities for mercury ion detection in seawater

The monitoring of heavy metal ions in ocean is crucial for environment protection and assessment of seawater quality. However, the detection of heavy metal ions in seawater with electrochemical sensors, especially for long-term monitoring, always faces challenges due to marine biofouling caused by the nonspecific adsorption of microbial and biomolecules. Herein, an electrochemical aptasensor, integrating both antifouling and antibacterial properties, was developed for the detection of Hg2+ in the ocean. In this electrochemical aptasensor, eco-friendly peptides with superior hydrophilicity served as anti-biofouling materials, preventing nonspecific adsorption on the sensing interface, while silver nanoparticles were employed to eliminate bacteria. Subsequently, a ferrocene-modified aptamer was employed for the specific recognition of Hg2+, leveraging the aptamer's ability to fold into a thymine-Hg2+-thymine (T-Hg2+-T) structure upon interaction, and bringing ferrocene nearer to the sensor surface, significantly amplifying the electrochemical response. The prepared electrochemical aptasensor significantly reduced the nonspecific adsorption in seawater while maintaining sensitive electrochemical response. Furthermore, the biosensor exhibited a linear response range of 0.01–100 nM with a detection limit of 2.30 pM, and realized the accurate monitoring of mercury ions in real marine environment. The research results offer new insights into the preparation of marine antifouling sensing devices, and it is expected that sensors with antifouling and antimicrobial capabilities will find broad applications in the monitoring of marine pollutants.

Ammonia-trapping multilayer polymer urease film amplifier coated surface plasmon resonance sensor for ultra-sensitive urea detection

In this paper, we have developed a new urea signal amplification technology based on a multilayer urease polymer film self-assembly structure for the first time, enabling the realization of ultra-accurate urea optical detection. We demonstrate the effectiveness of this technique based on surface plasmon resonance (SPR) platform. When the urea signal amplifier is combined with SPR sensors, multilayer urease polymer film contacts with urea molecules, the urea molecules are oxidated into NH3 and CO2, causing the pH increase, which weakens the electrostatic interaction between different polymer layers and induces the RI reduction of the multilayer urease film, thereby causing the shift of the SPR spectrum. Experiment results confirm that urea sensitivity has been improved 12-fold, and the limit of detection (LOD) has been optimized to less than 10−3 mmol/L. Furthermore, the anti-interference has been improved 22.8-fold and is kept even the interference signal strength increases by 100 times. Moreover, multilayered urease polymer leads to the increase of urease on the sensor surface, thus expanding the detection range of urea by 3.5 times. This provides a new way to solve the contradiction between high sensitivity and large measurement range of optical fiber biosensor. Importantly, the concept of using enzyme-loaded polymer films for signal amplification can be adapted for the detection of various other biomolecules by replacing the enzyme with a specific recognition element for the target molecule. This opens doors for developing highly sensitive and specific biosensors for diverse applications in healthcare, environmental monitoring, and food safety.

Cesium ion-guided detection of trichloroethylene in air

Whereas the close associations of cesium ion with organochlorine compounds have been previously documented, the present report is the first attempt to exploit these interactions to create a trichloroethylene (TCE)-selective sensor. Gold monolayer-protected clusters peripherally functionalized with Cs+ ions were used to prepare a chemiresistance film on MEMS-fabricated interdigitated electrodes. Vapor sensing properties of the cesium-rich chemiresistor were determined using a panel of chlorinated hydrocarbons including TCE as well as polar and non-polar VOCs for comparison. The sensor was selective and highly sensitive toward VOCs containing a 1,2-dichloro group at concentrations as low as 0.1 ppm. The results suggest the key interaction contributing to sensor response is a bidentate, metallocycle-like coordination of the 1,2-dichloro group to the cesium cations at the sensor surface.

Optimized Fabrication of Carbon-Fiber Microbiosensors for Codetection of Glucose and Dopamine in Brain Tissue.

Dopamine (DA) signaling is critically important in striatal function, and this metabolically demanding process is fueled largely by glucose. However, DA and glucose are typically studied independently and, as such, the precise relationship between DA release and glucose availability remains unclear. Fast-scan cyclic voltammetry (FSCV) is commonly coupled with carbon-fiber microelectrodes to study DA transients. These microelectrodes can be modified with glucose oxidase (GOx) to generate microbiosensors capable of simultaneously quantifying real-time and physiologically relevant fluctuations of glucose, a nonelectrochemically active substrate, and DA, which is readily oxidized and reduced at the electrode surface. A chitosan hydrogel can be electrodeposited to entrap the oxidase enzyme on the sensor surface for stable, sensitive, and selective codetection of glucose and DA using FSCV. This strategy can also be used to entrap lactate oxidase on the carbon-fiber surface for codetection of lactate and DA. However, these custom probes are individually fabricated by hand, and performance is variable. This study characterizes the physical nature of the hydrogel and its effects on the acquired electrochemical data in the detection of glucose (2.6 mM) and DA (1 μM). The results demonstrate that the electrodeposition of the hydrogel membrane is improved using a linear potential sweep rather than a direct step to the target potential. Electrochemical impedance spectroscopy data relate information on the physical nature of the electrode/solution interface to the electrochemical performance of bare and enzyme-modified carbon-fiber microelectrodes. The electrodeposition waveform and scan rate were characterized for optimal membrane formation and performance. Finally, codetection of both DA/glucose and DA/lactate was demonstrated in intact rat striatum using probes fabricated according to the optimized protocol. Overall, this work improves the reliable fabrication of carbon-fiber microbiosensors for codetection of DA and important energetic substrates that are locally delivered to the recording site to meet metabolic demand.

NO2 and NH3 detection using work function measurement of solvothermal synthesised ZnO–NiO nanocomposites: a case study

Work function measurement using Kelvin probe method has been demonstrated as an effective and novel approach towards detection of NH3 and NO2 gases using ZnO–NiO based nanocomposites. For this the nanocomposites were synthesised in different compositions using the solvothermal method. Formation of ZnO–NiO nanocomposites was confirmed using XRD and EDS studies. It is found that the nanoparticle morphology of NiO changes with different percentages of Zn addition. The work function of the sensing film was found to decrease and increase upon exposure to NH3 (1.51) and NO2 (1.18) gases owing to the reducing and oxidising nature of the test gases. Of the different composites, Zn0.75Ni0.25O exhibited highest sensor response towards the test gases. The increased response is attributed to the nanostructured morphology of the nanocomposite and the formation and collapse of the p-n heterojunction formed between p-type NiO and n-type ZnO. Besides, incorporation of NiO enhances the oxygen adsorption on the sensor surface assigned to the Ni2+ ions getting readily oxidised to Ni3+. Our results clearly suggest that the work function measurements could also be used as an effective way for NO2 and NH3 detection.

The Oxidase Mimicking Activity of MnOx NPs/Co3O4 NPs Hybrid Nanozyme for Glucose Oxidation

Herein, the hybrid nanozyme MnOx NPs/Co3O4 NPs on indium tin oxide coated glass substrate (ITO) was manufactured by imparting the porous morphology with its distinct merits: its surface valence states, oxygen vacancies, large surface area, and abundant active sites. The oxidase-like activity was investigated via the catalytic oxidation of chromogenic substrate in the presence of glucose visualized by the eyes. MnOx NPs containing Mn2+ and Mn3+ have a superior ability to oxidize glucose by reducing dissolved oxygen and producing H2O2. Co3O4 NPs, in turn, reduce H2O2 with concomitant 3,3′,5,5′-tetramethylbenzidine (TMB) oxidization. Thus, the nanozyme mimics the dual roles of glucose oxidase and peroxidase. The oxidase-like activity of hybrid nanozyme for glucose was found to be higher than those of single components. The nanozyme responded to glucose with a linear range from 60 µM to 1200 μM. The acceptable performance is probably due to the facilitated access of glucose to the proximity of the sensor surface. Good reproducibility was accomplished by virtue of the meticulous construction of NPs. Without functionalization and enzyme utilization, the fabricated nanozyme holds promise as a substitute for peroxidase and oxidase for detecting glucose.

A Silicon-Based ROTE Sensor for High-Q and Label-Free Carcinoembryonic Antigen Detection.

This paper presents a biosensor based on the resonant optical tunneling effect (ROTE) for detecting a carcinoembryonic antigen (CEA). In this design, sensing is accomplished through the interaction of the evanescent wave with the CEA immobilized on the sensor's surface. When CEA binds to the anti-CEA, it alters the effective refractive index (RI) on the sensor's surface, leading to shifts in wavelength. This shift can be identified through the cascade coupling of the FP cavity and ROTE cavity in the same mode. Experimental results further show that the shift in resonance wavelength increases with the concentration of CEA. The biosensor responded linearly to CEA concentrations ranging from 1 to 5 ng/mL with a limit of detection (LOD) of 0.5 ng/mL and a total Q factor of 9500. This research introduces a new avenue for identifying biomolecules and cancer biomarkers, which are crucial for early cancer detection.

ZIF-8 functionalized S-tapered fiber-optic sensor for polystyrene nanoplastics detection by electrostatic adsorption

Microplastic (MP) residues in marine have become an increasingly serious environmental pollution issue, and in recent years the detection of MPs in marine started to attract worldwide research interests. Optical-fiber-based environmental sensors have been extensively employed for their several merits such as high sensitivity, pressure resistance, compactness and ease of constructing communication networks. However, fiber-optic refractive index sensors are not specifically developed for distinguishing MPs from other inorganic particles suspended in water. In this paper, an metal-organic framework (MOF) ZIF-8 functionalized S-tapered fiber (STF) sensor is proposed for specific detection of polystyrene nanoplastics (PSNPs) in aqueous environment. ZIF-8 coordination nanoporous polymers with different film thickness were immobilized over the surface of the fabricated STF structure based on self-growth technique and yielding a large surface area over the sensor surface. High sensitivity detection can be achieved by converting the concentration perturbation of PSNPs into evanescent waves over the ZIF-8 functionalized STF surface through the strong electrostatic adsorption effect and π-π stacking, while the fabricated sensor is insensitive to gravels with silica as the primary component in water. It is found that the proposed detector with 18 film layers achieves a sensitivity up to 114.1353nm/%(w/v) for the PSNPs concentration range of 0.01 %(w/v) to 0.08 %(w/v).

Development of a biophotonic fiber sensor using direct-taper and anti-taper techniques with seven-core and four-core fiber for the detection of doxorubicin in cancer treatment

Doxorubicin (DOX) is an important drug for cancer treatment, but its clinical application is limited due to its toxicity and side effects. Therefore, detecting the concentration of DOX during treatment is crucial for enhancing efficacy and reducing side effects. In this study, the authors developed a biophotonic fiber sensor based on localized surface plasmon resonance (LSPR) with the multimode fiber (MMF)-four core fiber (FCF)-seven core fiber (SCF)-MMF-based direct-taper and anti-taper structures for the specific detection of DOX. Compared to other detection methods, it has the advantages of high sensitivity, low cost, and strong anti-interference ability. In this experiment, multi-walled carbon nanotubes (MWCNTs), cerium-oxide nanorods (CeO2-NRs), and gold nanoparticles (AuNPs) were immobilized on the probe surface to enhance the sensor's biocompatibility. MWCNTs and CeO2-NRs provided more binding sites for the fixation of AuNPs. By immobilizing AuNPs on the surface, the LSPR was stimulated by the evanescent field to detect DOX. The sensor surface was functionalized with DOX aptamers for specific detection, enhancing its specificity. The experiments demonstrated that within a linear detection range of 0-10 µM, the sensitivity of the sensor is 0.77 nm/µM, and the limit of detection (LoD) is 0.42 µM. Additionally, the probe's repeatability, reproducibility, stability, and selectivity were evaluated, indicating that the probe has high potential for detecting DOX during cancer treatment.

A microfiber biosensor for detection of AKT protein in human embryonic kidney cell lysate based on the vernier effect

The AKT protein is closely related to the cancer and diabetes. Rapid detection of AKT is very important in medical diagnosis. This paper proposed a parallel connected tapered seven-core fiber (PTSCF) biosensor to utilize vernier effect to improve sensitivity. Experimental results showed that 5.99 times improvements have been achieved in the refractive index sensing in the ranges of 1.333–1.337. By functionalizing AKT-Ab on the PTSCF sensor surface, a fast detection (<40 min) and an ultra-low limit of detection (LoD) of 0.044 ng/mL have been achieved for AKT protein solutions. The proposed PTSCF biosensor has been applied to detect AKT proteins in human embryonic kidney cell lysates and compared with those obtained by the western blotting (WB) method. Experimental results showed that the LoD of the PTSCF biosensor is 400-fold less than that of WB method. The proposed PTSCF biosensor holds great potential for applications in various medical fields, including intra-operative rapid detection, animal experiments, and pathological research.

Evaluating Multi-target Regression Framework for Dynamic Condition Prediction in Wellbore

In recent years, the focus has shifted towards leveraging physics-based modelling and data-driven analysis to predict drilling incidents and anomalies in real time, with the goal of reducing non-productive periods. However, much of this attention has directed at specific drilling operations like drilling and tripping, leaving other vital processes, such as wellbore conditioning, comparatively overlooked. The primary objective of this study is to employ data-driven techniques for predicting the dynamic state of the wellbore by utilising sensor data, operating parameters, and surface measurements. Accurate predictions are pivotal for automating these processes, promising significant savings in both redundant time and associated costs, ultimately elevating operational efficiency.In this research, the surface drilling parameters such as flowrate, rotation speed, block position, and drill string length are incorporated with the surface measurements such as hookload, pressure, and torque during wellbore conditioning operation to predict further surface sensor measurements. Different parameter settings are evaluated to find the best approach. Six supervised learning algorithms are used to select the best prediction method. The findings reveal that considering all surface parameters and measurements yields the most accurate predictions. Among various single and multi-target regression methods, including deep learning approaches, the Gaussian process and random forest models exhibit the lowest prediction errors.By reliably predicting and understanding wellbore behaviour, this research paves the way for more efficient and autonomous drilling operations in the future, bridging a critical gap in the industry's automation capabilities.

Numerical heat and mass transfer in magnetized Williamson liquid motion over a sensor wall engulfed in a micro-cantilever system: An application to thin-film fluidic cells

Central focus of this numerical analysis is to investigate the influence of magnetic body force and thermal radiation on the time-dependent electrically conducting two-dimensional viscous incompressible boundary layer flow of non-Newtonian Williamson fluid over a microcantilever sensor surface suspended in a squeezed regime numerically. A novel heat source/sink and Soret effects are included in the respective governing equations. The constructed time-dependent nonlinear coupled partial differential equations are solved by using a bobust RK-4 technique. Increasing magnetic number increases the velocity distribution and decreases the temperature and concentration profiles in the flow regime.Enhancing Soret number increases the mass diffusion profile. Increasing magnetic number suppress the skin-friction coefficient. Heat transport rate booted with rising radiation number and Sherwood number decreased with enlarged Schmidt number in the channel regime. Finally, the numerical accuracy of the present similarity solutions and used numerical method is validated with existing results and observed a remarkable agreement.

AptaShield: A Universal Signal-Transduction System for Fast and High-Throughput Optical Molecular Biosensing.

Biosensing technologies are often described to provide facile, sensitive, and minimally to noninvasive detection of molecular analytes across diverse scientific, environmental, and clinical diagnostic disciplines. However, commercialization has been very limited mostly due to the difficulty of biosensor reconfiguration for different analyte(s) and limited high-throughput capabilities. The immobilization of different biomolecular probes (e.g., antibodies, peptides, and aptamers) requires the sensor surface chemistry to be tailored to provide optimal probe coupling, orientation, and passivation and prevent nonspecific interactions. To overcome these challenges, here we report the development of a solution-phase biosensor consisting of an engineered aptamer, the AptaShield, capable of universally binding to any antigen recognition site (Fab') of fluorescently labeled immunoglobulins (IgG) produced in rabbits. The resulting AptaShield biosensor relies on a low affinity dynamic equilibrium between the fluorescently tagged aptamer and IgG to generate a specific Förster resonance energy transfer (FRET) signal. As the analyte binds to the IgG, the AptaShield DNA aptamer-IgG complex dissociates, leading to an analyte concentration-dependent decrease of the FRET signal. The biosensor demonstrates high selectivity, specificity, and reproducibility for analyte quantification in different biological fluids (e.g., urine and blood serum) in a one-step and low sample volume (0.5-6.25 μL) format. The AptaShield provides a universal signal transduction mechanism as it can be coupled to different rabbit antibodies without the need for aptamer modification, therefore representing a robust high-throughput solution-phase technology suitable for point-of-care applications, overcoming the current limitations of gold standard enzyme-linked immunosorbent assays (ELISA) for molecular profiling.

Intelligent salivary biosensors for periodontitis: in vitro simulation of oral oxidative stress conditions.

One of the most common oral diseases affecting millions of people worldwide is periodontitis. Usually, proteins in body fluids are used as biomarkers of diseases. This study focused on hydrogen peroxide, lipopolysaccharide (LPS), and lactic acid as salivary non-protein biomarkers for oxidative stress conditions of periodontitis. Electrochemical analysis of artificial saliva was done using Gamry with increasing hydrogen peroxide, bLPS, and lactic acid concentrations. Electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) were conducted. From EIS data, change in capacitance and CV plot area were calculated for each test condition. Hydrogen peroxide groups had a decrease in CV area and an increase in percentage change in capacitance, lipopolysaccharide groups had a decrease in CV area and a decrease in percentage change in capacitance, and lactic acid groups had an increase of CV area and an increase in percentage change in capacitance with increasing concentrations. These data showed a unique combination of electrochemical properties for the three biomarkers. Scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS) employed to observe the change in the electrode surface and elemental composition data present on the sensor surface also showed a unique trend of elemental weight percentages. Machine learning models using hydrogen peroxide, LPS, and lactic acid electrochemical data were applied for the prediction of risk levels of periodontitis. The detection of hydrogen peroxide, LPS, and lactic acid by electrochemical biosensors indicates the potential to use these molecules as electrochemical biomarkers and use the data for ML-driven prediction tool for the periodontitis risk levels.

In Situ-Derived N-Doped ZnO from ZIF-8 for Enhanced Ethanol Sensing in ZnO/MEMS Devices.

Microelectromechanical systems (MEMS) gas sensors have numerous advantages such as compact size, low power consumption, ease of integration, etc., while encountering challenges in sensitivity and high resistance because of their low sintering temperature. This work utilizes the in situ growth of Zeolitic Imidazolate Framework-8 (ZIF-8) followed by its conversion to N-doped ZnO. The results obtained from scanning electron microscopy (SEM) and transmission electron microscopy (TEM) indicate that the in situ derivation of ZIF-8 facilitates the adhesion of ZnO particles, forming an island-like structure and significantly reducing the interfaces between these particles. Furthermore, powder X-ray diffraction (XRD) analysis, elemental mapping, and X-ray photoelectron spectroscopy (XPS) analysis confirm the conversion of ZIF-8 to ZnO, the successful incorporation of N atoms into the ZnO lattice, and the creation of more oxygen vacancies. The ZIF-8-derived N-doped ZnO/MEMS sensor (ZIF (3)-ZnO/MEMS) exhibits remarkable gas sensitivity for ethanol detection. At an operating temperature of 290 °C, it delivers a substantial response value of 80 towards 25 ppm ethanol, a 13-fold enhancement compared with pristine ZnO/MEMS sensors. The sensor also exhibits an ultra-low theoretical detection limit of 11.5 ppb to ethanol, showcasing its excellent selectivity. The enhanced performance is attributed to the incorporation of N-doped ZnO, which generates abundant oxygen vacancies on the sensor's surface, leading to enhanced interaction with ethanol molecules. Additionally, a substantial two-order-of-magnitude decrease in the resistance of the gas-sensitive film is observed. Overall, this study provides valuable insights into the design and fabrication strategies applicable to high-performance MEMS gas sensors in a broader range of gas sensing.

UV-durable self-cleaning coatings for autonomous driving

A key technology to ensure the safety and accuracy of autonomous driving for future transportation is the cleanliness of the sensor surfaces for accurate signal reading. This study focuses on hydrophobic coatings with self-cleaning performances and UV durability, their possible degradation mechanism of static water contact angle (sWCA), and the effect of the hydrophobic surface on camera image quality. The UV-durable hydrophobic coatings are applied by a spray process followed by a thermal curing. The UV-durable hydrophobic coatings are evaluated on a vision camera under lab-simulated weathering conditions such as rain, mud, fog, and bugs, on samples as-prepared and after various hours of Weather-Ometer® weathering. The results indicate that the sWCA degradation of the UV-durable hydrophobic coatings during accelerated weathering is corresponding to the loss of fluorine (F) atomic percentage in the coatings, and the vision camera imaging quality improves significantly with the UV-durable hydrophobic coatings in comparison to an uncoated surface. The self-cleaning performances of the UV-durable hydrophobic coatings, as measured by two metrics using signal-to-noise ratio and modulation transfer function 50 loss (MTF50loss), linearly correlate with sWCA of the coatings. The UV-durable hydrophobic coatings on the sensor surface will significantly benefit autonomous driving specifically for accurate signal reading under inclement weather.

Enhanced Gas Sensing Performance of CuO-ZnO Composite Nanostructures for Low-Concentration NO2 Detection

The detection of nitrogen dioxide (NO2) is essential for safeguarding human health and addressing environmental sustainability. That is why, in the last decades, gas sensors have been developed to detect NO2 to overcome these hazards. This study explores the use of a novel CuO-ZnO composite synthesized through a polyol and sol–gel technique to enhance gas sensing performance. The CuO-ZnO composite offers the advantage of a synergic combination of its properties, leading to improved sensitivity, selectivity, and low detection limit. The innovative polyol technique employed in this research enables the controlled synthesis of hierarchical CuO and porous ZnO structures. The composite formation is achieved using the sol–gel method, resulting in CuO-ZnO composites with different ratios. The structural, morphological, and optical properties of the materials have been characterized using FESEM, X-ray diffraction, and UV-vis spectroscopy. Gas sensing experiments demonstrate enhanced performance, particularly in sensitivity and selectivity for NO2, even at low concentrations. The composites also exhibit improved baseline stability compared to pristine CuO and ZnO. This study explains the influence of humidity on gas sensing properties by examining interactions between water molecules and sensor surfaces. Notably, the developed CuO-ZnO composite displays excellent selectivity towards NO2, attributed to favorable bonding characteristics and acid-base properties. Overall, this research contributes to advancing gas sensor technology, providing a promising potential for sensitive and selective NO2 detection, thereby addressing critical needs for human health and environmental protection.

Singlet oxygen-based photoelectrochemical detection of miRNAs in prostate cancer patients’ plasma: A novel diagnostic tool for liquid biopsy

Dysregulation of miRNA expression occurs in many cancers, making miRNAs useful in cancer diagnosis and therapeutic guidance. In a clinical context using methods such as polymerase chain reaction (PCR), the limited amount of miRNAs in circulation often limits their quantification. Here, we present a PCR-free and sensitive singlet oxygen (1O2)-based strategy for the detection and quantification of miRNAs in untreated human plasma from patients diagnosed with prostate cancer. A target miRNA is specifically captured by functionalised magnetic beads and a detection oligonucleotide probe in a sandwich-like format. The formed complex is concentrated at the sensor surface via magnetic beads, providing an interface for the photoinduced redox signal amplification. The detection oligonucleotide probe bears a molecular photosensitiser, which produces 1O2 upon illumination, oxidising a redox reporter and creating a redox cycling loop, allowing quantification of pM level miRNA in diluted human plasma within minutes after hybridisation and without target amplification.