Search Results (1,038)

This numerical study introduces a surface plasmon resonance (SPR)-based biosensor utilizing a kagome lattice-inspired hollow core photonic crystal fiber (PCF) for the highly sensitive detection of various blood biomarkers and analytical components. The sensor is designed to detect key blood biomarkers such as water, glucose, plasma, and hemoglobin (Hb), as well as analytical targets including krypton, sylgard, ethanol, polyacrylamide (PA), and bovine serum albumin (BSA), by monitoring shifts in the resonance wavelength (RW). A dual-polarization approach is employed by analyzing both transverse magnetic (TM) and transverse electric (TE) modes. The proposed sensor demonstrates exceptional performance, achieving maximum wavelength sensitivities (Sw) of 18,900 nm RIU⁻¹ for TM pol. and 16,800 nm RIU⁻¹ for TE pol. Corresponding peak amplitude sensitivities (S_A) of 71,224 RIU⁻¹ for TM pol. and 58,112 RIU⁻¹ for TE pol. were also observed. The peak sensor resolution (S_R) for both modes is on the order of 10⁻⁶ RIU, underscoring its high precision. Owing to its enhanced sensitivity, compact design, and robust dual-polarization capability, the proposed biosensor holds strong promise for point-of-care diagnostics and real-time blood component analysis. Full article

This work describes a non-enzymatic electrochemical glucose biosensor combining for the first time molecularly imprinted polymers (MIPs) for glucose concentration and gold nanoparticles (AuNPs) on screen-printed carbon electrodes (SPEs), where both MIPs and AuNPs were assembled in situ. Electrochemical impedance spectroscopy (EIS) was used to evaluate the analytical performance of the sensor, which has a linear range between 1.0 µM and 1.0 mM when standard solutions are prepared in buffer. Direct measurement of glucose was performed by chronoamperometry, measuring the oxidation current generated during direct glucose oxidation. The selectivity was tested against ascorbic acid and the results confirmed a selective discrimination of the electrode for glucose. Overall, the work presented here represents a promising tool for tracking glucose levels in serum. The use of glucose MIP on the electrode surface allows the concentration of glucose, resulting in lower detection limits, and the use of AuNPs reduces the potential required for the oxidation of glucose, which increases selectivity. In addition, this possible combination of two analytical measurements following different theoretical concepts can contribute to the accuracy of the analytical measurements. This combination can also be extended to other biomolecules that can be electrochemically oxidised at lower potentials. Full article

Diabetic wounds are characterized by a refractory healing cycle resulting from the synergistic effects of hyperglycemic microenvironment, oxidative stress, bacterial infection, and impaired angiogenesis. Conventional hydrogel dressings, with limited functionality, struggle to address the complexities of chronic diabetic ulcers. Smart hydrogels, possessing biocompatibility, porous architectures mimicking extracellular matrix, and environmental responsiveness, have emerged as promising biomaterials for diabetic wound management. This review systematically elucidates the specific response mechanisms of smart hydrogels to wound microenvironmental stimuli, including pH, matrix metalloproteinase-9 (MMP-9), reactive oxygen species (ROS), and glucose levels, enabling on-demand release of antimicrobial agents and growth factors through dynamic bond modulation or structural transformations. Subsequently, the review highlights recent advances in novel hydrogel-based sensors fabricated via optical (photonic crystal, fluorescence) and electrochemical principles for real-time monitoring of glucose levels and wound pH. Finally, critical challenges in material development and scalable manufacturing of multifunctional hydrogel components are discussed, alongside prospects for precision diagnostics and therapeutics in diabetic wound care. Full article

Sweat-based electrochemical sensors for wearable applications have attracted substantial interest due to their non-invasive nature, compact design, and ability to provide real-time data. Remarkable advancements have been made in integrating these devices into flexible platforms. While thin-film polymer substrates are frequently employed for their durability, the prolonged buildup of sweat on such materials can disrupt consistent sensing performance and adversely affect skin comfort over extended periods. Therefore, investigating lightweight, comfortable, and breathable base materials for constructing working electrodes is essential for producing flexible and breathable sweat electrochemical sensors. In this study, nylon fabric was chosen as the base material for constructing the working electrode. The electrode is prepared using a straightforward printing process, incorporating Ti₃C₂T_X MXene/polyaniline and methylene blue as modification materials in the electronic intermediary layer. The synergistic effect of the modified layer and the multi-level structure of the current collector enhances the electrochemical kinetics on the electrode surface, improves electron transmission efficiency, and enables the nylon fabric-based electrode to accurately and selectively measure glucose concentration in sweat. It exhibits a wide linear range (0.04~3.08 mM), high sensitivity (3.11 μA·mM⁻¹), strong anti-interference capabilities, and high stability. This system can monitor glucose levels and trends in sweat, facilitating the assessment of daily sugar intake for personal health management. Full article

Microneedles have emerged as a versatile technology for biosensing across biomedical domains and are increasingly being explored for other applications like agriculture. This review highlights recent advancements in the development of microneedle-based biosensors in novel areas. Biomedical applications include continuous glucose monitoring, multiplexed biomarker detection beyond glucose, and numerous recent works presenting fully integrated systems comprising microneedle arrays alongside miniaturized wearable electronics. Agricultural applications largely focus on the detection of plant growth markers, hormones, and nutrient levels. Despite significant progress, challenges remain in overcoming biofouling and electrode degradation, optimizing electrode longevity for long-term (weeks to months) in situ monitoring, and creating scalable sensor fabrication processes. Additionally, there is a need for standardized mechanical and electrical testing protocols, and guidelines specifying critical performance metrics that should be reported to facilitate accurate literature comparisons. The review concludes by outlining key opportunities for future research to address these persisting challenges. Full article

Metabolic diseases are increasing in relevance both in health and the economy in most countries. In this direction, if gold-standard technologies are based on blood analysis, non-invasive glucose monitoring is a relevant and great challenge that has not yet been fully resolved. Sweat represents a more suitable medium for the non-invasive sensing and monitoring of glucose than other bodily fluids, such as saliva, tears, or urine. However, the measurement of glucose levels requires the use of highly precise and sensitive sensors, given the low glucose concentration in sweat. This paper provides an overview of the patent landscape related to wearable biosensors for the monitoring of glucose levels in sweat. Full article

Aim: The purpose of this study was to explore the broad experience of continuous glucose monitoring from the perspective of patients diagnosed with type 1 diabetes mellitus, including not only their emotions and feelings but also the lifestyle changes, perceptions, and social aspects associated with its use. Design: This is a phenomenological qualitative study. Patient or Public Contribution: The sample consisted of 10 adult patients diagnosed with type 1 diabetes who had been using the continuous glucose monitoring system for at least 6 months and were patients of the Endocrinology and Nutrition Service of the University Hospital Complex of Ourense. Methods: The recorded interviews were conducted in November 2024. The conversations were audio-recorded with the participants’ consent, and then transcribed for thematic analysis. Results: Three main categories were identified: “experience prior to continuous glucose monitoring” (accessibility, prior knowledge, and expectations), “experience with the use of continuous glucose monitoring” (perception of healthcare support, concerns, strengths, and alarm management), and “experience regarding the disease” (self-management of the disease and safety). Despite the fact that diabetes mellitus is a complex chronic disease, all participants provided a positive assessment of their progress and improved control through continuous glucose monitoring. Conclusions: All participants felt more secure and protected with continuous glucose monitoring, improving their quality of life. The main concern among the subjects was the possibility of the sensor failing. They positively valued the alarm system in case of hypoglycemia. The CGM is a highly effective tool for the management and self-control of diabetes and promotes the relationship between patients and professional health. Impact: The findings of this study have important implications for clinical care, highlighting the need for more training and more health education at the first level of health care, such as health centers. Full article

Numerous research projects on biosensors have been conducted, and a substantial number of academic studies and conference papers on biosensors are published annually. However, only a few biosensors have been commercialized. In this review, we took blood glucose meters as an example to review the development, characteristics, and challenges of biosensors in the literature. The four subsystems of the physical sensors are illustrated to emphasize the importance of standardization and traceability in the sensors. The development of physical sensors, chemical sensors, and biosensors is introduced. The importance of reference materials as a standard for evaluating sensor performance is emphasized. The basic technique and four types of chemical transducers are described, and we show that the biosensors’ response must be processed with these chemical sensors. The characteristics of the glucose meter are introduced to explain the success of this sensor, especially the sensing materials of glucosidases. Two types of highly developed and competitive biosensors, continuous glucose monitoring (CGM) and paper-based biosensors, are introduced, and the trends and future implications of both biosensors are illustrated. The challenges facing biosensor development are summarized into several key factors, and future research directions are discussed. A list of factors for the successful commercialization of biosensors is also proposed. Full article

Introduction: In healthcare centers with limited resources, or for patients who prefer to make continuous changes in their treatment themselves and do not want to rely solely on technology, intermittent glucose monitoring (isCGM) with an insulin pump is a viable option that warrants further study. Material and methods: prospective single-center study that collected data at 3 months and after isCGM implantation in pediatric patients with Type 1 diabetes, categorized according to their insulin regimen. Results: We found statistically significant differences in the time in range (TIR) between 70 and 180 mg/dl at 3 months after using the sensor (p = 0.017), although these differences were not maintained at 1 year (p = 0.064). When stricter TIRs (70–140 mg/dl) were analyzed, statistically significant differences were observed at 3 months (p = 0.01) and at 1 year (p = 0.018) in favor of patients using CSII. While 75% of the patients in the CSII group had good control with HbA1c < 7% after one year of sensor use, only 34.6% in the MDI group achieved these values. However, the CSII group presented a higher coefficient of variation (62.31% at 3 months and 43.08% at 1 year) (p = 0.02), and a higher number of hypoglycemic episodes (7.38% and 7.32%, respectively) (p = 0.016). The CSII group also had a higher number of capillary blood glucose measurements at the beginning of the study (8.32/day) (p = 0.249), but this number became similar between both groups after one year. Conclusions: We found statistically significant differences in favor of CSII over MDI in terms of metabolic control after one year of isCGM use. However, the TIR values were still below the range considered to be indicative of good control. These findings lead us to question whether CSII should be initially considered in specific cases where HCL is not possible, or if it would be more effective to wait until the patient is ready, or the necessary resources are available to start directly CSII integrated in a closed loop system. Full article

Recently, the incidence of diabetes has increased across all socioeconomic groups, with a notable increase in developing countries. Although advances in medical devices have enhanced healthcare accessibility, these benefits remain largely out of reach for individuals residing in remote areas. Concurrently, a variety of devices have been created to detect glucose biomarkers. Among these, microfluidic paper-based sensors have received substantial attention due to their affordability, disposability, and ease of production. Research on microfluidic paper-based glucose sensors has become particularly prominent owing to their considerable potential and wide applicability, especially in the integration of artificial intelligence and machine learning in glucose sensor processing. This review aims to examine recent advancements and progress in the development of microfluidic paper-based glucose sensors over the past five years, highlighting their advantages, limitations, and prospects. The sensors combined with artificial intelligence and machine learning have potential for future applications. Full article

Sensor selection in IoT-based smart healthcare systems is a complex fuzzy decision-making problem due to the presence of numerous uncertain and interdependent evaluation criteria. Traditional fuzzy multi-criteria decision-making (MCDM) approaches often assume independence among criteria and rely on aggregation operators that impose sharp transitions between preference levels. These assumptions can lead to decision outcomes with insufficient differentiation, limited discriminatory capacity, and potential issues in consistency and sensitivity. To overcome these limitations, this study proposes a novel fuzzy decision-making framework by integrating Quasi-D-Overlap functions into the fuzzy MARCOS (Measurement of Alternatives and Ranking According to Compromise Solution) method. Quasi-D-Overlap functions represent a generalized extension of classical overlap operators, capable of capturing partial overlaps and interdependencies among criteria while preserving essential mathematical properties such as associativity and boundedness. This integration enables a more intuitive, flexible, and semantically rich modeling of real-world fuzzy decision problems. In the context of real-time health monitoring, a case study is conducted using a hybrid edge–cloud architecture, involving sensor tasks such as heartrate monitoring and glucose level estimation. The results demonstrate that the proposed method provides greater stability, enhanced discrimination, and improved responsiveness to weight variations compared to traditional fuzzy MCDM techniques. Furthermore, it effectively supports decision-makers in identifying optimal sensor alternatives by balancing critical factors such as accuracy, energy consumption, latency, and error tolerance. Overall, the study fills a significant methodological gap in fuzzy MCDM literature and introduces a robust fuzzy aggregation strategy that facilitates interpretable, consistent, and reliable decision making in dynamic and uncertain healthcare environments. Full article

The detection of glucose concentration has a wide range of applications and plays a significant role in the fields of the food industry, medical health, and illness diagnostics. The utilization of sensor technology for glucose concentration detection is an effective approach. Glucose sensors utilizing nanomaterials, with high sensitivity, strong resistance to interference, and compact size, exhibit tremendous potential in glucose concentration detection. Traditional enzyme-based sensors exhibit superior selectivity and high sensitivity; however, they are deficient in terms of interference resistance capabilities. With the development of nanotechnology, the performance of glucose sensors has been significantly improved. This review discusses the research progress in non-enzymatic electrochemical glucose nanosensors, including noble metal-based glucose sensors and non-noble transition metal compound-based glucose sensors, as well as the applications of multimetallic materials in nanosensors. Additionally, the application of nanosensors based on fluorescence and colorimetric principles in the detection of glucose concentration is introduced in this review. Finally, a perspective on the challenges and prospects of nanosensors in the field of glucose detection is presented. Full article

Molecular sensor systems, e.g., implantables and wearables, provide extensive health-related monitoring. Glucose sensor systems have historically prevailed in wearable bioanalysis applications due to their continuous and reliable glucose monitoring, a feat not yet accomplished for other biomarkers. However, the advancement of reagentless detection methodologies may facilitate the creation of molecular sensor systems for multiple analytes. Improving the sensitivity and selectivity of molecular sensor systems is also crucial for biomarker detection under intricate physiological circumstances. The term multidomain molecular sensor systems is utilized to refer, in general, to both biological and chemical sensor systems. This review examines methodologies for enhancing signal amplification, improving selectivity, and facilitating reagentless detection in multidomain molecular sensor devices. The review also analyzes the fundamental components of multidomain molecular sensor systems, including substrate materials, bodily fluids, power, and decision-making units. The review article further investigates how extensive data gathered from multidomain molecular sensor systems, in conjunction with current data processing algorithms, facilitate biomarker detection for precision medicine. Full article

Milk lactose concentration has been proposed as a noninvasive indicator of metabolic health in dairy cows, particularly during early lactation when metabolic demands are elevated. This study aimed to investigate the relationship between milk lactose levels and physiological, biochemical, and behavioral parameters in early-lactation Holstein cows. Twenty-eight clinically healthy cows were divided into two groups: Group 1 (milk lactose < 4.70%, n = 14) and Group 2 (milk lactose ≥ 4.70%, n = 14). Both groups were monitored over a 21-day period using the Brolis HerdLine in-line milk analyzer (Brolis Sensor Technology, Vilnius, Lithuania) and SmaXtec intraruminal boluses (SmaXtec Animal Care Technology^®, Graz, Austria). Parameters including milk yield, milk composition (lactose, fat, protein, and fat-to-protein ratio), blood biomarkers, and behavior were recorded. Cows with higher milk lactose concentrations (≥4.70%) produced significantly more milk (+12.76%) and showed increased water intake (+15.44%), as well as elevated levels of urea (+21.63%), alanine aminotransferase (ALT) (+22.96%), glucose (+4.75%), magnesium (+8.25%), and iron (+13.41%) compared to cows with lower lactose concentrations (<4.70%). A moderate positive correlation was found between milk lactose and urea levels (r = 0.429, p < 0.01), and low but significant correlations were observed with other indicators. These findings support the use of milk lactose concentration as a practical biomarker for assessing metabolic and physiological status in dairy cows, and highlight the value of integrating real-time monitoring technologies in precision livestock management. Full article

Selenium (Se) is an essential trace element involved in antioxidant redox regulation, thyroid hormone metabolism, and cancer prevention. Among its different forms, elemental selenium (Se⁰), particularly at the nanoscale, has gained growing attention in food, feed, and biomedical applications due to its lower toxicity and higher bioavailability compared to inorganic selenium species. However, the detection of Se⁰ in real samples remains challenging as current analytical methods are time-consuming, labour-intensive, and often unsuitable for rapid analysis. In this study, we developed a method for rapidly measuring Se⁰ using carbon nanodots (CNDs) produced from the Maillard reaction between glucose and glycine. The fabricated CNDs were water-dispersible and strongly fluorescent, with an average particle size of 3.90 ± 1.36 nm. Comprehensive characterisation by transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), fluorescence spectroscopy, and Raman spectroscopy confirmed their structural and optical properties. The CNDs were employed as fluorescent probes for the selective detection of Se⁰. The sensor showed a wide linear detection range (0–12.665 mmol L⁻¹), with a low detection limit (LOD) of 0.381 mmol L⁻¹ and a quantification limit (LOQ) of 0.465 mmol L⁻¹. Validation with spiked real samples—including ultra-pure water, tap water, and soft drinks—yielded high recoveries (98.6–108.1%) and low relative standard deviations (<3.4%). These results highlight the potential of CNDs as a simple, reliable, and environmentally friendly sensing platform for trace-level Se⁰ detection in complex food and beverage matrices. Full article