Search Results (1,125)

In the context of research aimed at identifying the causes of the progressive decline in cellular and tissue functions characteristic of aging, in recent decades, increasing attention has been devoted to the sirtuin family. Sirtuins are named after the Sir2 protein of Saccharomyces cerevisiae, a product of the SIR gene family, known as “silent information regulator 2”. Sirtuins are NAD⁺-dependent protein deacetylases and deacylases characterized by a conserved catalytic domain of approximately 275 amino acids. The removal of acetyl groups from acetyl-lysine residues on proteins is critical in regulating a wide range of biological functions, including gene silencing, genome stability, longevity, metabolism, and cellular physiology. In humans, the sirtuin family comprises seven isoforms (SIRT1–SIRT7), each with specific substrate preferences and primarily, but not exclusively, localized in the nucleus (SIRT1, SIRT6, and SIRT7), cytoplasm (SIRT2), and mitochondria (SIRT3, SIRT4, and SIRT5). Sirtuins may regulate numerous cellular processes associated with survival and longevity, including transcription and DNA repair, inflammation, glucose and lipid metabolism, oxidative stress, mitochondrial function, apoptosis, autophagy, and stress resistance. Sirtuins’ dependence on NAD⁺ allows them to function as cellular energy sensors, linking metabolic demands to selective lysine deacylation in various subcellular organelles. The aim of this review is to provide an update on this family of molecules, describing their molecular structures, physiological functions, roles in aging processes, and potential to be modulated to serve as a strategy for promoting healthy aging. Full article

This systematic review examines how gait analysis has been applied to understand, detect, and manage diabetes and its complications, with a focus on wearable sensor technologies and computational methods. A total of 30 studies were identified from IEEE Xplore, Scopus, and Google Scholar databases using systematic search and screening processes. Data extraction followed a structured framework addressing research questions on gait applications, technologies, and associated parameters. Results indicate that wearable sensor technologies, coupled with advanced computational modeling and machine learning, can capture meaningful gait alterations associated with long-term metabolic dysregulation and neuropathic changes. Applications range from diabetic neuropathy detection and foot ulcer prevention to intervention evaluation and early biomarker identification. The review highlights current progress and outlines future directions toward predictive gait analytics that may serve as indirect, secondary markers of metabolic status and improve diabetes care outcomes. Furthermore, this synthesis provides evidence for integrating wearable gait assessment into diabetes management protocols, potentially enabling early detection of complications, personalized intervention strategies, and non-invasive monitoring approaches that complement traditional glucose measurements. Full article

In₂O₃ has high electron mobility, strong affinity for oxidizing gases, and abundant tunable surface oxygen species. These features enable efficient charge transfer during ozone adsorption, making In₂O₃ a promising ozone-sensing material. However, conventional In₂O₃-based gas sensors still suffer from insufficient sensitivity at low ozone concentrations and slow response/recovery rates, limiting their performance for high-precision gas detection. In this study, morphology-controlled In₂O₃ nanorods were synthesized via a glucose-assisted hydrothermal method, enabling coordinated regulation of the material structure and surface properties. Compared with conventional In₂O₃ nanocubes, the glucose-modulated In₂O₃ nanorods exhibited an approximately sevenfold increase in response toward 1 ppm O₃, indicating markedly improved capability for detecting low-concentration ozone. In addition, the sensor demonstrated a relatively low detection limit of about 80 ppb and fast response/recovery behavior (108 s/238 s). This strategy improves gas sensing performance through morphology optimization, increased surface active sites, and enhanced electron transport, offering a feasible materials design route for high-performance ozone gas sensors and showing potential for real-time environmental ozone monitoring and related applications. Full article

This work presents a compact microwave sensor for noninvasive blood glucose monitoring based on a substrate-integrated waveguide loaded with a complementary split-ring resonator on RO4350. The sensing principle uses shifts in resonance frequency and changes in S-parameters to track the dielectric dispersion of glucose-containing tissue. The resonator is constructed using Substrate-Integrated Waveguide (SIW) technology, which mimics the propagation characteristics of a conventional rectangular waveguide. To validate its versatility, the sensor implements three practical sample delivery modes: direct liquid contact with the sensing surface, a glass tube holder mounted over the active region, and a non-invasive fingertip interface. Electromagnetic simulations and benchtop measurements confirm clear glucose-dependent frequency shifts with stable matching and insertion levels. Across the physiological range of 20 to 200 mg·dL⁻¹, the sensor exhibits clear glucose-dependent resonance shifts in all configurations. In direct contact mode, the resonance frequency shifts from 10.83 GHz to 10.45 GHz with sensitivities up to 2.47 MHz per mg·dL⁻¹. The tube configuration shows a shift from 10.49 GHz to 10.38 GHz with sensitivity up to 0.80 MHz per mg·dL⁻¹, while reducing contamination. In the non-invasive fingertip mode, the resonance shifts from 2.56 GHz to 2.52 GHz with sensitivities up to 0.25 MHz per mg·dL⁻¹. These results confirm the sensor’s compactness, reliability, and suitability for portable, low-cost glucose monitoring. The results indicate that the proposed sensor can support practical continuous or spot monitoring and offers a clear path toward portable and low-cost glucose assessment. Full article

This paper provides a feasibility study of a non-invasive microwave-based glucose-sensing system based on a small printed slot antenna with etched step-impedance resonators (SIRs) on an FR4 substrate in the ground plane at approximately 5.7 GHz. The sensor proposed takes advantage of the effect of the antenna resonant frequency and reflection coefficient (S11) perturbation due to the dielectric loading of a human finger placed in the antenna near field. Instead of declaring direct glucose specificity, this paper is dedicated to understand whether the measures of RF can be translated to the invasive glucose values under the condition of controlled positioning. A vector network analyzer was used to measure the experimental values where resonant frequency and S11 magnitude were obtained at the point of peak sensitivity due to fixed finger placement at the point. These RF properties were associated with invasively measured glucose values using three modeling methods: a simple analytical linear formula, a second-degree Polynomial Ridge regression model, and a Random Forest machine learning model. The comparative analysis has established that nonlinear data-driven models outperform the analytical formulations significantly with the highest predictive accuracy being the Random Forest model (R² = 0.72, RMSE = 10.57 mg/dL, MAE = 5.16 mg/dL). The findings affirm that the impacts of antenna loading control the raw measurements, but the trend related to glucose can be extracted upon machine learning calibration under controlled conditions. The research provides a methodological framework of RF-based non-invasive glucose sensing and the need to employ various phantom-based validation, sub-subject-based modeling, or clinically based evaluation metrics in future studies. Full article

The flexible foam piezoresistive sensor demonstrates significant potential for wearable strain-sensing applications due to its substantial deformation capacity, excellent flexibility, and cost effectiveness. However, conventional flexible foam piezoresistive sensors often struggle to simultaneously achieve high sensitivity, a wide pressure detection range, fast response and long-term stability. This paper employed a glucose-based sugar-templating method to fabricate a fine-pore (50 μm) foam structure complemented by a dual-filler strategy to enhance overall performance. A robust porous conductive network was constructed by embedding zinc oxide (ZnO) and multi-walled carbon nanotubes (MWCNTs) into a polydimethylsiloxane (PDMS) matrix. The resulting sensor exhibits outstanding piezoresistive properties, featuring a wide linear detection range (0–80% strain) and a high sensitivity of 9.02 kPa⁻¹ within the 0–10 kPa pressure range. It demonstrates rapid response/recovery times of 50/70 ms and maintains stable output performance even after 5000 compression cycles at 300 kPa. The sensor also exhibits negligible environmental interference and excellent long-term stability. When attached to finger joints, feet soles, or the throat, the sensor enables functions such as finger bending recognition, race-walking violation discrimination, gait analysis, and vocal fold vibration recognition, thereby demonstrating its considerable potential for application in human–computer interaction and human motion detection. Full article

Wireless Body Area Networks (WBANs) enable real-time health monitoring essential for timely clinical intervention, yet their performance is frequently hindered by sensor degradation, noise interference, and strict low-latency constraints in resource-limited environments. Conventional preprocessing approaches indiscriminately reprocess all incoming data, including uncorrupted samples, thereby increasing computational overhead, introducing latency, and potentially distorting valid physiological trends. This study introduces a unified real-time monitoring framework tailored for WBAN systems. The key contributions include: (1) an adaptively gated multi-stage preprocessing pipeline that selectively restores corrupted samples while preserving clean data, (2) an overlap-aware sliding-window mechanism enabling low-latency operation, and (3) a clinically informed risk assessment strategy for early-warning support. By avoiding unnecessary modification of intact signals, the framework maintains physiological integrity while substantially improving reconstruction and predictive reliability. Across multiple vital signs, the proposed approach achieves substantial reconstruction gains, with Mean Squared Error (MSE) reductions ranging from 53% to 67% under strong degradation conditions. An adaptive ARIMA-based forecasting layer captures short-term physiological dynamics with directional accuracies of approximately 65–70% for one-step (10 s) ahead prediction. Early-warning behavior is intentionally conservative, prioritizing false alarm suppression over aggressive alerting. Per-signal evaluation reveals high sensitivity for blood pressure signals, whereas glucose and certain high-variability modalities exhibit conservative sensitivity under modality-specific thresholds. Importantly, the aggregated multi-modal risk decision achieves strong overall system-level performance, with sensitivity and specificity of 0.89 and 0.92, respectively. Overall, the proposed framework establishes a robust, low-latency, and computationally efficient foundation for dependable physiological monitoring in WBAN environments, leveraging selective processing to optimize both resource utilization and clinical reliability. Full article

Although natural enzymes have a high catalytic activity as biocatalysts, they still face many limitations in practical applications, including high preparation and purification costs, poor environmental stability, and difficulties in recovery and reuse. Nanozymes are a class of synthetic nanomaterials with enzymatic catalytic properties. They are regarded as promising alternatives to natural enzymes due to their low cost, good stability, adjustable catalytic activity, and easy surface modification. Among many nanozyme materials, metal–organic frameworks (MOFs) and covalent organic frameworks (COFs) have attracted much attention due to their high specific surface area, adjustable porosity, and stable framework structure. This review summarizes the latest research progress of nanozymes based on MOFs and COFs and reveals the catalytic properties of different enzymes (oxidase, peroxidase, catalase, glucose oxidase, superoxide dismutase, hydrolase) simulated by them. In addition, their potential applications in sensors and medical fields are discussed. Finally, this review discusses the current challenges and developments of organic framework-based nanozymes and provides suggestions for future research directions. Full article

Background/Objectives: Effective glycemic management from the time of diagnosis is essential in the care of children and adolescents with type 1 diabetes (T1D), as early glycemic patterns can influence long-term health outcomes. Methods: This exploratory study evaluated a one-month interactive, group- and play-based education program designed to enhance food and carbohydrate counting skills among families of children and adolescents with newly diagnosed (ND) T1D (<1 year since diagnosis) or suboptimal glycemic control (SGC) (hemoglobin A1c (HbA1c) > 7.5% (58 mmol/mol)). The intervention included hands-on learning activities in food and carbohydrate counting, and peer interaction to support development of diabetes self-management skills. Data were collected at baseline, post-intervention, and at six-months follow-up through medical records, glucose sensor data, and a questionnaire assessing diabetes self-management skills, dietary practices, and carbohydrate counting. Results: Between September 2022 and April 2024, 55 children and adolescents were enrolled in the ND group and 22 in the SGC group. Post-intervention, carbohydrate counting skills improved, particularly in the ND group. Participants reported greater confidence and independence in carbohydrate counting and insulin dosing, with parents noting sustained benefits at six-months follow-up. No significant changes were observed in glycemic control, including time-in-range and postprandial glucose profiles. Conclusions: In this exploratory study, early interactive and play-based group education was associated with improvements in carbohydrate counting skills and self-care confidence in children and adolescents with newly diagnosed T1D. These improvements were not accompanied by changes in glycemic outcomes. The findings occurred during a complex and transitional phase following diagnosis. Further research is needed to examine sustainability and long-term clinical impact. Full article

Background: Streptococcus pneumonia is the primary etiological agent of community-acquired pneumonia (CAP). Pneumococci promote severe lung injury through the release of virulence factors, including pneumolysin (PLY). Obesity/diabetes increases pneumonia-associated mortality, but the mechanisms remain elusive. We found that obese db/db mice have increased pulmonary barrier disruption to PLY. Previously we showed that upregulation of NOX1 in endothelial cells (EC) of db/db mice drives endothelial dysfunction, but a role for NOX1 in PLY-induced lung injury, especially in diabetic conditions, has not yet been described. Results: Increased NOX1 in lung ECs dose-dependently increased superoxide and EC barrier disruption (p < 0.05). Even at low activity levels, NOX1 greatly potentiated PLY-induced EC barrier disruption, whereas loss of NOX1 activity, either pharmacological or genetic, reduced barrier disruption (p < 0.05). Blockade of calcium entry protected the EC barrier from combined PLY and NOX1, indicating a key role for calcium. Hyperglycemia amplified PLY-enduced EC barrier disruption and intracellular calcium and these effects were mitigated by NOX1 inhibition and silencing (p < 0.05). NOX1-enhanced calcium entry was reduced by knockout of calcium sensor STIM1, and PLY-induced barrier disruption was reduced by STIM1 inhibition. Levels of STIM1, Orai1, TRPV4, or TRPC4 were unchanged by HG, but TRPC1 significantly increased (p < 0.05). NOX1 and HG promoted increased STIM1 and TRPC1 binding, and silencing TRPC1 ameliorated PLY-induced barrier disruption (p < 0.05). Increased calcium promoted mitochondrial permeability transition pore (MPTP) opening and PPIF inhibition protected EC barrier function (p < 0.05). Conclusions: These results suggest that elevated glucose levels in obesity primes EC barrier disruption by amplifying PLY-induced calcium influx via a novel NOX1, STIM1, TRPC1 and MPTP signaling axis. Full article

Enzyme-free flexible glucose sensors hold great promise in the field of wearable health monitoring. However, their performance is limited by the balance between the catalytic interface activity and stability. This paper reports a strategy for interface gradient roughening of screen-printed carbon electrodes (SPCE) via controllable electrochemical exfoliation (EE). It systematically reveals the inherent relationships among the degree of EE treatment, electrode morphology, surface chemistry, and electrochemical performance. On this basis, the deposition of gold nanoparticles (AuNPs) with high density and uniform distribution is achieved, and a high-performance flexible enzyme-free glucose sensor is constructed. The study finds that EE treatment can significantly increase the true surface area of the electrode and introduce abundant oxygen-containing functional groups, thus effectively reducing the charge transfer resistance. Nevertheless, excessive exfoliation leads to the degradation of the conductive network, indicating the existence of a critical “performance window”. The EE-SPCE optimized with 150 cycles has both a high active area and good electrical conductivity, providing an ideal deposition substrate for AuNPs, increasing their distribution density by approximately 158% and reducing the average particle size to 125 nm. The fabricated AuNPs/EE-SPCE sensor exhibits excellent performance in glucose detection: it has a high sensitivity of 550.766 μA·mM⁻¹·cm⁻² in the range of 0.1–3 mM, a detection limit of 0.0998 mM, a wide linear range, excellent selectivity, long-term stability, and good mechanical flexibility. This research not only develops an efficient and scalable method for constructing flexible sensing interfaces but also clarifies the trade-off relationship among “roughening–conductivity–catalytic performance” at the mechanistic level, providing an important theoretical basis and a general strategy for rationally designing high-performance flexible electrochemical devices. Full article

Electrochemical biosensors are becoming increasingly prevalent across medical, food, and bioprocessing industries for monitoring complex biological processes. However, their sensitivity to contamination and exposure to potentially hazardous biological species often necessitates single-use disposal, contributing to the release of high-value, high-demand, and environmentally damaging materials into the environment. This study investigates the feasibility of a closed-loop recycling process for single-use glucose biosensors, with a focus on the recovery and reuse of noble metals silver and gold. Guided by ecodesign principles and using low-impact materials, we developed a silver screen ink, gold syringe ink, and a poly(lactic acid) (PLA) substrate. Sensors were fabricated by additive manufacturing and screen printing—enabling the scalability afforded by screen printing to produce the high-coverage silver layer while also minimising gold ink waste using additive manufacturing. A low-energy recovery method that exploited selective solvent compatibility was developed to reclaim silver and gold. Second-generation devices were then fabricated, demonstrating performance comparable to commercial equivalents while achieving an 80% reduction in material usage, cost, and environmental impact across 16 categories using a life cycle assessment (LCA). Full article

Diabetes continues to impose significant global health and economic burdens, driving the demand for robust, enzyme-free glucose sensors capable of reliable operation under physiological conditions. Here, we report the development of a high-performance nonenzymatic glucose sensor based on laser-induced graphene (LIG) modified with zinc oxide (ZnO) and platinum (Pt) nanostructures. ZnO was electrodeposited onto LIG with modulation potential and deposition duration systematically optimized. The ZnO/LIG electrodes were characterized electrochemically using potassium ferricyanide and evaluated for glucose oxidation in phosphate-buffered solution. Subsequent electrodeposition of Pt under analogous optimized conditions yielded a ternary Pt/ZnO/LIG architecture with enhanced electrocatalytic activity. Sensor performance was assessed by cyclic voltammetry and chronoamperometry, with hydrodynamic conditions optimized for maximal response. The Pt/ZnO/LIG sensor demonstrated a high sensitivity of 37.125 µA mM⁻¹ cm⁻², a wide linear dynamic range (0.5–10 mM; 12–28 mM), and a low detection limit of 77.78 µM. The electrode exhibited excellent reproducibility, long-term stability over 7 weeks, and strong selectivity against common interfering species. Robust performance was also confirmed through real sample testing, highlighting its applicability in physiologically relevant matrices. These findings highlight the Pt/ZnO/LIG platform as a promising candidate for next-generation enzyme-free glucose monitoring systems for clinical and point-of-care diabetes management. Full article

Impaired glucose metabolism, a known precursor to type 2 diabetes, is associated with dysregulation of the autonomic nervous system. To assess such autonomic states, consumer wearable devices provide continuous, non-invasive physiological monitoring and may capture autonomic signatures related to metabolic status. This exploratory study examined whether dynamic features of heart rate (HR) and heart rate variability (HRV) during sleep—derived from a consumer wrist-worn device (Fitbit)—are associated with glucose metabolism status in free-living adults. We analyzed 189 nights from 18 participants (7 participants in the higher-glycemic-risk group, estimated glycated hemoglobin (HbA1c) ≥ 5.5%; 11 participants in the lower-glycemic-risk group, estimated HbA1c < 5.5%). From 28 candidate HR/HRV variables, Elastic Net regression ($\alpha =0.5$) was applied to identify features associated with nocturnal mean glucose. Fourteen features retained non-zero coefficients; notably, dynamic features capturing overnight trends and variability patterns showed stronger associations than conventional static mean values. The nocturnal trends of within-window standard deviation and variance of $ln\left(\mathrm{RMSSD}\right)$ (root mean square of successive differences between consecutive RR intervals, estimated here from PPG-derived inter-beat intervals; RMSSD) emerged as prominent candidates, alongside HR variability indices. Independent between-group comparisons further confirmed that two dynamic HRV features differed significantly between the lower- and higher-glycemic-risk groups (both $\mathit{p}<0.05$; Cohen’s $\left|d\right|>1.1$). Specifically, the lower-glycemic-risk group exhibited decreasing overnight trends in HRV variability, consistent with progressive autonomic stabilization during sleep. In contrast, the higher-glycemic-risk group showed increasing variability trends, suggestive of persistent autonomic instability. These directional patterns are consistent with prior evidence linking autonomic dysfunction to impaired glucose metabolism. We characterize these findings as hypothesis-generating. The identified dynamic HR/HRV features represent physiologically plausible candidate correlates of glycemic status and warrant confirmatory investigation in larger, independent cohorts with laboratory-measured HbA1c. More broadly, this work highlights the potential of widely available, consumer-grade wearable devices to move beyond activity tracking and support continuous, real-world assessment of cardiometabolic health, thereby expanding their utility in everyday health monitoring and preventive medicine. Full article

Background: Salt-sensitive blood pressure (SSBP) represents a prevalent yet underrecognized hypertensive phenotype, in which blood pressure (BP) and volume status are disproportionately influenced by dietary sodium intake. Beyond BP elevation alone, salt sensitivity reflects a convergence of renal sodium handling abnormalities, neurohormonal activation, vascular dysfunction, and inflammatory pathways that link excessive sodium exposure to progressive kidney injury and adverse cardiac remodeling. Given its association with chronic kidney disease (CKD) and the association of heart failure with preserved ejection fraction (HFpEF), improved recognition of SSBP has direct clinical relevance. Objective: This narrative review aims to synthesize current mechanistic and clinical evidence on SSBP, focusing on pathophysiology, cardiorenal interactions, diagnostic challenges, and phenotype-guided therapeutic strategies with practical applicability. Methods: A narrative literature review was conducted using PubMed, Scopus, and Web of Science from inception through January 2026. Experimental, translational, and clinical studies, along with relevant guideline documents, were integrated to provide conceptual and clinical interpretation rather than quantitative analysis. Key Findings: Impaired renal sodium excretion, intrarenal RAAS activation, sympathetic overactivity, endothelial dysfunction, and immune-mediated inflammation contribute to sodium retention, microvascular dysfunction, and fibrotic remodeling across the kidney–heart axis. These pathways are strongly supported by experimental and translational data, but direct interventional clinical validation remains limited for several mechanisms. Clinically, salt-sensitive individuals often exhibit non-dipping BP patterns, albuminuria, salt-induced edema, and a predisposition to HFpEF. Dynamic BP monitoring combined with targeted laboratory assessment improves identification of this phenotype and supports individualized management. Conclusions: Early recognition of SSBP enables targeted interventions beyond uniform sodium restriction. Phenotype-guided strategies integrating lifestyle modification, RAAS blockade, thiazide-like diuretics, mineralocorticoid receptor antagonists, and sodium-glucose co-transporters 2 inhibitors (SGLT2i) may improve cardiorenal outcomes. Emerging precision tools (e.g., wearable blood-pressure sensors, digital sodium tracking technologies, etc.) remain exploratory but may further refine individualized management. Full article