Search Results (629)

More than 14% of the world’s population suffered from diabetes mellitus in 2022. This metabolic condition is defined by increased blood glucose concentrations. Among the different types of diabetes, type 1 diabetes, caused by a lack of insulin secretion, is particularly challenging to treat. In this regard, automatic glucose level estimation implements Continuous Glucose Monitoring (CGM) devices, showing positive therapeutic outcomes. AI-based glucose prediction has commonly followed a deterministic approach, usually with a lack of interpretability. Therefore, these AI-based methods do not provide enough information in critical decision-making scenarios, like in the medical field. This work intends to provide accurate, interpretable, and personalized glucose prediction using the Temporal Fusion Transformer (TFT), and also includes an uncertainty estimation. The TFT was trained using two databases, an in-house-collected dataset and the OhioT1DM dataset, commonly used for glucose forecasting benchmarking. For both datasets, the set of input features to train the model was varied to assess their impact on model interpretability and prediction performance. Models were evaluated using common prediction metrics, diabetes-specific metrics, uncertainty estimation, and interpretability of the model, including feature importance and attention. The obtained results showed that TFT outperforms existing methods in terms of RMSE by at least 13% for both datasets. Full article

Mid-infrared passive spectroscopic imaging is a novel non-invasive and remote sensing method based on Planck’s law. It enables the acquisition of component-specific information from the human body by measuring naturally emitted thermal radiation in the mid-infrared region. Unlike active methods that require an external light source, our passive approach harnesses the body’s own emission, thereby enabling safe, long-term monitoring. In this study, we successfully demonstrated the simultaneous, non-invasive measurements of blood glucose and lactate levels of the human body using this method. The measurements, conducted over approximately 80 min, provided emittance data derived from mid-infrared passive spectroscopy that showed a temporal correlation with values obtained using conventional blood collection sensors. Furthermore, to evaluate localized metabolic changes, we performed k-means clustering analysis of the spectral data obtained from the upper arm. This enabled visualization of time-dependent lactate responses with spatial resolution. These results demonstrate the feasibility of multi-component monitoring without physical contact or biological sampling. The proposed technique holds promise for translation to medical diagnostics, continuous health monitoring, and sports medicine, in addition to facilitating the development of next-generation healthcare technologies. Full article

Internationally, the prevalence of type 2 diabetes mellitus (T2DM) and obesity rates are increasing significantly. As these epidemics continue to spread, the continuation of further research is paramount given that chronic diseases, such as T2DM, cause strain on both economies and healthcare systems. Recently, adipose tissue has been identified as an endocrine organ that produces many hormones that influence many bodily processes. Adipose tissue dysregulation (ATD)—when adipokines (adipose tissue hormones) are produced in abnormal amounts—plays an important role in T2DM development, progression, and prognosis. This narrative review focuses on mechanisms linking ATD with T2DM through adipokine actions (specifically, leptin and adiponectin) on insulin resistance and glucose metabolism. Here we show that the adipokines leptin and adiponectin are valuable in monitoring, diagnosing, and treating diseases. Further, their ratio (the leptin-to-adiponectin ratio, or LAR) may be more valuable than either adipokine individually. The LAR may give researchers the ability to utilize a primary prevention approach by utilizing LAR as a biomarker influencing early prognosis and treatment. Targeting ATD through diet, weight loss, physical activity, etc., may improve prevention and management outcomes for patients living with or at risk of T2DM. Full article

Diabetic foot ulcers (DFUs), which affect approximately 15% of individuals with diabetes mellitus (DM), result from complex molecular disturbances involving chronic hyperglycemia, immune dysfunction, and infection. At the molecular level, chronic hyperglycemia promotes the formation of advanced glycation end products (AGEs), activates the AGE-RAGE-NF-κB axis, increases oxidative stress, and impairs macrophage polarization from the pro-inflammatory M1 to the reparative M2 phenotype, collectively disrupting normal wound healing processes. The local wound environment is further worsened by antibiotic-resistant polymicrobial infections, which sustain inflammatory signaling and promote extracellular matrix degradation. The rising threat of antimicrobial resistance complicates infection management even further. Recent studies emphasize that optimal glycemic control using antihyperglycemic agents such as metformin, Glucagon-like Peptide 1 receptor agonists (GLP-1 receptor agonists), and Dipeptidyl Peptidase 4 enzyme inhibitors (DPP-4 inhibitors) improves overall metabolic balance. These agents also influence angiogenesis, inflammation, and tissue regeneration through pathways including AMP-activated protein kinase (AMPK), mechanistic target of rapamycin (mTOR), and vascular endothelial growth factor (VEGF) signaling. Evidence indicates that maintaining glycemic stability through continuous glucose monitoring (CGM) and adherence to antihyperglycemic treatment enhances antibiotic effectiveness by improving immune cell function and reducing bacterial virulence. This review consolidates current molecular evidence on the combined effects of glycemic and antibiotic therapies in DFUs. It advocates for an integrated approach that addresses both metabolic and microbial factors to restore wound homeostasis and minimize the risk of severe outcomes such as amputation. Full article

The increasing prevalence of diabetes mellitus necessitates the development of advanced glucose-monitoring systems that are non-invasive, reliable, and capable of real-time analysis. Wearable electrochemical biosensors have emerged as promising tools for continuous glucose monitoring (CGM), particularly through sweat-based platforms. This review highlights recent advancements in enzymatic and non-enzymatic wearable biosensors, with a specific focus on the pivotal role of nanomaterials in enhancing sensor performance. In enzymatic sensors, nanomaterials serve as high-surface-area supports for glucose oxidase (GOx) immobilization and facilitate direct electron transfer (DET), thereby improving sensitivity, selectivity, and miniaturization. Meanwhile, non-enzymatic sensors leverage metal and metal oxide nanostructures as catalytic sites to mimic enzymatic activity, offering improved stability and durability. Both categories benefit from the integration of carbon-based materials, metal nanoparticles, conductive polymers, and hybrid composites, enabling the development of flexible, skin-compatible biosensing systems with wireless communication capabilities. The review critically evaluates sensor performance parameters, including sensitivity, limit of detection, and linear range. Finally, current limitations and future perspectives are discussed. These include the development of multifunctional sensors, closed-loop therapeutic systems, and strategies for enhancing the stability and cost-efficiency of biosensors for broader clinical adoption. Full article

Background/Objectives: Postprandial hyperglycemia is a risk factor for diabetes and cardiovascular diseases, even in healthy individuals. Kanzaki mulberry leaf and water chestnut tea (MW tea), a blend of mulberry (Morus alba) leaves and water chestnut (Trapa japonica) leaves and husks, is rich in polyphenols and 1-deoxynojirimycin (DNJ) and may suppress postprandial glucose spikes, but evidence regarding its short-term daily intake is limited. This study aimed to evaluate the postprandial glycemic response and safety of two-week MW tea consumption using continuous glucose monitoring (CGM). Methods: We conducted a randomized, double-blind, placebo-controlled, two-period crossover trial involving 31 participants. Each intervention period lasted two weeks, separated by a one-week washout. Participants consumed either MW tea or a placebo before meals. Interstitial glucose levels were measured every 15 min using CGM. Postprandial glucose responses were recorded every 15 min for 180 min after a standardized meal on the first day of each period. The primary outcome was the coefficient of variation (CV) in glucose levels, calculated using data from the central 10 days of each intervention period. Safety was assessed using CGM-derived hypoglycemia metrics and blood test results. Results: The CV of glucose levels during the MW tea period was significantly lower than during the placebo period (mean difference: 0.02, p = 0.0006). A significant reduction in 1 h postprandial glucose area under the curve was also observed. No significant differences were found in hypoglycemia occurrence, liver/renal/inflammatory markers, or self-reported adverse symptoms. Notably, 1,5-anhydroglucitol (1,5-AG) levels significantly increased during MW tea intake, suggesting improved glycemic control. Conclusions: Short-term consumption of Kanzaki MW tea effectively suppressed postprandial glucose variability without safety concerns. These findings support MW tea as a promising natural supplement for glycemic management and the prevention of diabetes. Full article

Background: Advanced hybrid closed-loop (AHCL) systems have improved the glycemic control in type 1 diabetes (T1D). While time in range (TIR) (70–180 mg/dL) is the standard metric, time in tight range (TITR) (70–140 mg/dL) offers a stricter assessment. Real-world comparisons using the TITR are limited. This study compared the TIR and TITR metrics between the MiniMed™ 780G and Tandem Control-IQ™ in adults with T1D. Methods: This retrospective, single-center study included 42 propensity-score-matched adults with T1D (28 MM780G users and 14 Tandem Control-IQ users), each with ≥3 months of AHCL system use. Glycemic metrics from continuous glucose monitoring (CGM) were analyzed over a 14-day period. Comparisons between groups were conducted using Mann–Whitney U tests, adjusted linear regression, and linear mixed-effects models accounting for repeated measures. Results: At three months, the MM780G users achieved significantly higher TITR (60.1% ± 12 vs. 49.5% ± 9.3; p = 0.005) and TIR (83.7% ± 7.6 vs. 72.1% ± 7.5; p < 0.001) values, along with lower glucose variability, compared to these values in the Tandem Control-IQ users. The linear regression model confirmed that the MM780G was independently associated with a higher TITR (β = 14.2; p = 0.005). Mixed-effects modeling for the TIR showed a significant interaction between timepoint and device type (β = 4.81; p = 0.006), favoring the MM780G. Conclusions: In this real-world analysis, both AHCL systems improved glycemic control, but the MiniMed 780G could be associated with a superior performance in achieving tighter glucose targets without increasing hypoglycemia. TITR may serve as a valuable complementary metric alongside TIR in evaluating AHCL systems’ effectiveness. However, these findings should be interpreted cautiously due to limitations such as the retrospective design, small sample size, potential residual confounding, and lack of standardization in the device settings. Further studies are warranted to confirm these results and assess their generalizability. Full article

Background/Objectives: Continuous glucose monitoring (CGM) has transformed diabetes management, with time in range (TIR) emerging as a key glycemic metric. However, TIR lacks sensitivity to glycemic variability, leading to the introduction of time in tight range (TiTR), which defines a narrower range (70–140 mg/dL). This review synthesizes current evidence on TiTR’s clinical relevance and its potential to predict complications. Methods: A literature search was conducted, primarily using PubMed as the main database, to identify studies that specifically evaluate TiTR and its clinical implications, published until February 2025. Results: Preliminary data indicate that a 10% increase in TiTR is associated with a 23.8% reduction in microvascular complications. While TiTR aligns more closely with physiological glucose control, standardized targets remain undefined. Conclusions: This study provides clinicians with insights into optimizing glycemic control beyond traditional metrics. The correlation of TiTR with other glycemic markers and its association with diabetes-related complications suggest that TiTR can complement traditional measures to provide a more comprehensive assessment of glycemic status. From a clinical perspective, incorporating TiTR into routine practice may help personalize treatment strategies, improve risk stratification, and support more precise therapeutic decisions, particularly in patients using continuous glucose monitoring (CGM). Future research should refine TiTR thresholds and evaluate its integration into diabetes management, particularly in populations using advanced technologies. Full article

Endothelial dysfunction appears early in type 1 diabetes (T1D). The detection of the first vascular disturbances in T1D patients is crucial, and the introduction of novel techniques, such as flow-mediated skin fluorescence (FMSF) and adaptive optics retinal camera (Rtx) imaging, gives hope for better detection and prevention of angiopathies in the future. In this study, we aimed to investigate microcirculation disturbances in pediatric patients with T1D with the use of FMSF and Rtx imaging. This research focused especially on the relationship between microvascular parameters obtained in FMSF and Rtx measurements, and the glycemic control evaluated in continuous glucose monitoring (CGM) reports. We observed significantly increased wall thickness (WT) and wall-to-lumen ratio (WLR) values in T1D patients in comparison to the control group. Although we did not observe significant differences between the T1D and control groups in the FMSF results, a trend toward significance between the time in range (TIR) and hyperemic response (HR_max) and an interesting correlation between the carotid intima-media thickness (cIMT_max) and HR_max. were observed. In conclusion, FMSF and Rtx measurments are innovative techniques enabling the detection of early microvascular disturbances. Full article

Diabetes mellitus (DM) is one of the most common endocrine disorders in dogs. Glycated albumin (GA), a biomarker of short-term glycemia, may offer a valuable tool for assessing glycemic control in dogs with DM. This pilot study evaluated the correlation between GA and conventional glycemic markers and continuous glucose monitoring (CGM)-derived metrics in dogs. A total of 30 dogs were included in this prospective pilot study, comprising dogs with diabetes mellitus (n = 10) and healthy controls (n = 20). Of these, 11 dogs that lacked anemia, hypoalbuminemia, or azotemia and whose owners consented to 14-day CGM were analyzed for sensor-based metrics (dogs with diabetes, n = 7; controls, n = 4). Across the full cohort, GA showed significant correlations with fructosamine and HbA1c, while within the CGM subset, GA was significantly associated with mean glucose level, TIR2, and TAR2. These findings suggest that GA, in conjunction with fructosamine and HbA1c, offers valuable insights into glycemic control over a 2-week period and could serve as a reliable biomarker for glucose monitoring in dogs with diabetes. Full article

In the context of the relentless pursuit of precision, intelligence, and personalization within the realm of medical technology, the real-time monitoring of human physiological signals has assumed heightened significance. Implantable wireless sensor devices have exhibited extraordinary capabilities in tracking internal physiological parameters, including intraocular pressure, blood glucose levels, electrocardiographic activity, and arterial blood pressure. These devices are characterized by elevated temporal continuity and exceptional measurement accuracy. This paper undertakes an in-depth investigation into the key technologies underlying biodegradable implantable sensing devices. Initially, it expounds on diverse sensing mechanisms employed in implantable devices. Additionally, it presents common data transmission and power supply strategies for wireless sensing systems. Finally, it introduces biodegradable materials suitable for human implantation and their respective application domains and enumerates several implantable devices that are either under development or have already been commercialized. Through an in-depth and comprehensive discourse on the current state of development and extant challenges in this domain, the development trajectory of biodegradable devices is put forward. Moreover, this paper also serves as a valuable reference for the design and selection of implantable medical devices. Full article

Background: Metabolic bariatric surgery is a highly effective and long-lasting treatment for obesity and related chronic conditions. Women of reproductive age represent the largest group undergoing these procedures. Observational studies suggest an increased risk of preterm birth and impaired foetal growth in this population, though the underlying mechanisms remain unclear. A key hypothesis is that altered glucose metabolism, characterised by frequent hypoglycaemia and glycaemic fluctuations, may contribute to these adverse outcomes. While glycaemic variability following metabolic bariatric surgery has been documented, its pattern during pregnancy and impact on pregnancy outcomes are still underexplored. Methods: In this Belgian multicentre prospective cohort study, we will investigate glycaemic patterns during pregnancy in women who have undergone metabolic bariatric surgery. Women aged 18–45 years with a confirmed singleton pregnancy up to 11 weeks and 6 days and a history of Roux-en-Y gastric bypass or sleeve gastrectomy will be eligible for inclusion. Women with pregestational diabetes or those taking medication known to interfere with glucose metabolism will be excluded. All participants will receive blinded continuous glucose monitoring (Dexcom^® G6) for a 10-day period at four time points throughout the pregnancy. Foetal body composition and growth will be measured during routine ultrasound; skinfolds will be measured in the neonate. The primary outcome is the association between mean glycemia and glycaemic variability on continuous glucose monitoring and birth weight. The planned sample size is ninety-five women. Linear mixed models for repeated measurements will be used for analysis. Confounders such as smoking, micronutrient deficiency, and surgery-to-conception interval will be added to the model as covariates. In a second exploratory phase, each participant in the surgical group will be matched with a control participant—without a history of metabolic bariatric surgery—based on pre-pregnancy BMI and age. Control participants will undergo the same study procedures, allowing for exploratory comparison of glycaemic patterns and other study outcomes. Discussion: This prospective longitudinal study will be the largest study using continuous glucose monitoring to investigate glucose metabolism during pregnancy after metabolic bariatric surgery and its impact on foetal growth and newborn body composition. Trial registration: ClinicalTrials.gov: NCT05084339. Registration date: 15 October 2021. Full article

Background/Objectives: Effective diabetes self-management is critical for glycemic management and well-being, yet Latino youth face unique cultural and socioeconomic barriers that are insufficiently explored in the literature. This review mapped existing evidence on diabetes self-management for Latino youth. Methods: Searches were conducted in PubMed, CINAHL, SCOPUS, Web of Science, LILACS, ERIC, and The Cochrane Library, using the gray literature and reference lists, in September 2024, following JBI guidelines. The included studies were qualitative, quantitative, and mixed-methods studies and reviews on diabetes self-management for Latinos aged 0–30 with type 1 or 2 diabetes. Studies including participants over 30 or with gestational diabetes were excluded. Two reviewers independently extracted data using a standardized table and analyzed findings using the Association of Diabetes Care & Education Specialists framework (ADCES7) for self-care behaviors: healthy eating, being active, monitoring, taking medication, problem-solving, reducing risks, and healthy coping. Results: Forty-five studies (forty from the United States) were included from 860 citations. The findings highlighted challenges in adopting diabetes-friendly diets, including cultural preferences, food insecurity, and limited resources. Physical activity improved glycemic control but was hindered by family and school obligations. Continuous glucose monitoring (CGM) enhanced outcomes, though economic barriers limited access. Family-centered education improved medication adherence, while family support strengthened problem-solving. CGMs and insulin pumps reduced complications, and culturally adapted psychological support enhanced emotional well-being and glycemic management. Conclusions: This review underscores persistent disparities in diabetes self-management among Latino youth. While the study designs and settings were heterogeneous, the findings highlight the need for culturally tailored, family-centered interventions that address structural barriers and psychosocial needs to improve care. Full article

Background/Objectives: DEXCOM™ continuous glucose monitoring devices (DCGMs) have been shown to improve glycaemic control and complication rates in people with Type 1 diabetes (T1DM). However, little qualitative data exists regarding user satisfaction, useful features and the overall lived experience of using a DCGM which will strongly impact one’s quality of life (QOL), compliance and the self-management of diabetes. This study aimed to assess DCGM users’ satisfaction rates and experiences with device features in patients with T1DM in Ireland. Methods: A questionnaire consisting of open- and closed-ended questions together with a glucose monitoring satisfaction survey (GMSS) was offered to all patients attending Sligo University Hospital (SUH) diabetes clinic who used a DCGM for at least six months. Results: Data was analysed for 73 participants. Self-reported QOL improved in 88% of participants and 52% of participants reported fewer hypoglycaemic events. The features most liked by participants were alerts given when the glycaemic target was not in range, improved quality of life, improved hypoglycaemia awareness and the need for reduced finger pricking. However, concerns were also identified about redundant alarms and sensor failures, phone incompatibility and skin reactions. DCGM was associated with good levels of glucose monitoring satisfaction with an overall satisfaction score of 3.67 ± 1.24 out of 5. Participants reported high openness (4.01 ± 0.91), increased trust (3.77 ± 1.16) and low emotional (1.70 ± 0.97) and behavioural burden (2.38 ± 1.10) with DCGM usage. Male participants who had diabetes for a mean duration of 20.06 ± 0.89 years and used DEXCOM^TM for approximately 2 years demonstrated significantly higher levels of satisfaction (p < 0.05). Conclusions: The findings of this study provide a first exploration of patients’ perspectives on DCGM devices in an Irish setting. Results suggest that DCGM users are highly satisfied with the device with an increase in self-reported QOL. Adaptations to features based on patient feedback should be considered to further enhance user satisfaction and maximise QOL benefits. Full article

Background/Objectives: The aim of this secondary analysis is to determine the baseline characteristics that are associated with a higher likelihood of weight-loss success in a personalized nutrition intervention. Methods: Data were analyzed in adults with abnormal glucose metabolism and obesity from a 6-month behavioral counseling randomized clinical trial. Participants were randomized to two calorie-restricted diets: a low-fat diet (Standardized) or a personalized nutrition diet leveraging a machine learning algorithm (Personalized). The gradient boosting machine method was used to determine the baseline variables (i.e., age, weight-loss self-efficacy) that predicted successful weight loss (≥5%) at 6 months in each study arm separately, using repeated five-fold cross-validation with 100 repetitions. Results: A total of 155 participants (Personalized: n = 84 vs. Standardized: n = 71) contributed data (mean [standard deviation]: age, 59 [10] y; 66.5% female; 56.1% White; body mass index (BMI), 33.4 [4.6] kg/m²). In both arms, higher baseline self-efficacy for weight loss was a predictor of weight-loss success. Participants with a higher BMI (p < 0.0001) in the Standardized arm and those who were older (p < 0.0001) in the Personalized arm were more likely to achieve successful weight loss. Conclusions: Future weight-loss interventions may consider providing tailored behavioral support for individuals based on weight-loss self-efficacy, BMI, and age. Full article