Monitoring Of Glucose Levels Research Articles

RSSDI Expert Consensus for Optimal Glucose Monitoring in Diabetes Mellitus in India and Recommendations for Clinical Practice

Effective management of diabetes warrants accurate and regular monitoring of glucose levels to prevent serious diabetes-associated complications and long-term health consequences. Hence, achieving target glucose levels and maintaining adequate glycemic control is essential in diabetes to prevent episodes of hypoglycemia. Multiple glucose monitoring tools have been developed over time, each with differing degrees of precision, convenience, and real-time input. The management of diabetes has been considerably improved by using these various glucose monitoring devices, both in terms of treatment outcomes and patient quality of life. However, in India, the lack of awareness, patient education, availability, and affordability of glucose monitoring devices poses a significant concern resulting in poor adherence to glucose monitoring and low medication adherence thereby increasing disease burden. Consequently, there is an urgent need for healthcare professionals and policymakers in India to collaborate and address the challenges associated with glucose monitoring in patients with diabetes, while also providing recommendations to overcome these concerns. This recommendation article offers a comprehensive evaluation of various glucose monitoring tools available for use by patients suffering from different types of diabetes, explores the challenges associated with glucose monitoring in India, and also presents expert panel recommendations to enhance diabetes management effectively.

Metabolic and Endocrine Correlates of Subclinical Hypothyroidism in Young Adults with First-Episode and Drug-Naive Major Depressive Disorder

BackgroundMajor Depressive Disorder (MDD) is often associated with Subclinical Hypothyroidism (SCH), but the clinical and biochemical characteristics in young, first-episode, drug-naive patients remain unclear. This study aims to examine the prevalence and clinical correlates of SCH in this population to enhance screening and management strategies. MethodA cross-sectional study included 917 young Chinese patients (aged 18-35) diagnosed with first-episode, drug-naive MDD. Comprehensive clinical assessments were conducted, involving demographic data, psychiatric evaluations using the Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Rating Scale (HAMA), and Positive and Negative Syndrome Scale (PANSS), alongside biochemical measurements such as thyroid stimulating hormone, thyroid peroxidase antibodies (TPOAb), fasting blood glucose (FBG), total cholesterol (TC), high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), systolic blood pressure (SBP), and diastolic blood pressure (DBP). Binary logistic regression identified clinical correlates of SCH. ResultsThe prevalence of SCH among the study population was 58%. Logistic regression analysis identified significant predictors of SCH, including higher HAMD scores (OR = 1.26), TPOAb (OR = 1.003), FBG (OR = 2.28), TC (OR = 1.66), SBP (OR = 1.11), and DBP (OR = 1.07). In contrast, lower HDLC levels (OR = 0.28) were inversely associated with SCH. ConclusionThe high prevalence of SCH in young, first-episode, drug-naive MDD patients emphasizes the need for comprehensive metabolic and endocrine evaluations. Regular monitoring of thyroid function, glucose levels, blood pressure, and lipid profiles is crucial for early detection and intervention, potentially improving clinical outcomes in this vulnerable group.

Exploration of micro-miniature venturi pump for continuous glucose monitoring through interstitial fluid (ISF) extraction

Interstitial Fluid (ISF) is a naturally occurring body fluid that surrounds cells and tissues and contains certain markers useful for continuously monitoring glucose levels in the blood without constantly extracting it. Miniaturizing can reduce its cost and timescale. In this study, for continuous glucose monitoring the numerical analysis of a Polymethyl methacrylate (PMMA) based Micro-miniature venturi pump was carried out to extract Interstitial Fluid (ISF). The numerical study was carried out using COMSOL Multiphysics software by employing the k-ε turbulence model to obtain output as a vacuum at the throat of the pump. The micro-miniature venturi pump was numerically analyzed for several key parameters, including the dimensions of the throat, the convergent angle, and the divergent angle. This study obtained a minimum pressure of 49.41 kPa numerically and 70 kPa experimentally when an input pressure of 252 kPa of compressed air was given to the system. Further influence of turbulence kinetic energy and turbulence dissipation rate on throat pressure output have been notified. Notably, the pressure output reaches its minimum value of 49.41 kPa when the turbulent kinetic energy and the turbulent dissipation rate reach maximum values of 5.0 × 109 m2/s3 and 7000 m2/s2 respectively. As per the previous research findings, for continuous glucose monitoring through ISF extraction, a pressure level of 95 kPa is deemed adequate hence the designed micro-miniature venturi pump is suitable for this application.

Coral-like Ti3C2Tx/PANI Binary Nanocomposite Wearable Enzyme Electrochemical Biosensor for Continuous Monitoring of Human Sweat Glucose

With the continuous advancement of contemporary medical technology, an increasing number of individuals are inclined towards self-monitoring their physiological health information, specifically focusing on monitoring blood glucose levels. However, as an emerging flexible sensing technique, continuous and non-invasive monitoring of glucose in sweat offers a promising alternative to conventional invasive blood tests for measuring blood glucose levels, reducing the risk of infection associated with blood testing. In this study, we fabricated a flexible and wearable electrochemical enzyme sensor based on a two-dimensional Ti3C2Tx MXene nanosheets and coral-like polyaniline (PANI) binary nanocomposite (denoted as Ti3C2Tx/PANI) for continuous, non-invasive, real-time monitoring of sweat glucose. The exceptional conductivity of Ti3C2Tx MXene nanosheets, in conjunction with the mutual doping effect facilitated by coral-like PANI, significantly enhances electrical conductivity and specific surface areas of Ti3C2Tx/PANI. Consequently, the fabricated sensor exhibits remarkable sensitivity (25.16 μA·mM−1·cm−2), a low detection limit of glucose (26 μM), and an extensive detection range (0.05 mM ~ 1.0 mM) in sweat. Due to the dense coral-like structure of Ti3C2Tx/PANI binary nanocomposite, a larger effective area is obtained to offer more active sites for enzyme immobilization and enhancing enzymatic catalytic activity. Moreover, the sensor demonstrates exceptional mechanical performance, enabling a 60° bend in practical applications, thus satisfying the rigorous demands of human sweat detection applications. The results obtained from continuous 60 min in vitro monitoring of sweat glucose levels demonstrate a robust correlation with the data of blood glucose levels collected by a commercial glucose meter. Furthermore, the fabricated Ti3C2Tx/PANI/GOx sensor demonstrated agreement with HPLC findings regarding the actual concentration of added glucose. This study presents an efficient and practical approach for the development of a highly reliable MXene glucose biosensor, enabling stable and long-term monitoring of glucose levels in human sweat.

Enhanced Diabetes Detection and Blood Glucose Prediction Using TinyML-Integrated E-Nose and Breath Analysis: A Novel Approach Combining Synthetic and Real-World Data

Diabetes mellitus, a chronic condition affecting millions worldwide, necessitates continuous monitoring of blood glucose level (BGL). The increasing prevalence of diabetes has driven the development of non-invasive methods, such as electronic noses (e-noses), for analyzing exhaled breath and detecting biomarkers in volatile organic compounds (VOCs). Effective machine learning models require extensive patient data to ensure accurate BGL predictions, but previous studies have been limited by small sample sizes. This study addresses this limitation by employing conditional generative adversarial networks (CTGAN) to generate synthetic data from real-world tests involving 29 healthy and 29 diabetic participants, resulting in over 14,000 new synthetic samples. These data were used to validate machine learning models for diabetes detection and BGL prediction, integrated into a Tiny Machine Learning (TinyML) e-nose system for real-time analysis. The proposed models achieved an 86% accuracy in BGL identification using LightGBM (Light Gradient Boosting Machine) and a 94.14% accuracy in diabetes detection using Random Forest. These results demonstrate the efficacy of enhancing machine learning models with both real and synthetic data, particularly in non-invasive systems integrating e-noses with TinyML. This study signifies a major advancement in non-invasive diabetes monitoring, underscoring the transformative potential of TinyML-powered e-nose systems in healthcare applications.

Metabolic management of a successful pregnancy and postpartum complications in fructose‐1,6‐bisphosphatase deficiency

AbstractFructose‐1,6‐bisphosphatase (FBPase) deficiency is a rare, inborn error of metabolism, that causes hypoglycemia and lactic acidosis in response to inadequate glucose intake and/or high intakes of fructose, sucrose, or sorbitol. Pregnancy in women with FBPase deficiency puts them at high risk for metabolic decompensation due to increased glucose demands from the growing fetus. Here we report a 31‐year‐old primipara who was treated starting at 14 weeks gestation with a diet high in complex carbohydrates and low in fructose, sucrose, and sorbitol and close monitoring of glucose levels throughout her pregnancy. She delivered a healthy 2860 g baby at 37 weeks via vaginal delivery with no complications or hypoglycemia. At 5 months postpartum and 5 months of life, the patient and baby are doing well, although the patient experienced an episode of hypoglycemia and lactic acidosis at 4 months postpartum due to the increased metabolic demands of breastfeeding. This report adds to the limited case reports that discuss outcomes and proposed interventions during pregnancy in individuals with FBPase deficiency.

Smart photonic crystal hydrogels for visual glucose monitoring in diabetic wound healing

Diabetes is a global chronic disease that seriously endangers human health and characterized by abnormally high blood glucose levels in the body. Diabetic wounds are common complications which associate with impaired healing process. Biomarkers monitoring of diabetic wounds is of great importance in the diabetes management. However, actual monitoring of biomarkers still largely relies on the complex process and additional sophisticated analytical instruments. In this work, we prepared hydrogels composed of different modules, which were designed to monitor different physiological indicators in diabetic wounds, including glucose levels, pH, and temperature. Glucose monitoring was achieved based on the combination of photonic crystal (PC) structure and glucose-responsive hydrogels. The obtained photonic crystal hydrogels (PCHs) allowed visual monitoring of glucose levels in physiological ranges by readout of intuitive structural color changes of PCHs during glucose-induced swelling and shrinkage. Interestingly, the glucose response of double network PCHs was completed in 15 min, which was twice as fast as single network PCHs, due to the higher volume fraction of glucose-responsive motifs. Moreover, pH sensing was achieved by incorporation of acid-base indicator dyes into hydrogels; and temperature monitoring was obtained by integration of thermochromic powders in hydrogels. These hydrogel modules effectively monitored the physiological levels and dynamic changes of three physiological biomarkers, both in vitro and in vivo during diabetic wound healing process. The multifunctional hydrogels with visual monitoring of biomarkers have great potential in wound-related monitoring and treatment.Graphical abstract

Multilayer patch functionalized microfibrillated cellulosic paper sensor for sweat glucose monitoring.

Electrochemical analysis of glucose monitoring without painful blood collection provides a new noninvasive route for monitoring glucose levels. Thus, in this study, biobased cellulosic papers (methylated and phosphorylated one) based glucose monitoring sensor is developed. To achieve high hydrophilicity, microfibrillated cellulose (MFC) were functionalized using hexokinase mediated phosphorylation (-OH to -[Formula: see text]). The instinctive increased surface charge density from 36.2 ± 3.4 to 118.4 ± 1.2 µmol/g and decrease contact angle (45°-22°) confirms the increased hydrophilicity of paper. Furthermore, functionalized phos-MFC paper increase the capillary flow of sweat, required low quantity (1µl) of sweat for accurate analysis of glucose level. Additionally, chemically induced methyl groups (-CH3) make the sensor more barrier to other chemicals. In addition, a multilayer patch design combined with sensor miniaturization was used to lead to an increase in the efficiency of the sweat collection and sensing processes. Besides, this paper sensor integrated with artificial transdermal drug delivery unit (agarose gel as skin) for monitoring glucose levels in sweat. The patch monitoring system increase the accuracy of sensing with fluctuation in sweat vol. (1-4µl), temperature (20-70 °C), and pH (4.0-7.0). In addition, temperature dependency artificial transdermal delivery (within agarose gel) of drug metformin agrees the measurement accuracy of sensor, called "switch system" without any error. As a result, the reported MFC paper based multi-patch disposable sensing system provides a novel closed-loop solution for the noninvasive sweat-based management of diabetes mellitus.

Feeding and Eating Disorders in Young People with Type 1 Diabetes: A Systematic Review

Eating disorders (ED) are a growing concern among young individuals with type 1 diabetes (T1D), with a prevalence significantly higher than that observed in the general adolescent population. Studies indicate that adolescents with diabetes are 2 to 3 times more likely to develop ED compared to their non-diabetic peers. This increased prevalence is partly attributed to several risk factors unique to this population. Adolescence itself is a major risk factor for ED, characterized by hormonal fluctuations, rising concerns about body image, and experimental eating behaviors. However, for young people with T1D, these risks are exacerbated by additional challenges. Daily diabetes management, which involves rigorous monitoring of blood glucose levels and precise control of dietary intake, can contribute to increased stress and excessive preoccupation with weight and body shape. Furthermore, social expectations and pressures related to glycemic control can reinforce problematic eating behaviors. ED in young diabetics can have severe consequences on diabetes management and overall health. Restrictive eating or purging behaviors can lead to glycemic imbalances, poor diabetes control, and increased risk of associated complications. This can also worsen psychological difficulties, such as anxiety and depression, thereby amplifying the cycle of deteriorating mental and physical health. Effective management of ED in young diabetics requires a multidisciplinary approach. It is crucial to integrate interventions that address not only nutritional and psychological aspects but also the specific challenges related to managing T1D. Early detection and treatment of ED can improve clinical outcomes and promote a better balance between diabetes management and the mental health of patients.

A small-period long-period fiber grating biosensor based on immobilization of concanavalin A on polydopamine nanospheres for simultaneous detection of D-glucose and temperature

The accurate and sensitive monitoring of glucose levels plays a crucial role in diagnosing diabetes in clinical settings. In this work, a novel small-period long-period fiber grating (SP-LPG) biosensor was first developed for D-glucose detection based on the immobilization of concanavalin A (Con A) on polydopamine (PDA) nanospheres. SP-LPG was fabricated by using femtosecond laser direct writing technology and the obtained grating region was only 2.4 mm. The recognition element of D-glucose, Con A, was attached to the surface of PDA nanospheres. Due to the high specific surface area of PDA nanospheres, a large number of binding sites were available for Con A. The as-prepared sensor showed selective and sensitive to D-glucose measurement in the range of 10 nM to 10 mM and a low detection limit of 1.95 nM (S/N = 3) was achieved. Moreover, the small grating period of SP-LPG allows for the observation of Bragg reflection, which can be utilized for temperature sensing. This property eliminates the issue of temperature cross-sensitivity present in refractive index sensing. And the sensor exhibited a thermal sensitivity of 10 pm/°C within the range of 30 ∼ 100 °C. The developed sensor offers a convenient and efficient platform of simultaneously measuring multiple parameters, including target molecules and temperature, for real-time medical monitoring applications.

Study on the performance of MoS2/Au composites for non-enzymatic electrochemical glucose detection

Abstract Glucose concentration is considered an indicator for the diagnosis of diabetes, highlighting the importance of accurate glucose detection. Non-enzymatic electrochemical sensors have been extensively studied for glucose detection applications, with nanocomposites composed of molybdenum disulfide (MoS2) and gold nanoparticles (Au NPs) demonstrating high catalytic activity. In this study, a nanocomposite material composed of MoS2 and Au NPs (MoS2/Au) was synthesized and employed to construct a non-enzymatic electrochemical glucose biosensor. The detection limit of this sensor was explored, reaching as low as 1 mM. Additionally, compared to MoS2, the MoS2/Au nanocomposite exhibited a higher linear correlation coefficient and sensitivity, with a linear range of 1–25 mM and a sensitivity of 417.556 μA mM−1 cm−2. The sensor demonstrated excellent performance within the range of human blood glucose concentrations, showing potential for real-time monitoring and precise measurement of glucose levels. Furthermore, it exhibited good stability and reproducibility. These findings indicate the potential applications of MoS2/Au in biosensors and immunoassays.

Sensitivity and accuracy of single-mode fiber optic sensor for non-invasive glucose measurement

Abstract Routine glucose level monitoring is essential for diabetic patients. Standard measurement methods based on finger pricking are inconvenient and susceptible to infection risk. Therefore, simple and non-invasive measurements are urgently needed. Compared to other approaches, glucose level measurement using optical methods offers many advantages, such as set-up simplicity, high sensitivity, and high accuracy. We optimize the sensing performance of glucose level sensors based on a single-mode fiber optic. The fiber optic serves as a medium for light propagation from a diode laser to a photodiode and, at the same time, serves as an active sensing medium. In the sensing area, the fiber optic cladding is partly (i.e., 1 – 5 cm) stripped to allow direct contact, which leads to evanescent wave absorption by glucose molecules. The length of fiber optic stripping and bending radius, which determine the sensitivity and accuracy of the sensor, varied. Bent fiber optic sensors consistently show a higher sensitivity and accuracy than straight ones. Maximum sensitivity of 2.35 mV/(mg/dL) was attained for a 3 cm stripping length and 4.5 cm bending radius. The lowest sensitivity of the sensor, 0.453 mV/(mg/dL), was acquired at the stripping length of 5 cm for the straight fiber optic sensor. The highest accuracy of the developed sensor is 99% for bent fiber optic sensors.

New therapeutic approaches in corticosteroid-induced diabetes mellitus in children

Corticosteroid-induced diabetes is a significant complication in pediatric patients receiving steroid therapy for various medical conditions. This article reviews the pathophysiology, diagnosis, and management of corticosteroid-induced diabetes in children. Key therapeutic strategies include lifestyle modifications, pharmacologic interventions, and careful monitoring of blood glucose levels. Emphasis is placed on individualized treatment plans tailored to the child's specific needs and underlying condition. The article also discusses the importance of interdisciplinary collaboration among healthcare providers to optimize outcomes and minimize long-term complications. Early recognition and proactive management are critical in improving the quality of life for affected children.

Exploring the Feasibility of Digital Voice Assistants for Delivery of a Home-Based Exercise Intervention in Older Adults With Obesity and Type 2 Diabetes Mellitus: Randomized Controlled Trial.

Current clinical guidelines for the management of type 2 diabetes mellitus (T2DM) in older adults recommend the use of antihyperglycemic medications, monitoring of blood glucose levels, regular exercise, and a healthy diet to improve glycemic control and reduce associated comorbidities. However, adherence to traditional exercise programs is poor (<35%). Common barriers to adherence include fear of hypoglycemia and the need for blood glucose level monitoring before exercise. Digital health strategies offer great promise for managing T2DM as they facilitate patient-practitioner communication, support self-management, and improve access to health care services for underserved populations. We have developed a novel web-based software program allowing practitioners to create tailored interventions and deliver them to patients via digital voice assistants (DVAs) in their own homes. We aim to evaluate the feasibility of a 12-week, home-based, personalized lifestyle intervention delivered and monitored by DVAs for older adults with obesity and T2DM. In total, 50 older adults with obesity aged 50-75 years with oral hypoglycemic agent-treated T2DM were randomized to the intervention (DVA, n=25) or a control group (n=25). Participants allocated to the DVA group were prescribed a home-based muscle strengthening exercise program (~20- to 30-min sessions) and healthy eating intervention, delivered via DVAs (Alexa Echo Show 8; Amazon) using newly developed software ("Buddy Link"; Great Australian Pty Ltd). Control group participants received generalized physical activity information via email. Outcomes were feasibility, DVA usability (System Usability Scale), and objectively assessed physical activity and sedentary time (wrist-worn accelerometers). In total, 45 (90%) out of 50 participants completed this study. Mean adherence to prescribed exercise was 85% (SD 43%) with no intervention-related adverse events. System usability was rated above average (70.4, SD 16.9 out of 100). Compared with controls, the DVA group significantly decreased sedentary time (mean difference -67, SD 23; 95% CI -113 to -21 min/d), which was represented by a medium to large effect size (d=-0.6). A home-based lifestyle intervention delivered and monitored by health professionals using DVAs was feasible for reducing sedentary behavior and increasing moderate-intensity activity in older adults with obesity and T2DM. Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12621000307808; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=381364&isReview=true.

Development of a 3D Hydrogel SERS Chip for Noninvasive, Real-Time pH and Glucose Monitoring in Sweat.

Traditional diagnostic methods, such as blood tests, are invasive and time-consuming, while sweat biomarkers offer a rapid physiological assessment. Surface-enhanced Raman spectroscopy (SERS) has garnered significant attention in sweat analysis because of its high sensitivity, label-free nature, and nondestructive properties. However, challenges related to substrate reproducibility and interference from the biological matrix persist with SERS. This study developed a novel ratio-based 3D hydrogel SERS chip, providing a noninvasive solution for real-time monitoring of pH and glucose levels in sweat. Encapsulating the probe molecule (4-MBN) in nanoscale gaps to form gold nanoflower-like nanotags with internal standards and integrating them into an agarose hydrogel to create a 3D flexible SERS substrate significantly enhances the reproducibility and stability of sweat analysis. Gap-Au nanopetals modified with probe molecules are uniformly dispersed throughout the porous hydrogel structure, facilitating the effective detection of the pH and glucose in sweat. The 3D hydrogel SERS chip demonstrates a strong linear relationship in pH and glucose detection, with a pH response range of 5.5-8.0 and a glucose detection range of 0.01-5 mM, with R2 values of 0.9973 and 0.9923, respectively. In actual sweat samples, the maximum error in pH detection accuracy is only 1.13%, with a lower glucose detection limit of 0.25 mM. This study suggests that the ratio-based 3D hydrogel SERS chip provides convenient, reliable, and rapid detection capabilities with substantial application potential for analyzing body fluid pH and glucose.

Layer-by-layer Fabrication of Gold Nanoparticles/Polyaniline Modified Gold Electrodes for Direct Non-enzymatic Oxidation of Glucose

Background: Non-enzymatic direct glucose biofuel cell is a promising technology to harness sustainable renewable energy. Furthermore, monitoring glucose levels is essential for human lives with age. Thus, there is an increasing need to develop highly efficient and stable modified electrodes. Methods: This study reported the manufacture of gold nanoparticles/polyaniline/modified gold electrodes (Au NPs/PANI/Au electrode) based on the electrochemical polymerization method followed by the deposition of gold nanoparticles. The shapes and chemical constitution of the electrodes were examined by using different techniques including SEM, FTIR, XRD, EDS, and Raman spectroscopy techniques. The electrocatalytic efficiency of the present electrodes toward direct glucose oxidation was evaluated by applying cyclic voltammetry, linear sweep voltammetry, and square wave voltammetry techniques. Results: The results exhibited high electrocatalytic performance for direct glucose electrooxidation in alkaline media. The modified electrodes show the ability to electrooxidation of various glucose concentrations (1 μM ̶ 100 μM) with a limit of detection and limit of quantitation of 140 nM and 424 nM, respectively. Furthermore, the Au NPs/PANI/Au electrode showed higher durability, sensitivity, and selectivity toward glucose oxidation than the Au NPs/ Au electrode, which confirmed the role of the PANI layer in enhancing the stability of the modified electrode. Conclusion: Moreover, the molar fraction of glucose to KOH has a crucial role in the output current. Hence, the modified electrodes are great candidates for direct glucose biofuel cell application.

Near-infrared spectroscopy for glucose detection in aqueous solution

This work presents a near-infrared spectroscopy-based technique to measure the glucose concentration in an aqueous solution. A near-infrared light source sends optical energy through a glucose-water solution. The energy transmitted through the aqueous solution is received by a photodetector and a conditioning circuit that includes an operational amplifier and a low-pass filter to remove high-frequency noise. The received light intensity converted to DC voltage is found to be inversely proportional to the glucose concentration in the aqueous solution. The experimental results for glucose concentration in the range of 0–4000 mg/dL confirm the expected theoretical behavior. The sensitivity of the system is 26.25 μV/mgdL-1. The proposed glucose detection system is a promising tool for monitoring glucose levels in various industries, including food and beverage quality and healthcare.

Optimizing Physical Activity for Glycemic Control in Type 1 Diabetes: Strategies and Risks

Type 1 diabetes mellitus (T1DM) is a chronic autoimmune condition characterized by the destruction of insulin-producing beta cells in the pancreas, necessitating lifelong insulin therapy. This study explores the impact of physical activity on glycemic control and overall health in individuals with T1DM. Despite its proven benefits, including improved cardiovascular health, lower HbA1c levels, and reduced insulin requirements, over 60% of T1DM patients do not engage in regular exercise. Different types of physical activities—such as aerobic, anaerobic, and high-intensity interval training (HIIT)—affect metabolic responses differently. Aerobic exercises and HIIT have shown significant improvements in health-related quality of life (HRQoL) and reduced incidence of severe complications, such as diabetic ketoacidosis. However, exercise-induced hypoglycemia remains a significant risk, especially if exercise follows recent severe hypoglycemic episodes. Proper management strategies include adjusting insulin doses, monitoring glucose levels, and carbohydrate intake. The study highlights the importance of tailored exercise plans and preventive measures to mitigate risks such as nocturnal hypoglycemia and elevated ketones. Ultimately, effective integration of physical activity into diabetes management can lead to enhanced overall health and quality of life for individuals with T1DM.

Glucose Oxidase Coupling with Pistol-Like DNAzyme Based Colorimetric Assay for Sensitive Glucose Detection in Tears and Saliva.

Non-invasive monitoring of glucose levels in tears and saliva is crucial for diagnosing and predicting various illnesses, such as diabetic nephropathy. However, the capability of the current glucose detection methods to identify small amounts of glucose with a high sensitivity remains a significant obstacle. This study proposes a simple, visual technique for sensitively detecting glucose levels from tears and saliva using glucose oxidase (GOx) to catalyze glucose and pistol-like DNAzyme (PLDz) to enhance the signal. In particular, the β-D-glucose present in the samples serves as the initial molecule that GOx identifies and catalyzes to generate gluconic acid and hydrogen peroxide (H2O2). The H2O2 induces the self-cleavage of PLDz, activating the "part b" sequence. This activation initiates catalytic hairpin assembly (CHA) and releases the DNAzyme section in the H1 probe. The DNAzyme acts as a peroxidase analog, facilitating the catalysis of the 3,3',5,5'-tetramethylbenzidine (TMB)-hydrogen peroxide (H2O2) system and resulting in color changes. The proposed method exhibits a broad detection range of six orders of magnitude and a low limit of 0.32μM for glucose detection. Furthermore, the proposed method was highly effective in detecting glucose in saliva and tears, suggesting that it could potentially diagnose hyperglycemia-related disorders in clinical environments.

Comparison of Glucose and Immunoglobulin a Levels in Serum and Saliva of Patients with Type 1 and Type 2 Diabetes

Introduction: The monitoring and management of blood glucose levels are of significant importance in individuals diagnosed with diabetes mellitus. Accordingly, the objective of this study was to examine the potential of a non-invasive approach for the diagnosis and management of diabetes, through the measurement of glucose concentration and salivary IgA, and a comparison with fasting glucose and serum IgA levels in individuals with type 1 and 2 diabetes, in relation to a control group of healthy individuals. Methods: This case-control study was conducted on 76 individuals with diabetes (31 with type 1 diabetes and 45 with type 2 diabetes) and 24 healthy individuals. After obtaining the code of ethics and informed consent, serum and salivary IgA levels as well as fasting glucose, were measured for each participant. The data were analyzed using SPSS version 16 statistical software and the Spearman, Kruskal-Wallis, and Mann-Whitney tests. Results: The results showed a significant difference among the three groups (type 1 diabetes, type 2 diabetes, and healthy group) based on Fasting Blood Glucose, Hemoglobin A1c, Immunoglobulin A, salivary sugar, and salivary IgA (p&lt;0.001). Additionally, in the case group, parameters such as FBS, HbA1c, and salivary IgA showed a significant correlation with salivary sugar. Conversely, in the control group, only the salivary sugar level demonstrated a significant relationship with serum glucose level. The study's findings indicated that serum and salivary IgA levels were lower and higher, respectively, in the control subjects compared to the diabetic group (p&lt;0.001). Conclusion: In healthy individuals, salivary sugar can serve as an indicator to determine fasting blood sugar levels. In diabetic patients, salivary sugar can predict of FBS, HbA1c, and salivary IgA levels.