Sensors International最新文献

‘Give a man a biosensor, and you enable him to unlock a world of cost-effective solutions for research, diagnosis, and personalized healthcare’.

Biosensors have emerged as a game-changer in the realms of research sciences and healthcare, offering exceptional value for money. The integration of biosensors into these fields holds immense promise, empowering researchers and medical practitioners to unlock intricate mysteries in food and water safety, human biology, and health assessment. These state-of-the-art technologies are a breath of fresh air, revolutionizing disease detection and tracking to unprecedented levels, elevating the ability to monitor the body's response. They have become the linchpin of numerous cost-effective, highly efficient, and streamlined medical devices prevalent in modern healthcare. By harnessing the sensitivity and specificity of biosensors, healthcare professionals can hit the nail on the head, identifying even the subtlest biomarkers and indicators of various ailments, and enabling timely intervention and treatment. The superior quality of these biosensors ensures unrivaled diagnostic accuracy, leading to more reliable and effective healthcare outcomes. In a nutshell, biosensors have raised the bar, making research, public safety, and tailored healthcare options a walk in the park, ultimately enhancing overall health and well-being.

Biosensors offer immense potential in medical diagnostics due to their user-friendly nature, scalability, and efficient manufacturing. With intelligent wearable features, they facilitate seamless health monitoring for the elderly, bridging the gap between self-care and healthcare providers. This exchange of medical information reduces interference and hospital visits, opening avenues in wellness, fitness, and athletics for consumers and commercial entities.

This paper explores the advancements in Biosensors technology and their promising benefits in medicine, focusing on cardiovascular diseases and using informative diagrams. It examines fourteen key applications of Biosensors in the medical field, highlighting the integration of biomedical devices, apps, firmware, and advanced algorithms. These developments pave the way for innovative medical therapies, real-time evidence-based insights, customized solutions, and informed guidance, shaping a bright future for healthcare.

L-tryptophan (L-Trp) is a vital amino acid that sways neuronal function, immunity, and gut homeostasis, and its accurate detection in food samples is crucial. The aim of this study is to integrate zinc cobaltite (ZCO) nanoparticles and 3D porous reduced graphene oxide (rGO) on a screen-printed carbon electrode (SPCE) surface for building a novel electrochemical sensor to sensitively detect L-Trp in food products. A low-temperature aqueous solution method was employed in ZCO nanoflower synthesis and a hydrothermal approach was utilized to prepare 3D rGO. SEM, elemental mapping, XRD, Raman spectroscopy, XPS, and EIS characterizations were performed on the prepared nanocomposite, ZCO/3DrGO. Electrochemical experiments conducted with the cyclic and differential pulse voltammetric techniques were used for effectively assessing the catalytic power of ZCO/3DrGO/SPCE. With a low detection limit of 3 nM, high sensitivity of 19.53 μAμM⁻¹cm⁻², and a broad linear range of 0.08–5.93; 5.93–87.18 μM, the sensor demonstrated promising electrocatalytic activity towards L-Trp. Further, the reliability of the sensor was proved by analyzing its stability, repeatability, reproducibility, and selectivity towards L-Trp. The successful detection of L-Trp in dairy products (yogurt, milk, and cottage cheese) using the proposed sensor evinced its practical feasibility with high recovery of 98.16%–101.16% and low RSD of 2.8%.

This research highlights the significant role of green synthesis in the production of copper oxide (CuO) nanoparticles by using natural extracts as reducing agents. These nanoparticles have shown promising potential in two key applications: photocatalytic degradation of industrial dye effluents and electrochemical sensing of ciprofloxacin. The study found that Arundinaria gigantea leaf extract is an effective reducing agent for synthesizing well-defined crystalline structure CuO nanoparticles, with an average size of 36 nm. The CuO nanoparticles have demonstrated high efficiency in photocatalytic applications, effectively degrading AR88 dye under UV irradiation, making them a viable solution for eco-friendly water purification. Additionally, when incorporated into an electrochemical sensor, these CuO nanoparticles have improved sensitivity and selectivity in detecting ciprofloxacin in aqueous solutions with high accuracy and precision. This study emphasizes the versatility and effectiveness of green-synthesized CuO nanoparticles for various practical uses.

Silicon photonics is a rapidly developing field that offers cost-effective biosensors with improved sensitivity and the potential for interconnecting with other electronic devices for instant disease diagnosis. The Mach Zehnder interferometer architecture (MZI) is a key technology for biosensors, as it detects changes in refractive index (RI) caused by the presence of biomolecules. In this study, a silicon-polymer double-slot waveguide-based MZI was designed, with a small mode area and a large evanescent field to enhance light-analyte interaction. The waveguide was optimized by converting a normal slot waveguide into a double-slot waveguide with varying slot widths. In transmission spectrum, the wavelength shift was measured for both normal and disease samples. Additionally, the loss at a specific wavelength was analyzed to understand the impact of the biomolecule on the sensor performance. The results show that this sensor has a high sensitivity of 2.39 X10^5 nm/RIU, making it a promising candidate for biosensing applications.

Worldwide, there has been an increasing prevalence of kidney disorders for several years. Kidney disorders are characterized by abnormal kidney biomarkers like uric acid, urea, cystatin C, creatinine, kidney injury molecule-1, C-related protein, etc., in the human body. A person suffering from kidney disorders is prone to several other serious health consequences, such as cardiac diseases and renal failure, which can lead to death. However, early diagnosis of kidney disorders requires effective disease management to prevent disease progression. Existing diagnostic techniques used for monitoring kidney biomarker concentration include chromatographic assays, spectroscopic assays, immunoassays, magnetic resonance imaging (MRI), computed tomography (CT), etc. They also necessitate equipped laboratory infrastructure, specific instruments, highly trained personnel working on these instruments, and monitoring kidney patients. Hence, these are expensive and time-consuming. Since the past few decades, a number of biosensors, like electrochemical, optical, immunosensors, potentiometric, colorimetric, etc., have been used to overcome the drawbacks of conventional and modern techniques. These biosensing systems have many benefits, such as being cost-effective, quick, simple, highly sensitive, specific, requiring a minimum sample amount, reliable, and easy to miniaturize. This review article discusses the uses of effectual biosensors for kidney biomarker detection with their potential advantages and disadvantages. Future research needs to be implicated in developing highly advanced biosensors that must be sensitive, economical, and simple so that they can be used for on-site early detection of kidney biomarkers to assess kidney function.

Exploration of entire human body is now possible with the advancement in the field of biotechnology, biosensors and bio-inspired modeling. We model the flow of a fluid between parallel plates for a couple stress fluid in order to incorporate polar effects on the flow. The stream function is used to transform the governing equations to system of ordinary differential equations. The analytical solutions are found for velocity components, pressure distribution, the axial flow rate, the mean pressure drop and the shear stress. The effect of couple stress parameter on the velocity, pressure and the shear stress has been investigated through graphs. We have also used the data from the renal tubule of a rat kidney in our analytical results to study the effect of the couple stress parameter on the mean pressure drop across the slit of the rat’s renal tubule.

A simple, sensitive, and highly selective detection method was developed for creatinine using citrate-capped gold nanoparticles (C-AuNPs). TEM analysis confirmed the synthesis of the C-AuNPs and they were mostly spherical in shape. FTIR data showed peaks at 3302 cm⁻¹, 1635 cm⁻¹, 1219 cm⁻¹ and 771 cm⁻¹ indicating the presence of O–H, C=C, C–O, C–C groups on the surface of the synthesized C-AuNPs. XRD analysis revealed peaks at 33.8, 44.4, 64.6, 77.5, and 81.6° confirming the crystalline nature of the C-AuNPs. The principle of this method is based on the aggregation of C-AuNPs induced by the creatinine molecules which has been successfully employed for the colorimetric detection of creatinine ranging from 0.3 to 0.8 μg/100 μl (3–8 ppm). The degree of aggregation of C-AuNPs was found to have a linear relationship with the concentration of creatinine which allows the development of a colour gradient based on the varying creatinine concentrations. UV–Vis spectrophotometric analysis further confirmed the selectivity of the method among different analytes such as ascorbic acid, nicotinic acid, polyvinyl pyrrolidone, glucose, uric acid, and bovine serum albumin. It has also been successfully applied for the detection of creatinine in urine mimic samples with good recovery rates. Therefore, this method can be successfully employed for both qualitative and quantitative analysis of creatinine.

Different nanomaterials in single (CeO₂), binary (CdS/CeO₂ and Ag₃PO₄/CeO₂), ternary CdS/CeO₂/Ag₃PO₄ (4:1 molar ratio) and conductive polymer supported (PANI-CdS/CeO₂/Ag₃PO₄) were synthesized by co-precipitation method. Elemental analysis, crystal structure, surface area, morphology and optical properties of the as-synthesized nanoparticles were characterized. Electrochemical behavior of glassy carbon electrode modified by polyaniline supported CdS/CeO₂/Ag₃PO₄ nanocomposite were also characterized by electrochemical impedance spectroscopy and cyclic voltammetry in 0.1 M of K₃[Fe(CN)₆] containing 0.1 M KCl at pH 7 with a frequency range of 0.1 to 1000 Hz, with an amplitude of 50 mV. The voltammogramm shows that the process of all as synthesized nanocomposites modified glassy carbon electrode is diffusion controlled. Under optimum conditions, the electrochemical sensor showed Malathion concentrations in linear range of 1-13 $\times$ 10⁻⁷ M, good reproducibility, and no interference by other pesticides and high recovery values around 98.90%. As-synthesized nanocomposite modified glassy carbon electrode exhibits the lowest detection limit of 3.0 $\times$ 10⁻⁹ M for Malathion detection. The simplicity of preparation, high sensitivity, good stability and reproducibility of this nanostructured polyaniline supported CdS/CeO₂/Ag₃PO₄ electrode can be a potential candidate for application in the detection of Malathion.

An electrochemical biosensor for H₂O₂ detection was developed by using soybean peroxidase-copper phosphate mediated organic inorganic hybrid (OIH). The characterization of OIH was carried out by FESEM and FTIR. FESEM analysis showed a flower-like porous morphology of the OIH and FTIR confirmed the presence of soybean peroxidase and copper phosphate in the OIH. For sensor development, the paste of OIH was formulated in the presence of phosphate buffered saline (PBS) and was screen printed on indium tin oxide (ITO) coated glass substrate. Cyclic voltammetry analysis showed that the developed biosensor could detect H₂O₂ in the linear range of 20–100 ​μM with R² value of 0.963. The limit of detection (LOD) and sensitivity values calculated for H₂O₂ are 0.19 ​μM and 27.44 μA/(μM.cm2) respectively. Along with cyclic voltammetry experiments, electrochemical impedance spectroscopy (EIS) analysis was also carried out to study the sensing mechanism. The developed biosensor showed better selectivity towards H₂O₂ when tested against d-glucose, l-tyrosine, l-lysine, and l-ascorbic acid.

This work has been focused on developing a novel biosensor assisted by multivariate calibration methods to determine triglycerides (TGs, triacetin, tributyrin, tricaproin, tricaprylin, and tricaprin) in lyophilized serum samples. To achieve this goal, a bare glassy carbon electrode (GCE) was modified and used as the biosensing platform. To increase the sensitivity of the developed method, hydrodynamic methods were used to calibrate the biosensor response. To increase the selectivity of the developed biosensor, it was assisted by partial least squares-1 (PLS-1), radial basis function-PLS (RBF-PLS), and RBF-artificial neural network (RBF-ANN) for exploiting first-order advantage. After characterization of the modifications, the first-order advantage was exploited to increase the selectivity of the method by building a multivariate calibration set in a pre-analyzed lyophilized serum with different TGs concentrations, which were chosen according to the individual calibration curve. Calibration models were then built in the same pre-analyzed lyophilized serum and analyzed by PLS-1, RBF-PLS, and RBF-ANN. Therefore, their performances were examined to predict concentrations of a validation set. The results confirmed the successfulness of the calibration model developed by RBF-ANN. Finally, it was used to analyze two serum samples, and the results demonstrated that the method was successful because its results were compared with a reference method.