Sensing and Bio-Sensing Research最新文献

Textile based sensors have gained tremendous attention in moisture sensing. Moisture monitoring is crucial in wound healing. To promote the healing process, it is essential to maintain an optimal level of moisture while limiting unnecessary dressing changes. The objective of this research was to test how well a textile moisture sensor can detect moisture from the body and wound fluid when attached to the dressing. To this end, a 3D interdigitated capacitive structure was embroidered with silver conductive threads on the textile substrate, and a bandage was placed in the centre of the multilayer structure. When compared to traditional planar interdigitated structures, the main innovation of the proposed 3D capacitive structure lies in a larger surface area for interaction with the surrounding environment, leading to enhanced sensitivity to changes in capacitance with the respect to the moisture. The 3D structure of the bandage increased the ratio between electrodes and surface area to impact the surface charge sensitivity towards the adsorbed charges of the wound and body fluid. To observe the performance of the sensor, the bandage was exposed to simulated body fluid and wound fluid. Between dry and wet conditions, the sensor can detect capacitance differences of several orders of magnitude. The threshold volume for the 3D bandage was 30 μL to 50 μL, depending on the type of biofluids. The capacitive bandage integration with the inductor was tested at high frequencies (1–400 MHz). The shift in impedance was observed for the tested fluids. Finally, to compare sensing properties of the proposed structure against the previously reported designs, a bandage sensitivity was checked for three different configurations: (a) the proposed 3D bandage, (b) a 2D bandage, composed of textile substrate with both electrodes embroidered on top of bandage, and (c) classical interdigital structure without bandage composed of textile with embroidered electrodes on the top of it. The sensitivity of the 3D bandage for simulated body fluid and wound fluid is >6.6% and 7.4%, respectively, higher than the other two structures. The integration of the proposed textile-based sensor into a bandage could facilitate wound care and have a significant impact on efficacy for patients.

Coffee known for its diverse aromas shaped by postharvest treatments, particularly the roasting process, plays a pivotal role in determining the quality of the brewed beverage. This study focuses on classifying the aroma of Arabica coffee beans based on roasting temperature, employing an electronic nose equipped with a TGS gas array sensor. The classification methodology integrates deep learning through an artificial neural network (ANN), along with a calculation analysis utilizing the Pearson correlation coefficient. Raw Robusta coffee beans were subjected to five distinct roasting treatments (185 °C, 195 °C, 205 °C, 215 °C, and 225 °C), resulting in light roasts, light to medium roasts, medium to dark roasts, medium to dark roasts, and dark roasts. The repeatability test affirms the TGS sensor's reliability, exhibiting a standard deviation (STD) below 20%. Notably, the TGS 2612 and TGS 2611 sensors, dedicated to odor detection, demonstrated excellent validity with an STD below 10% across various roasting temperatures. Classification results from deep learning cross-validation showcase impressive accuracy: 98.2% for Light Roasts, 98.4% for Light to Medium Roasts, 98.8% for Medium Roasts, 97.8% for Medium Roasts, and 95.9% for Dark Roasts. In conclusion, this study reveals that the E-nose, utilizing the TGS gas sensor array with deep learning analysis, effectively detects and classifies coffee types based on roasting time with high accuracy.

By combining molybdenum disulfide quantum dots (MoS₂ QDs) synthesized using a facile hydrothermal method with copper nanoclusters (Cu NCs), copper-ion-modified molybdenum disulfide probes (Cu-MoS₂ QDs) were obtained, enabling sensitive detection and specific recognition of tetracycline (TET). The synthesized probes were characterized using techniques such as fourier-transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), and scanning electron microscopy (SEM). The fluorescence values of the probes and TET after their reaction at different concentrations were used to calculate a detection limit of 30 nM for the synthesized probes. The recovery rate of actual samples reached a high value of 95.70%, with a relative standard deviation below 2.00%, demonstrating excellent accuracy and precision. The probe exhibited high selectivity towards TET. The accuracy is maximized when the concentration of the probe is 4.50 × 10⁻⁵ mol/L, indicating enhanced performance of the molybdenum disulfide probe after copper ion modification and obtaining favorable detection outcomes. This probe holds great potential in enhancing the safety of animal-derived food, ensuring public health, and preserving water resources.

Mycoplasma pneumoniae (MP) is a prominent etiological agent of bronchitis and community-acquired pneumonia. MP, the smallest prokaryotes that are wall-less, free-living, and capable of self-replication, are present in more than 200 species of arthropods, animals, and humans. The swift advancement of nanotechnology has facilitated the utilization of a wide range of nanomaterials in constructing effective biosensing platforms that can detect a variety of target analytes. Nanomaterials possess unique magnetic, optical, and electronic properties and a high ratio of surface area to volume. These attributes enable the manipulation and control of these materials through the covalent or noncovalent attachment of recognition moieties. This has generated possibilities for detecting pathogenic microbes that were hitherto unattainable. Regulating the dimensions and composition of the nanomaterials' surfaces can substantially enhance the analytical capabilities of nanomaterials used in assays. As a result, the identification of pathogenic bacteria at the location of the incident can be accomplished swiftly and with minimal sample volumes required to ensure public safety. Assays utilizing nanomaterials offer numerous advantages over traditional pathogen detection methods. These include cost-effectiveness, rapidity, and exceptional precision, mainly when applied to high-throughput screening processes. Furthermore, these assays do not require labels and provide real-time responses. Moreover, they adhere to the standards and regulations set forth by regulatory agencies, hospitals, and the food industry. Nonetheless, obstacles exist in the detection of MP. The persistent difficulty in diagnosing pneumonia caused by MP is attributable to the absence of a sensitive, specific, and rapid detection method. Early-stage MP infections are frequently misdiagnosed due to the absence of distinct clinical and imaging features and atypical symptoms. In addition to serological tests, PCR and rapid culture derived from pharynx samples are the principal laboratory diagnostic techniques. Rapid antigen assays are another example. In this review, various nanotechnology-based methods for detecting MP are examined. Although applying nanotechnology to the detection of MP has yielded encouraging results, obstacles remain to be resolved. Further research is necessary to optimize these nanotechnology-based detection methods' sensitivity, specificity, and velocity.

Detecting early signs of disease can significantly mitigate the risk of severe consequences. Chronic kidney disease (CKD), stemming from various underlying conditions like diabetes mellitus, high blood pressure, obesity, and heart disease, manifests as an impairment in the kidneys' ability to efficiently filter blood. Consequently, a small amount of the protein albumin might be excreted into the urine. In this study, we have developed a novel biosensor utilizing copper nanoparticles to identify even trace levels of albumin in urine samples. Unlike conventional immunoassay methods, our biosensor doesn't rely on antibodies for its creation. By utilizing gum tree as a stabilizing agent, we've successfully synthesized the copper nanosensor, achieving distinct optical properties and prolonged stability. This method allowed for the precise quantification of bovine serum albumin (BSA) under optimized conditions. To perform quantitative analysis, we established a calibration curve by plotting the variations in absorbance at 580 nm between the sample and the blank. This assay effectively detected albumin within the concentration range of 25 to 250 mg/L (with an R² value of 0.98), and it exhibited a low limit of detection (LOD) at 6.5 mg/L. Notably, CuNPs demonstrated excellent specificity towards albumin. Moreover, we successfully applied this developed method for the rapid screening of albumin in synthetic and authentic urine samples, achieving recovery percentages ranging from 90% to 104% using UV–visible spectrometry. Overall, this colorimetric method holds significant promise for on-site albumin detection, offering high accuracy, exceptional selectivity, and minimal reagent consumption.

The silver vanadate AgVO@g-CN was synthesized by the Co-precipitation method for the first time. The electrocatalytic potential of the AgVO@g-CN nanocomposite is investigated using cyclic voltammetry and differential pulse voltammetry to detect caffeine (CAF). The linear relationship between peak current and CAF concentration has been determined to be in the 6.5 to 255 μM wide linear range, with a lower detection limit of 0.038 μM. The sensitivity of produced electrode was 5.87 μAμM⁻¹ cm⁻¹. The successful application of the modified AgVO@g-CN nanocomposite electrode for CAF detection demonstrates operational stability, and the novel technique displayed good repeatability and reproducibility. Caffeine levels in commercial coffee, Red Bull, and Coca-Cola were successfully determined using the proposed sensor. The results obtained clearly show the capability of sensing and possible application of AgVO@g-CN nanocomposite for real-time electrochemical detection of CAF.

This article introduces a novel plasmonic magnetic field sensor (MFS) that utilizes a Metal-Insulator-Metal (MIM) waveguide configuration with a W-shaped cavity filled with magnetic fluid (MF). The MFS's unique design combines the advantages of plasmonic sensing, offering a promising solution for the detection of magnetic field strength. It operates based on the inherent properties of surface plasmon polaritons and the magneto-optical properties of MF, resulting in a shift in resonant wavelength. The performance of the proposed MFS has been investigated through numerical calculation employing the finite element method (FEM). Remarkably, the MFS exhibits a maximum magnetic field sensitivity of 49.11 pm/Oe, covering a detection range from 33 Oe to 200 Oe. The recorded figure of merit (FOM) and Q-factor of the MFS are 18.39 and 18.4 respectively, attesting to its high performance and reliability. This innovation has the potential to revolutionize fields such as navigation, medical diagnostics, and robotics technologies by seamlessly integrating optical sensing into traditional devices. The proposed sensor's excellent performance, compact size, and cost-effectiveness position it as a promising technology for widespread adoption, contributing to advancements in magnetic field sensing across scientific, industrial, and technological domains.

In recent years, fiber sensing technology has become more and more important in many fields of applied science. The versatility of the fiber sensors to obtain reliable and precise measurements while maintaining compact size and reduced costs has no comparison in sensing technology. However, the most intriguing property of optical fiber sensors is represented by the possibility to extend the sensing area to the whole length of the optical device. A direct consequence of this property is the capability to achieve a higher density of sensing points, thus making the optical fiber a perfect platform for implementing distributing sensing paradigm. In this context, distributed fiber sensing represents a new opportunity for biomedical applications, where the spatial density of sensing points is fundamental to achieve precise mapping of physical measurands. In this contribution we aim to review the main technologies that achieve higher density of sensing points and distributed sensing, in particular optical frequency domain reflectometry based on Rayleigh scattering. We focus our attention on the key aspects of distributing sensing that enable innovative applications in biomedical field such as, temperature mapping during thermo-therapies, guidance reconstruction of needles and catheters, shape sensing of medical device and other emerging application in the field.

After a decade of research, development, and instrument commercialization, capillary electrophoresis (CE) has firmly established itself as a recognized analytical technique. CE is a separation method that segregates charged species based on their charge and size. In the field of environmental science, CE instruments have emerged as an ideal choice due to their simplicity, efficiency, affordability, and compact design. Furthermore, CE's equipment requirements are straightforward, making it well-suited for easy miniaturization. This review provides a comprehensive overview of the latest advancements in the CE technology, with a focus on its miniaturization. It delves into portable CE and microchip-based CE, exploring their structural characteristics, advantages, and limitations. Additionally, it investigates a modular approach that consolidates all essential components onto a single board, offering a holistic perspective on the innovative possibilities within the realm of miniature capillary electrophoresis.