Biosensors-Basel最新文献

With the goal of fast and accurate diagnosis of infectious diseases, this study presents a novel electrochemical biosensor that employs a refined aptamer (C9t) for the detection of spike (S) protein SARS-CoV-2 variants in a flexible multielectrode aptasensor array with PoC capabilities. Two aptamer modifications were employed: removing the primer binding sites and including two dithiol phosphoramidite anchor molecules. Thus, reducing fabrication time from 24 to 3 h and increasing the stability and sparseness for multi-thiol aptasensors compared to a standard aptasensor using single thiols, without a reduction in aptamer density. The biosensor fabrication, optimization, and detection were verified in detail by electrochemistry, QCM-D, SPR, and XPS. The analyte-receptor binding was further confirmed spectroscopically at the level of individual molecules by AFM-IR. The aptasensor possesses a low limit of detection (8.0 fg/mL), the highest sensitivity reported for S protein (209.5 signal per concentration decade), and a wide dynamic detection range (8.0 fg/mL-38 ng/mL) in nasopharyngeal samples, covering the clinically relevant range. Furthermore, the C9t aptasensor showed high selectivity for SARS-CoV-2 S proteins over biomarkers for MERS-CoV, RSV, and Influenza. Even more, it showed a three times higher sensitivity for the Omicron in comparison to the Wuhan strain (wild type), alpha, and beta variants of the SARS-CoV-2 virus. Those results demonstrate the creation of an affordable and variant-selective refined C9t aptasensor that outperformed current rapid diagnosis tests.

Human monkeypox (Mpox) is a zoonotic disease caused by the Monkeypox virus (MPXV). As of 14 August 2024, the World Health Organization (WHO) has declared it a global health emergency. For Mpox, this was the second public health emergency of global significance in the past two years. MPXV belongs to the Poxviridae family and is phylogenetically and epidemically divided into two clades: the Congo Basin (Clade-I) and the West African (Clade-II) clades. Clade-I has been associated with more severe disease progression and higher mortality compared to Clade-II, and thus the differentiation between clades can play an important role in predicting disease prognosis. The LAMP technique has the advantages of not requiring thermal cycling and achieving higher amplification in a shorter time compared to qPCR. Different types of LAMP assays were developed in this study to benefit from these advantages. We report the development of LAMP-1 and LAMP-2 assays using the LAMP method to detect MPXV Clade-I and Clade-II, respectively. The LAMP-1 assay includes both fluorescence and visible colorimetric readout tests developed with sensitivities of 10³ and 10⁷ copies, respectively. For the LAMP-2 assay, a probe-based test utilizing the Novel R-Duplex DARQ probe was developed, offering fluorescence detection at a sensitivity of 10³ copies. As a result, we successfully developed three highly specific molecular diagnostic tests that distinctly differentiate between MPXV clades, delivering essential tools for the precise diagnosis and effective control of Mpox.

In this study, a novel rapid immunochromatographic (IC) test for African swine fever virus (ASFV) antibodies is presented. An immunochromatographic test (IC) is a detection technique that combines membrane chromatography with immunolabeling. This approach saves time for antibody preparation, resulting in a shorter production cycle. p54 is an important structural protein of African swine fever, and an ideal protein for serotype diagnosis. Gold nanoparticles are attached to the ASFV p54-Fc fusion protein, and the ASFV-specific antigen p54 and Staphylococcus aureus protein A (SPA) are labeled on a nitrocellulose membrane, at positions T and C, respectively. We developed a SPA double sandwich IC test strip, and assessed its feasibility using ASFV p54 and p54-Fc fusion proteins as antigens. ASFV p54 and p54-Fc fusion proteins were expressed and purified. A sandwich cross-flow detection method for p54, which is the primary structural protein of ASFV, was established, using colloidal gold conjugation. Our method can detect ASFV antibodies in field serum samples in about 15 min using a portable colloidal gold detector, demonstrating high specificity and sensitivity (1:320), and the coincidence rate was 98% using a commercial ELISA kit. The dilution of the serum sample can be determined by substituting the absorbance (T-line) interpreted by portable devices into the calibration curve function formula of an African swine fever virus standard serum. In summary, our method is rapid, cost-effective, precise, and highly selective. Additionally, it introduces a new approach for constructing IC test strips using SPA protein without antibody preparation, making it a reliable on-site antibody test for ASFV.

Firefly luciferases have been extensively used for bioanalytical applications, including their use as bioluminescent reporters, biosensors, and for bioimaging biological and pathological processes. Due to their intrinsic pH- sensitivity, in recent years we have demonstrated that firefly luciferases can also be harnessed as color- tuning sensors of intracellular pH. However, it is known that mammalian cells require temperatures higher than 36 °C, which red-shift the bioluminescence spectra of most firefly luciferases, decreasing their activities and the resolution of ratiometric pH analysis. Therefore, we prospected and engineered novel pH-sensitive firefly luciferases for mammalian cells. We humanized the luciferases of Amydetes vivianii (Amy-Luc) and Cratomorphus distinctus (Crt-Luc) fireflies, inserted them into the pCDNA3 vector, and compared their bioluminescence and pH-sensing properties with those of Macrolampis firefly luciferase (Mac-Luc) inside fibroblasts. The transfected COS-1 with Mac-Luc and Crt-Luc displayed lower bioluminescence activity and considerably red-shifted spectra (611 and 564 nm, respectively) at 37 °C, whereas Amy-Luc displayed the highest bioluminescence activity and spectral stability at 37 °C inside cells, displaying the most blue-shifted spectrum at such temperatures (548 nm) and the best spectral resolution at different pH values, making it possible to ratiometrically estimate the pH from 6.0 to 8.0. These results show that Amy-Luc is a novel brighter reporter gene and suitable pH- indicator for mammalian cells. Furthermore, whereas at pH 8.0 the spectrum was thermally stable, at pH 6.0 Amy-Luc showed higher temperature sensitivity, raising the possibility of using this luciferase as an intracellular temperature sensor. Thus, the improved bioluminescence properties as compared to existing luciferases could offer advantages for in vivo imaging and pH- sensing for the study of mammalian cellular physiology.

The COVID-19 pandemic has highlighted the urgent need for rapid, sensitive, and reliable diagnostic tools for detecting SARS-CoV-2. In this study, we developed and optimized a surface plasmon resonance (SPR) biosensor incorporating advanced materials to enhance its sensitivity and specificity. Key parameters, including the thickness of the silver layer, silicon nitride dielectric layer, molybdenum disulfide (MoS₂) layers, and ssDNA recognition layer, were systematically optimized to achieve the best balance between sensitivity, resolution, and attenuation. The optimized configuration, consisting of a 45 nm silver layer, a 13 nm silicon nitride layer, 2 MoS₂ layers, and a 5 nm ssDNA layer, demonstrated superior performance for detecting SARS-CoV-2 in PBS solution. The biosensor exhibited high sensitivity at low viral concentrations, achieving a sensitivity of 375.01°/RIU, a detection accuracy of 0.002, and a quality factor of 38.34 at 1.0 mM SARS-CoV-2 concentration. Performance metrics validated the sensor's capability for reliable detection, particularly in early-stage diagnostics where timely intervention is critical. Moreover, the biosensor's linear response to refractive index changes confirmed its potential for quantitative viral concentration analysis. This study underlines the significance of integrating advanced materials, such as MoS₂ and silicon nitride, to enhance SPR biosensor performance. The findings establish the proposed biosensor as a robust and precise diagnostic tool for SARS-CoV-2 detection, with potential applications in clinical diagnostics and epidemiological monitoring.

Lateral flow assay has been extensively used for at-home testing and point-of-care diagnostics in rural areas. Despite its advantages as convenient and low-cost testing, it suffers from poor quantification capacity where only yes/no or positive/negative diagnostics are achieved. In this study, machine learning and deep learning models were developed to quantify the analyte load from smartphone-captured images of the lateral flow assay test. The comparative analysis identified that random forest and convolutional neural network (CNN) models performed well in classifying the lateral flow assay results compared to other well-established machine learning models. When trained on small-size images, random forest models excelled CNN models in image classification. Contrarily, CNN models outperformed random forest models in classifying noisy images.

Continuous glucose monitoring based on the minimally invasive implantation of glucose sensor is characterized by high accuracy and good stability. At present, glucose concentration monitoring based on fluorescent glucose capsule sensor is a new development trend. In this paper, we design a fluorescent glucose capsule sensor with a design optimization study. The motion trajectory of incident light in the fluorescent gel layer is simulated based on the Monte Carlo method, and the cloud maps of light intensity with the light intensity distribution at the light-receiving layer are plotted. Altering the density of fluorescent molecules, varying the thickness of tissue layers, and adjusting the angle of incidence deflection, the study investigates the influence of these parameter changes on the optimal position of reflected light at the bottom. Finally, the simulation results were utilized to design and fabricate a fluorescent glucose capsule sensor. Rabbit subcutaneous tissue glucose level tests and real-time glucose solution concentration monitoring experiments were performed. This work contributes to the real-time monitoring of glucose levels and opens up new avenues for research on fabricating glucose sensors.

Hyperspectral imaging (HSI) technology, which offers both spatial and spectral information, holds significant potential for enhancing diagnostic performance during endoscopy and other medical procedures. However, quantitative evaluation of HSI cameras is challenging due to various influencing factors (e.g., light sources, working distance, and illumination angle) that can alter the reflectance spectra of the same target as these factors vary. Towards robust, universal test methods, we evaluated several data normalization methods aimed at minimizing the impact of these factors. Using a high-resolution HSI camera, we measured the reflectance spectra of diffuse reflectance targets illuminated by two different light sources. These spectra, along with the reference spectra from the target manufacturer, were normalized with nine different methods (e.g., area under the curve, standard normal variate, and centering power methods), followed by a uniform scaling step. We then compared the measured spectra to the reference to evaluate the capability of each normalization method in ensuring a consistent, standardized performance evaluation. Our results demonstrate that normalization can mitigate the impact of some factors during HSI camera evaluation, with performance varying across methods. Generally, noisy spectra pose challenges for normalization methods that rely on limited reflectance values, while methods based on reflectance values across the entire spectrum (such as standard normal variate) perform better. The findings also suggest that absolute reflectance spectral measurements may be less effective for clinical diagnostics, whereas normalized spectral measurements are likely more appropriate. These findings provide a foundation for standardized performance testing of HSI-based medical devices, promoting the adoption of high-quality HSI technology for critical applications such as early cancer detection.

Ocular cystinosis is a disease in which accumulated cystine crystals cause damage to the eyes, necessitating timely treatment and ongoing monitoring of cystine levels. The current treatment involves frequent administration of cysteamine eye drops, which suffer from low bioavailability and can lead to drug toxicity, making it essential to prescribe an appropriate dosage based on the patient's condition. Additionally, cystine crystal levels are typically assessed subjectively via slit-lamp examination, requiring frequent clinical visits and causing discomfort for the patient. In this study, we propose a theranostic contact lens that simultaneously performs therapy and diagnosis on a single platform utilizing gold nanoparticles (GNPs). The binding interactions between GNPs and cystine were confirmed in solution, and thermodynamic analysis further elucidated the bonding force between the two substances. With a comprehensive understanding of these interactions, we investigated the potential of the theranostic GNP-loaded contact lens (GNP-CL). Upon exposure to various concentrations of cystine, the GNP-CL demonstrated distinct color changes, transitioning from red to blue. This color shift enabled quantitative monitoring of cystine levels. The treatment efficacy was validated by confirming a reduction in cystine concentration following the reaction. This platform has the potential to improve disease management in ocular cystinosis by reducing the reliance on cysteamine and offering an objective self-monitoring tool that does not require specialized equipment.

Carbendazim (CBZ) is used to prevent fungal infections in agricultural crops. Given its high persistence and potential for long-term health effects, it is crucial to quickly identify pesticide residues in food and the environment in order to mitigate excessive exposure. Aptamer-based sensors offer a promising solution for pesticide detection due to their exceptional selectivity, design versatility, ease of use, and affordability. Herein, we report the development of an electrochemical aptasensor for CBZ detection. The sensor was fabricated through a one-step electrodeposition of platinum nanoparticles (Pt NPs) and reduced graphene oxide (rGO) on a glassy carbon electrode (GCE). Then, a CBZ-specific aptamer was attached via Pt-sulfur bonds. Upon combining CBZ with the aptamer on the electrode surface, the redox reaction of the electrochemical probe K₄[Fe(CN)₆] is hindered, resulting in a current drop. Under optimized conditions (pH of 7.5 and 25 min of incubation time), the proposed aptasensor showed a linear current reduction to CBZ concentrations between 0.5 and 15 nM. The limit of detection (LOD) for this proposed aptasensor is 0.41 nM. Along with its repeatable character, the aptasensor demonstrated better selectivity for CBZ compared to other potential compounds. The recovery rates for detecting CBZ in skim milk and tap water using the standard addition method were 98% and 96%, respectively. The proposed aptasensor demonstrated simplicity, sensitivity, and selectivity for detecting CBZ with satisfactory repeatability. It establishes a strong foundation for environmental monitoring of CBZ.