Sensors & diagnostics最新文献

In this study, we developed a novel electrochemical sensing chip integrated with reduced graphene oxide (rGO) with laser-induced graphene (LIG) for the detection of exosomes associated with breast cancer biomarkers. Employing laser-induced technology, a three-dimensional porous graphene material is fabricated on the surface of a flexible polyimide film, which is subsequently combined with rGO through π–π stacking. This integration facilitates the doping of two-dimensional and three-dimensional material (2D/3D) structures, significantly enhancing the conductivity of the electrode material. Additionally, this approach markedly improves the surface hydrophobicity and biomolecule affinity of LIG, optimizing the immobilization of specific antibodies for exosomes. Importantly, this experiment marks the first occasion of merging two-dimensional rGO with three-dimensional LIG, resulting in the construction of a high-performance biosensing chip that enables specific capture and highly sensitive detection of exosomes. Under optimized conditions, the quantitative detection range for exosomes is established at 5 × 10² to 5 × 10⁵ particles per μL, with a limit of detection (LOD) of 166 particles per μL. The biosensor is successfully used to analyze exosomes in breast cancer cell lines and patient serum samples, proving its practical application. This electrochemical biosensing chip offers significant practical application value in the early screening and diagnosis of diseases.

Microfluidic electrochemical sensors (μCS) can be portable, highly sensitive, and low-cost but are less frequently studied nor applied. Additionally, simultaneous electro-deposition of gold nanoparticles (ED (AuNPs)) and electro-polymerization of L-cysteine (EP (L-cys)) are introduced for the first time for modifying the surface of the working electrode through a paper-based microfluidic sensor. This study depicts that by employing such modification, the electrochemically active surface area (ECSA) and the electron transfer rate are increased together and result in improved sensitivity. The modified μCS is depicted to enable sensitive voltametric determination of, e.g., clozapine (CLZ), an anti-psychotic drug to treat schizophrenia. The proposed sensor was characterized by different techniques, and several key parameters were optimized. Under the optimum conditions and using square-wave voltametry (SWV), a linear dose–response for a concentration range from 0.5 to 10.0 μM of CLZ was achieved. The limit of detection and sensitivity resulted in 70.0 nM and 0.045 mA cm⁻² μM⁻¹, respectively. Besides, this excellent sensitivity combines with high stability, which was tested for six repetitive measurements with a single device resulting in high reproducibility. Additionally, this procedure was validated with measurements of clozapine in human blood plasma, which demonstrated the excellent applicability of the device, rendering it a promising platform for point-of-care diagnostics and environmental monitoring.

Detecting pesticides like atrazine is a significant global health challenge due to their association with numerous foodborne illnesses. Traditional detection methods often lack sensitivity and time efficiency, highlighting the urgent need for improved early detection techniques to mitigate pesticide contamination and outbreaks. This study introduces a novel portable electrochemical prototype that integrates an ARM-based microcontroller with an impedance spectroscopy (EIS)-based biosensing system. The data processed through the algorithm generates easily interpretable impedance values. The platform demonstrates a broad detection range for atrazine (1 fg mL⁻¹ to 10 ng mL⁻¹) with a limit of detection (LoD) of 1 fg mL⁻¹ and an assay processing time of approximately 5 minutes, showcasing its remarkable efficiency. The sensor consistently maintains cross-reactivity variation below 20%, ensuring reliable performance. This research aims to offer a low-cost, replicable mobile platform for biosensing applications, thereby enhancing access for individuals with limited lab-based research experience and broadening the scope of proactive pesticide monitoring.

In the field of point-of-care diagnostics, lateral flow assays (LFAs) stand out as highly promising due to their compact size, ease of use, and rapid analysis times. These attributes make LFAs invaluable, especially in urgent situations or resource-limited regions. However, their Achilles' heel has always been their limited sensitivity and selectivity. To address these issues, various innovative approaches, including sample enrichment, assay optimization, and signal amplification, have been developed and are extensively discussed in the literature. Despite these advancements, the importance of antibody orientation is often neglected, even though improper orientation can significantly impair detection performance. This review article first explores well-established traditional methodologies, such as minor physical adjustments and non-specific chemical bond formations. It then shifts focus to the oriented immobilization of antibodies on probe surfaces. This approach aims to enhance sensitivity and selectivity fundamentally by leveraging protein affinities or complementary amino acid sequences. The review summarizes the impact of antibody orientation on the analytical performance of LFAs in terms of sensitivity, specificity, speed, reliability, cost-effectiveness, and stability. Additionally, we introduce recent modifications to assay membrane materials and discuss the current limitations and future prospects of LFAs.

Biomarkers provide critical molecular insights into diseases and abnormal conditions. However, detecting them at ultra-low concentrations is a challenge, particularly in areas with limited resources and access to sophisticated instruments. Our research is primarily focused on mitigating this challenge. In this report, we introduce a colorimetric immunosensor for detecting insulin, an essential hormone biomarker that regulates glucose metabolism, at picomolar concentrations using citrate-functionalized magnetic particles. This immunosensor utilizes a two-antibody sandwich immunoassay: one antibody is covalently conjugated to the nanoparticles to capture and isolate the target marker, while the other is labeled with horseradish peroxidase for colorimetric detection of insulin. We conducted comparative analyses of insulin detection in buffer, saliva, and serum samples, offering valuable analytical insights. Our findings indicate a detection limit of 10 pM, with dynamic ranges of 10 pM to 1 nM, 10 pM to 10 nM, and 50 pM to 1 nM for insulin detection in buffer solution, 2-fold diluted serum, and 20-fold diluted artificial saliva, respectively. We demonstrate the application of the color immunosensor to type 1 diabetes and healthy human serum samples. For human saliva analysis, the detection limit needs to be improved in our future studies. Overall, our study enhances biomarker analysis in biofluids through an equipment-free colorimetric method, which is particularly relevant for point-of-need applications.

Single-molecule detection methods based on electrical readout can transform disease diagnostics by miniaturizing the downstream sensor to enable sensitive and rapid biomarker quantification at the point-of-care. In particular, solid-state nanopores can be used as single-molecule electrical counters for a variety of biomedical applications, including biomarker detection. Integrating nanopores with efficient DNA amplification methods can improve upon sensitivity and accessibility concerns often present in disease detection. Here, we present nanopores as biosensors downstream of a reverse-transcription recombinase polymerase amplification (RT-RPA)-based assay targeting synthetic SARS-CoV-2 RNA. We demonstrate the efficacy of nanopore-integrated RT-RPA for the direct electrical detection of target amplicons, and discuss challenges from RPA-based assays and adaptations that facilitate solid-state nanopore readout.

Monitoring metabolites in situ at the single-cell scale is important for revealing cellular heterogeneity and dynamic changes of cell status, which provides new possibilities for disease research. Benefiting from the advantages of both electrochemical and optical methods, electrochemiluminescence (ECL) has great potential in this field. However, developing real-time in situ imaging methods is full of challenges. In this study, an ECL imaging method for formaldehyde (FA), a kind of cellular metabolite, was developed based on the in situ generation of co-reactants at the electrode interface and was successfully applied to the monitoring of single-cell FA release. Amino groups can undergo a rapid nucleophilic addition reaction with FA to form amino alcohol intermediates, which can be used as co-reactants for tris(2,2′-bipyridyl)ruthenium(II) [Ru(bpy)₃²⁺] to significantly enhance the strength of ECL. Poly(amidoamine) (PAMAM), with a large number of amino groups, and reduced graphene oxide (rGO), with excellent electrical conductivity and electrocatalytic properties, were introduced as the modification layer on the electrode surface to realize the “turn on” detection of FA. This sensing method also eliminated the use of the classic toxic co-reactant tripropylamine (TPrA) and was further applied to in situ imaging of single-cell FA release. It successfully obtained ECL images at different time points after the stimulation of HeLa cells with thapsigargin (TG), revealing the change pattern in drug efficacy over time. This work proposes a new ECL imaging approach for real-time in situ monitoring of FA release from single cells, further broadening the application of ECL imaging in single-cell analysis.

Iron, the most abundant transition metal in the body, regulates cellular function but can be harmful in excess, leading to reactive oxygen species production and cellular damage. Intracellular Fe²⁺ exerts a significant impact on cellular function, potentially contributing to various critical diseases. To address this, detection methods need high selectivity, sensitivity, and real-time monitoring capabilities, essential for comprehending disease progression. This necessitates advancements beyond conventional detection approaches. Frataxin, a crucial mitochondrial protein, is indispensable for sustaining life, contributing not only to iron metabolism but also to the formation of iron–sulfur clusters critical for cellular function. Its deficiency is implicated in neurodegenerative diseases. We have developed a nanosensor, based on fluorescence resonance energy transfer (FRET), designed to probe iron efflux mechanisms and facilitate dynamic monitoring of iron concentration and its spatial distribution within living cells. To construct this nanosensor, we strategically positioned CyaY, a bacterial frataxin ortholog, between ECFP and Venus, forming a FRET pair. This innovative nanosensor, designated as FeOS (iron optical sensor), demonstrates exceptional selectivity for iron and maintains stability under physiological pH conditions. Additionally, we engineered three mutant variants: I17C, AD10-I17C, and D76H, with A10D-I17C displaying the highest affinity for iron and a broad detection range. The distinguishing feature of this sensor is that it is genetically encoded, facilitating real-time detection of iron levels within living cells.

In many gas sensing tasks, we simply wish to become aware of gas compositions that deviate from normal, “business-as-usual” conditions. We provide a methodology, illustrated by example, to computationally predict the performance of a gas sensor array design for detecting anomalous gas compositions. Specifically, we consider a sensor array of two zeolitic imidazolate frameworks (ZIFs) as gravimetric sensing elements for detecting anomalous gas compositions in a fruit ripening room. First, we define the probability distribution of the concentrations of the key gas species (CO₂, C₂H₄, H₂O) we expect to encounter under normal conditions. Next, we construct a thermodynamic model to predict gas adsorption in the ZIF sensing elements in response to these gas compositions. Then, we generate a synthetic training data set of sensor array responses to “normal” gas compositions. Finally, we train a support vector data description to flag anomalous sensor array responses and test its false alarm and missed-anomaly rates under conceived anomalies. We find the performance of the anomaly detector diminishes with (i) greater variance in humidity, which can mask CO₂ and C₂H₄ anomalies or cause false alarms, (ii) higher levels of noise emanating from the transducers, and (iii) smaller training data sets. Our exploratory study is a step towards computational design of gas sensor arrays for anomaly detection.

Microfluidic chips designed to measure viscosity with extremely small amounts of liquids are expected to examine biological fluids, such as for the prediction of disease states and stress assessment, and for the evaluation of the physical properties of novel synthetic materials. However, these devices typically require sample volumes of several tens of μL or more, which has limitations when collecting biological samples from individuals nearly non-invasively. In this study, we fabricated a flow channel on a nonwoven fabric substrate with tailored hydrophilic and hydrophobic properties to enable viscosity measurements with the small-volume flow of aqueous solutions, such as 3 μL of saline. By measuring the electrical conductivity of the liquid using comb-shaped printed electrodes in contact with the flow path, we quantified the time and distance of liquid flow driven by capillary action to estimate solution viscosity. Using a mixture of glycerol and saline solution with varying viscosities, while maintaining a constant ion concentration, we demonstrated the capability to assess the relative viscosity of solutions. This was achieved by evaluating the correlation coefficient between the flow time and distance, and the net electrical conductivity, which is influenced by the viscosity and ion concentration of the solutions. This study lays the groundwork for developing a low-cost technique to measure the viscosity of solutions with a few μL, offering potential for routine health monitoring and disease prevention.