Biosensors-Basel最新文献

This article explores the development and application of innovative piezoelectric sensors in point-of-care diagnostics. It highlights the significance of bedside tests, such as lateral flow and electrochemical tests, in providing rapid and accurate results directly at the patient's location. This paper delves into the principles of piezoelectric assays, emphasizing their ability to detect disease-related biomarkers through mechanical stress-induced electrical signals. Various applications of piezoelectric chemosensors and biosensors are discussed, including their use in the detection of cancer biomarkers, pathogens, and other health-related analytes. This article also addresses the integration of piezoelectric materials with advanced sensing technologies to improve diagnostic accuracy and efficiency, offering a comprehensive overview of current advances and future directions in medical diagnostics.

Viral infectious diseases pose a serious threat to global public health due to their high transmissibility, rapid mutation rates, and limited treatment options. Recent outbreaks of diseases such as plague, monkeypox, avian influenza, and coronavirus disease 2019 (COVID-19) have underscored the urgent need for efficient diagnostic and surveillance technologies. Focusing on viral infectious diseases that seriously threaten human health, this review summarizes and analyzes detection techniques from the perspective of combining viral surveillance and prevention advice, and discusses applications in improving diagnostic sensitivity and specificity. One of the major innovations of this review is the systematic integration of advanced biorecognition and detection technologies, such as bionanosensors, rapid detection test strips, and microfluidic platforms, along with the exploration of artificial intelligence in virus detection. These technologies address the limitations of traditional methods and enable the real-time monitoring and early warning of viral outbreaks. By analyzing the application of these technologies in the detection of pathogens, new insights are provided for the development of next-generation diagnostic tools to address emerging and re-emerging viral threats. In addition, we analyze the current progress of developed vaccines, combining virus surveillance with vaccine research to provide new ideas for future viral disease prevention and control and vaccine development, and call for global attention and the development of new disease prevention and detection technologies.

Diabetes mellitus is a pathological condition that requires continuous measurement of glucose concentration in human blood. In this study, two enzymatic mediator-free glucose biosensors based on premodified graphite rod (GR) electrodes were developed and compared. GR electrode modified with electrochemically synthesized dendritic gold nanostructures (DGNS), a cystamine (Cys) self-assembled monolayer (SAM), and glucose oxidase (GOx) (GR/DGNS/Cys/GOx) and GR electrode modified with DGNS, Cys SAM, enzymatically obtained polyaniline (PANI) nanocomposites with embedded 6 nm gold nanoparticles (AuNPs) and GOx (GR/DGNS/Cys/PANI-AuNPs-GOx/GOx) were investigated electrochemically. Biosensors based on GR/DGNS/Cys/GOx and GR/DGNS/Cys/PANI-AuNPs-GOx/GOx electrodes were characterized by a linear range (LR) of up to 1.0 mM of glucose, storage stability of over 71 days, sensitivity of 93.7 and 72.0 μA/(mM cm²), limit of detection (LOD) of 0.027 and 0.034 mM, reproducibility of 13.6 and 9.03%, and repeatability of 8.96 and 8.01%, respectively. The GR/DGNS/Cys/PANI-AuNPs-GOx/GOx electrode was proposed as more favorable for glucose concentration determination in serum due to its better stability and resistance to interfering electrochemically active species. The technological solutions presented in this paper are expected to enable the development of innovative mediator-free enzymatic glucose biosensors, offering advantages for clinical assays, particularly for controlling blood glucose concentration in individuals with diabetes.

Quantitative nucleic acid detection is widely used in molecular diagnostics for infectious diseases. Here, we demonstrate that the previously developed MLFIA (magnetically localized fluorescent immunoassay) has the potential to detect Polymerase Chain Reaction (PCR) and loop-mediated isothermal amplification (LAMP) products using biotinylated and fluorescent primers and streptavidin-coated magnetic nanoparticles. The functionalized nanoparticles separate amplified DNA from non-incorporated primers in situ, allowing the quantification of DNA products. We compare magnetically localized fluorescence detection to commercial technologies based on the DNA intercalation of fluorescent dyes. Our system allows the detection of PCR and LAMP products but is approximately 10 times less sensitive than standard commercial assays. Future optimizations, such as enhancing the signal-to-noise ratio and improving nanoparticle functionalization, could significantly increase sensitivity and bring it closer to current diagnostic standards. This work highlights the potential of magnetically localized fluorescence detection to detect DNA.

Peritoneal dialysis (PD) is a vital treatment for end-stage renal disease patients, but its efficacy is often compromised by complications such as infections and peritoneal fibrosis. Biological field-effect transistors (BioFETs) present a promising solution for rapid, sensitive, and non-invasive detection of indicators and biomarkers associated with these complications, potentially enabling early intervention. However, BioFETs are yet to be adopted for PD monitoring. This review presents a forward-looking analysis of the capacity and potential integration of BioFETs into PD management systems, highlighting their capacity to monitor both routine indicators of dialysis efficiency and metabolic status, as well as specific biomarkers for complications such as inflammation and fibrosis. We examine the challenges in adapting BioFETs for PD applications, focusing on key areas for improvement, including sensitivity, specificity, stability, reusability, and clinical integration. Furthermore, we discuss various approaches to address these challenges, which are crucial for developing point-of-care (PoC) and multiplexed wearable devices. These advancements could facilitate continuous, precise, and user-friendly monitoring, potentially revolutionizing PD complication management and enhancing patient care.

Detecting kidney function biomarkers is critical for the early diagnosis of kidney diseases and monitoring treatment efficacy. In this work, a portable, 3D-printed colorimetric sensor platform was developed to detect key kidney biomarkers: uric acid, creatinine, and albumin. The platform features a 3D-printed enclosure with integrated diffused LED lighting to ensure a controlled environment for image acquisition. A disposable 3D-printed flow cell holds samples, ensuring precision and minimizing contamination. The sensor relies on colorimetric analysis, where a reagent reacts with blood serum to produce a color shift proportional to the biomarker concentration. Using a smartphone, the color change is captured, and RGB values are normalized to calculate concentrations based on the Beer-Lambert Law. The system adapts to variations in smartphones, reagent brands, and lighting conditions through an adaptive calibration algorithm, ensuring flexibility and accuracy. The sensor demonstrated good linear detection ranges for uric acid (1-30 mg/dL), creatinine (0.1-20 mg/dL), and albumin (0.1-8 g/dL), with detection limits of 1.15 mg/dL, 0.15 mg/dL, and 0.11 g/dL, respectively. These results correlated well with commercial biochemistry analyzers. Additionally, an Android application was developed to handle image processing and database management, providing a user-friendly interface for real-time blood analysis. This portable, cost-effective platform shows significant potential for point-of-care diagnostics and remote health monitoring.

Cortisol, a steroid hormone, is closely associated with human mental stress. The rapid, real-time, and continuous detection of cortisol using wearable devices offers a promising approach for individual mental health. These devices must exhibit high sensitivity and long-term stability to ensure reliable performance. This study developed a wearable electrochemical sensor based on molecularly imprinted polymer (MIP) technology for real-time and dynamic monitoring of cortisol in sweat. A flexible gold (Au) electrode with interfacial hydrophilic treatment was employed to construct a highly stable electrode. The integration of a silk fibroin/polyvinylidene fluoride (SF/PVDF) composite membrane facilitates directional sweat transport, while liquid metal bonding enhances electrode flexibility and mechanical anti-delamination capability. The sensor exhibits an ultrawide detection range (0.1 pM to 5 μM), high selectivity (over 100-fold against interferents such as glucose and lactic acid), and long-term stability (less than 3.76% signal attenuation over 120 cycles). Additionally, a gradient modulus design was implemented to mitigate mechanical deformation interference under wearable conditions. As a flexible wearable device for cortisol monitoring in human sweat, the sensor's response closely aligns with the diurnal cortisol rhythm, offering a highly sensitive and interference-resistant wearable solution for mental health monitoring and advancing personalized dynamic assessment of stress-related disorders.

Cardiovascular diseases have long been a major challenge to human health, and the treatment differences caused by individual variability remain unresolved. In recent years, personalized cardiovascular drug therapy has attracted widespread attention. This paper reviews the strategies for achieving personalized cardiovascular drug therapy through traditional dynamic monitoring and multidimensional data integration and analysis. It focuses on key technologies for dynamic monitoring, dynamic monitoring based on individual differences, and multidimensional data integration and analysis. By systematically reviewing the relevant literature, the main challenges in current research and the proposed potential directions for future studies were summarized.

The Glucose Management Indicator (GMI) is a biomarker of glycemic control which estimates hemoglobin A1c (HbA1c) based on the average glycemia recorded by continuous glucose monitoring sensors (CGMS). The GMI provides an immediate overview of the patient's glycemic control, but it might be biased by the patient's sensor wear adherence or by the sensor's reading errors. This study aims to evaluate the GMI's performance in the assessment of glycemic control and to identify the factors leading to erroneous estimates. In this study, 147 patients with type 1 diabetes, users of CGMS, were enrolled. Their GMI was extracted from the sensor's report and HbA1c measured at certified laboratories. The median GMI value overestimated the HbA1c by 0.1 percentage points (p = 0.007). The measurements had good reliability, demonstrated by a Cronbach's alpha index of 0.74, an inter-item correlation coefficient of 0.683 and an inter-item covariance between HbA1c and GMI of 0.813. The HbA1c and the difference between GMI and HbA1c were reversely associated (Spearman's r = -0.707; p < 0.001). The GMI is a reliable tool in evaluating glycemic control in patients with diabetes. It tends to underestimate the HbA1c in patients with high HbA1c values, while it tends to overestimate the HbA1c in patients with low HbA1c.

This review explores the development, technological foundations, and applications of biosensor technologies across various fields, such as medicine for disease diagnosis and monitoring, and the food industry. However, the primary focus is on their use in detecting contaminants and pathogens, as well as in environmental monitoring for water quality assessment. The review classifies different types of biosensors based on their bioreceptor and transducer, highlighting how they are specifically designed for the detection of emerging contaminants (ECs) and pathogens in water. Key innovations in this technology are critically examined, including advanced techniques such as systematic evolution of ligands by exponential enrichment (SELEX), molecularly imprinted polymers (MIPs), and self-assembled monolayers (SAMs), which enable the fabrication of sensors with improved sensitivity and selectivity. Additionally, the integration of microfluidic systems into biosensors is analyzed, demonstrating significant enhancements in performance and detection speed. Through these advancements, this work emphasizes the fundamental role of biosensors as key tools for safeguarding public health and preserving environmental integrity.