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Diabetes mellitus accompanies an abnormally high glucose level in the bloodstream. Early diagnosis and proper glycemic management of blood glucose are essential to prevent further progression and complications. Biosensor-based colorimetric detection has progressed and shown potential in portable and inexpensive daily assessment of glucose levels because of its simplicity, low-cost, and convenient operation without sophisticated instrumentation. Colorimetric glucose biosensors commonly use natural enzymes that recognize glucose and chromophores that detect enzymatic reaction products. However, many natural enzymes have inherent defects, limiting their extensive application. Recently, nanozyme-based colorimetric detection has drawn attention due to its merits including high sensitivity, stability under strict reaction conditions, flexible structural design with low-cost materials, and adjustable catalytic activities. This review discusses various nanozyme materials, colorimetric analytic methods and mechanisms, recent machine learning based analytic methods, quantification systems, applications and future directions for monitoring and managing diabetes.

Glucose level is a primary indicator in the diagnosis and treatment of diabetes mellitus. According to the correlation between glucose concentration in blood and tears, measuring tear glucose can be an alternative to traditional strips test for blood glucose. Thus, measuring tear glucose levels could provide noninvasive monitoring of blood glucose. As a biocompatible biosensor, a nanoparticle embedded contact lens (NECL) is developed which is composed of glucose oxidase and cerium oxide (III). Using spectroscopy, we found the detectable changes in reflection spectrum of contact lenses with respect to the glucose concentration, and developed correlation curve of the reflection spectrum with known glucose level. Furthermore, we assessed tear glucose level and compared blood glucose level with the diabetic mouse model to evaluate this approach. Our algorithm for regular monitoring of glucose using contact lens biosensor may lead to noninvasive monitoring of tear glucose level. NECL may provide simple and noninvasive glucose monitoring based on the spectral changes in contact lens biosensor.

Microfluidic devices have revolutionized biosensing by enabling precise manipulation of minute fluid volumes across diverse applications. This review investigates the incorporation of machine learning (ML) into the design, fabrication, and application of microfluidic biosensors, emphasizing how ML algorithms enhance performance by improving design accuracy, operational efficiency, and the management of complex diagnostic datasets. Integrating microfluidics with ML has fostered intelligent systems capable of automating experimental workflows, enabling real-time data analysis, and supporting informed decision-making. Recent advances in health diagnostics, environmental monitoring, and synthetic biology driven by ML are critically examined. This review highlights the transformative potential of ML-enhanced microfluidic systems, offering insights into the future trajectory of this rapidly evolving field.

Accurate freckle segmentation is essential for dermatological assessments and cosmetic applications, but existing lesion detection techniques are primarily designed for well-defined skin abnormalities such as melanomas and tumors, making them less effective at capturing subtle features like freckles. In this study, we present an automated freckle segmentation framework that integrates the Gaussian Mixture Model (GMM) and the Viola-Jones algorithm for skin segmentation, coupled with an energy map-based approach for freckle detection. The process begins with image is clustered using GMM, followed by facial region detection with the Viola-Jones algorithms. A post-processing step then segments the selection of the skin region. Subsequently, an energy map is generated by combining the blue and saturation channels, while Contrast-Limited Adaptive Histogram Equalization (CLAHE) and morphological operations enhance freckle contrast. The final segmentation is achieved through binarization and additional post-processing techniques. Quantitative evaluations demonstrate that the proposed method surpasses conventional approaches in recall, Intersection over Union (IoU), and Dice coefficient, highlighting its effectiveness in accurate freckle detection and segmentation. These findings indicate that, with further refinement, the proposed framework holds significant potential for applications in both clinical dermatology and cosmetic science.

The development of random number generators (RNGs) using speckle patterns is pivotal for secure encryption key generation, drawing from the recent statistical properties identified in speckle-based imaging. Speckle-based RNG systems generate a sequence of random numbers through the unpredictable and reproducible nature of speckle patterns, ensuring a source of randomness that is independent of algorithms. However, to guarantee their effectiveness and reliability, these systems demand a meticulous and rigorous approach. In this study, we present a blood-inspired RNG system with a microfluidics device, designed to generate random numbers at a rate of 5.5 MHz and a high-speed of 1250 fps. This process is achieved by directing a laser beam through a volumetric scattering medium to procure speckle patterns. Additionally, designed microfluidic device requires only a minimal blood sample of 5 µl to capture these speckle patterns effectively. After implementing the two-pass tuple-output von Neumann debiasing algorithm to counteract statistical biases, we utilized the randomness statistical test suite from the National Institute of Standards and Technology for validation. The generated numbers successfully passed these tests, ensuring their randomness and unpredictability. Our blood-inspired RNG, utilizing whole blood, offers a pathway for affordable, high-output applications in fields like encryption, computer security, and data protection.

The crucial role of platelets in hemostasis and their broad implications under various physiological conditions underscore the importance of accurate platelet-function testing. Platelets are key to clotting blood and healing wounds. Therefore, accurate diagnosis and management of platelet disorders are vital for patient care. This review outlines the significant advancements in platelet-function testing technologies, focusing on their working principles and the shift from traditional diagnostic methods to more innovative approaches. These improvements have deepened our understanding of platelet-related disorders and ushered in personalized treatment options. Despite challenges such as interpretation of complex data and the costs of new technologies, the potential for artificial-intelligence integration and the creation of wearable monitoring devices offers exciting future possibilities. This review underscores how these technological advances have enhanced the landscape of precision medicine and provided better diagnostic and treatment options for platelet-function disorders.

The global effort to manage diabetes effectively is driving continuous innovation in glucose monitoring devices. While current systems have improved patient care, persistent challenges with sensor stability and invasiveness highlight the need for advanced, patient-friendly technologies. A particularly promising frontier is emerging from the convergence of advanced polymer science and artificial intelligence (AI), opening new pathways for noninvasive biosensing. This feature review provides a comprehensive overview of polymer-based “hardware”, such as molecularly imprinted polymers (MIPs), conductive polymer hydrogels (CPHs), and functional coatings, which offer robust and biocompatible alternatives to traditional enzyme-based sensors. Concurrently, we examine (AI) “software”, including machine learning and predictive modeling, which enable reliable interpretation of complex biosignals for real-time glucose monitoring. Furthermore, this review highlights critical challenges in scalability, long-term in vivo stability, regulatory approval, and clinical adoption, while discussing strategies for successful translation into pharmaceutical technology and medical devices. By mapping the current landscape and future directions, this review aims to guide research toward the next generation of intelligent, patient-centric, noninvasive glucose monitoring platforms.

Platelet aggregation and adhesion are critically involved in both normal hemostasis and thrombosis during vascular injury. Before any surgery, it is important to identify the number of platelets and their functionality to reduce the risk of bleeding; therefore, platelet function testing is a requirement. We introduce a novel evaluation method of assessing platelet function with laser speckle contrast imaging. The speckle decorrelation time (SDT) of the blood flowing through a microfluidic channel chip provides a quantitative measure of platelet aggregation. We compared SDTs of whole blood and platelet-poor blood, i.e., whole blood stripped of its buffy coat region, and found a marked reduction in decorrelation time for platelet-poor blood. The measured SDT of platelet-poor blood was 1.04 ± 0.21 ms, while that of whole blood was 2.64 ± 0.83 ms. To further characterize the sensitivity of our speckle decorrelation time-based platelet function testing (SDT-PFT), we added various agonists involved in platelet aggregation, including adenosine diphosphate (ADP), epinephrine (EPI), and arachidonic acid (AA). In this study, the results show that whole blood with ADP resulted in the largest SDT, followed by whole blood with AA, whole blood with EPI, whole blood without agonist, and platelet-poor blood with or without agonist. These findings show that SDT-PFT has the potential for rapid screening of bleeding disorders and monitoring of anti-platelet therapies with only a small volume of blood.

Red blood cells (RBCs) undergo irreversible biochemical and morphological changes during storage, contributing to the hemorheological changes of stored RBCs, which causes deterioration of microvascular perfusion in vivo. In this study, a home-built optofluidic system for laser speckle imaging of flowing stored RBCs through a transparent microfluidic channel was employed. The speckle decorrelation time (SDT) provides a quantitative measure of RBC changes, including aggregation in the microchannel. The SDT and relative light transmission intensity of the stored RBCs were monitored for 42 days. In addition, correlations between the decorrelation time, RBC flow speed through the channel, and relative light transmission intensity were obtained. The SDT of stored RBCs increased as the storage duration increased. The SDTs of the RBCs stored for 21 days did not significantly change. However, for the RBCs stored for over 35 days, the SDT increased significantly from 1.26 ± 0.27 ms to 6.12 ± 1.98 ms. In addition, we measured the relative light transmission intensity and RBC flow speed. As the RBC storage time increased, the relative light transmission intensity increased, whereas the RBC flow speed decreased in the microchannel. The optofluidic laser speckle image decorrelation time provides a quantitative measure of assessing the RBC condition during storage. Laser speckle image decorrelation analysis may serve as a convenient assay to monitor the property changes of stored RBCs.

Platelets play essential roles in the formation of blood clots by clumping with coagulation factors at the site of vascular injury to stop bleeding; therefore, a reduction in the platelet number or disorder in their function causes bleeding risk. In our research, we developed a method to assess platelet aggregation using an optical approach within a microfluidic chip’s channel by evaluating the size of laser speckles. These speckles, associated with slowed blood flow in the microfluidic channel, had a baseline size of 28.54 ± 0.72 µm in whole blood. Removing platelets from the sample led to a notable decrease in speckle size to 27.04 ± 1.23 µm. Moreover, the addition of an ADP-containing agonist, which activates platelets, resulted in an increased speckle size of 32.89 ± 1.69 µm. This finding may provide a simple optical method via microfluidics that could be utilized to assess platelet functionality in diagnosing bleeding disorders and potentially in monitoring therapies that target platelets.