Fluctuations In Blood Glucose Levels Research Articles

Intermittent hyperglycaemia induces macrophage dysfunction by extracellular regulated protein kinase-dependent PKM2 translocation in periodontitis.

Early fluctuations in blood glucose levels increased susceptibility to macrophage dysfunction. However, the underlying pathological mechanisms linking glucose variations and macrophage dysregulation remains elusive. In current study, we established an animal model of transient intermittent hyperglycaemia (TIH) to simulate early fluctuations in blood glucose levels. Our findings revealed that both TIH and diabetic group exhibited more severe periodontal lesions and increased secretion of pro-inflammatory cytokines compared to healthy controls. In immortalized bone marrow-derived macrophages (iBMDMs), phagocytosis and chemotaxis were impaired with transient and lasting hyperglycaemia, accompanied by enhanced glycolysis. We also found that TIH activated pyruvate kinase M2 (PKM2) through the phosphorylation of extracellular regulated protein kinase (ERK) in vivo, particularly at dimeric levels. In macrophage cultured with TIH, PKM2 translocated into the nucleus and involved in the regulating inflammatory genes, including TNF-α, IL-6 and IL-1β. PKM2 translocation and secretion of inflammatory cytokines were attenuated by PD98059, while PKM2 tetramer activator TEPP-46 prevented the formation of dimeric PKM2 in macrophages. Moreover, inhibition of glycolysis alleviated the TIH-induced pro-inflammatory cytokines. In conclusion, our manuscript provides a rationale for understanding how TIH modulates metabolic rewiring and dysfunction in macrophages via ERK-dependent PKM2 nuclear translocation.

The role of low glycemic index and load diets in medical nutrition therapy for type 2 diabetes: an update.

The increasing prevalence of type 2 diabetes mellitus (T2DM) and its microvascular and macrovascular complications necessitate an optimal approach to prevention and management. Medical nutrition therapy serves as the cornerstone of diabetes care, reducing reliance on diabetic medications for glycemic control and mitigating cardiovascular risk. The broadening field of research in the effect of low glycemic index (GI) and/or glycemic load (GL) diets on individuals with T2DM has yielded promising results in the existing literature. Adopting low-GI and GL dietary patterns contributes to minimizing fluctuations in blood glucose levels, thus presenting a good strategy for achieving enhanced glycemic control. Furthermore, the above dietary practices may offer a viable alternative and practical approach to weight management in individuals with T2DM. However, clinical practice guidelines for diabetes dietary management show inconsistency regarding the certainty of evidence supporting the implementation of low-GI/GL nutritional patterns. This review aims to thoroughly evaluate the available data on the effectiveness of low-GI and low-GL diets in managing glycemic control and reducing cardiovascular risk factors.

A systematic review on diabetic retinopathy detection and classification based on deep learning techniques using fundus images.

Diabetic retinopathy (DR) is the leading cause of visual impairment globally. It occurs due to long-term diabetes with fluctuating blood glucose levels. It has become a significant concern for people in the working age group as it can lead to vision loss in the future. Manual examination of fundus images is time-consuming and requires much effort and expertise to determine the severity of the retinopathy. To diagnose and evaluate the disease, deep learning-based technologies have been used, which analyze blood vessels, microaneurysms, exudates, macula, optic discs, and hemorrhages also used for initial detection and grading of DR. This study examines the fundamentals of diabetes, its prevalence, complications, and treatment strategies that use artificial intelligence methods such as machine learning (ML), deep learning (DL), and federated learning (FL). The research covers future studies, performance assessments, biomarkers, screening methods, and current datasets. Various neural network designs, including recurrent neural networks (RNNs), generative adversarial networks (GANs), and applications of ML, DL, and FL in the processing of fundus images, such as convolutional neural networks (CNNs) and their variations, are thoroughly examined. The potential research methods, such as developing DL models and incorporating heterogeneous data sources, are also outlined. Finally, the challenges and future directions of this research are discussed.

Optimizing type 2 diabetes management: AI-enhanced time series analysis of continuous glucose monitoring data for personalized dietary intervention.

Despite advanced health facilities in many developed countries, diabetic patients face multifold health challenges. Type 2 diabetes mellitus (T2DM) go along with conspicuous symptoms due to frequent peaks, hypoglycemia <=70 mg/dL (while fasting), or hyperglycemia >=180 mg/dL two hours postprandial, according to the American Diabetes Association (ADA)). The worse effects of Type 2 diabetes mellitus are precisely associated with the poor lifestyle adopted by patients. In particular, a healthy diet and nutritious food are the key to success for such patients. This study was done to help T2DM patients improve their health by developing a favorable lifestyle under an AI-assisted Continuous glucose monitoring (CGM) digital system. This study aims to reduce the blood glucose level fluctuations of such patients by rectifying their daily diet and maintaining their exertion vs. food consumption records. In this study, a well-precise prediction is obtained by training the ML model on a dataset recorded from CGM sensor devices attached to T2DM patients under observation. As the data obtained from the CGM sensor is time series, to predict blood glucose levels, the time series analysis and forecasting are done with XGBoost, SARIMA, and Prophet. The results of different Models are then compared based on performance metrics. This helped in monitoring various trends, specifically irregular patterns of the patient's glucose data, collected by the CGM sensor. Later, keeping track of these trends and seasonality, the diet is adjusted accordingly by adding or removing particular food and keeping track of its nutrients with the intervention of a commercially available all-in-one AI solution for food recognition. This created an interactive assistive system, where the predicted results are compared to food contents to bring the blood glucose levels within the normal range for maintaining a healthy lifestyle and to alert about blood glucose fluctuations before the time that are going to occur sooner. This study will help T2DM patients get in managing diabetes and ultimately bring HbA1c within the normal range (<= 5.7%) for diabetic and pre-diabetic patients, three months after the intervention.

Investigation of the Cognitive Activity Between the Leaf Extracts of Eclipta alba and Ziziphus jujuba in Diabetic Animal Models.

Diabetes mellitus (DM), a prevalent metabolic disorder, is associated with widespread damage to bodily systems, notably causing significant dysfunction within the peripheral and central nervous systems (CNS). The primary objective of this study is to explore the extent of DM's impact on cognitive and behavioral functions and to evaluate the therapeutic potential of ethanol leaf extracts from Ziziphus jujuba (ZJ) and Eclipta alba (EA) in mitigating these adverse effects. Utilizing an established animal model, we aimed to determine the effectiveness of these plant extracts in ameliorating the cognitive impairments commonly seen in diabetic states. In our experimental framework, we allocated Wistar rats (n=6 per group) into eight different groups, inducing DM through alloxan administration. The intervention groups were treated orally with either the standard antidiabetic drug glibenclamide or varying doses of ZJ and EA extracts over periods of seven and 21 days. Throughout the study, we carefully tracked fluctuations in blood glucose levels, noting considerable decreases, particularly following the 21-day treatment interval. Post-treatment, the rats' cognitive functions were assessed using the Morris water maze (MWM) test. This evaluation revealed significant cognitive enhancement in the diabetic rats administered with ZJ and EA extracts, with these groups displaying reduced latency in finding the submerged platform, indicative of improved learning and memory. These observations were statistically significant (p<0.01). The findings underscore the hypoglycemic effects of ZJ and EA extracts and suggest their viability as cognitive enhancers in the context of DM. The protective effects of these extracts against cognitive decline caused by DM are clear. They add important new information to the research on natural phytochemicals for managing chronic diseases. This study opens new avenues for the application of these substances in treating neurocognitive disorders associated with DM.

Association of Long-Term HbA1c Variability with Anxiety and Depression in Patients with Type 2 Diabetes: A Cross-Sectional Retrospective Study.

To explore the relationship between long-term glycemic variability and anxiety and depression in patients with type 2 diabetes. A cohort comprising 214 individuals diagnosed with type 2 diabetes participated in this study. Comprehensive demographic and laboratory information was gathered for them. The evaluation of anxiety relied on the 7-item Generalized Anxiety Disorder Scale (GAD-7), while depression was assessed utilizing the 9-item Health Questionnaire (PHQ-9). Based on the presence or absence of anxiety and depression, participants were categorized into either the mood disorder or control groups. Subsequently, univariate and stepwise multiple binary logistic regression analyses were conducted to investigate the potential correlations between factors and the presence of anxiety and depression. The prevalence of anxiety disorders is 23%, and depression is 32%. The prevalence of smoking, diabetic autonomic neuropathy, stroke, and osteoporosis in the mood disorder group was significantly higher than that in the control group (P < 0.05), the glycated hemoglobin A1c variability score (HVS), mean hemoglobin A1c value, total cholesterol, urinary albumin/creatinine and systemic immune-inflammatory index (SII) were significantly higher in the control group (P < 0.05). The level of high-density lipoprotein in the mood disorder group was significantly lower than the control group (P < 0.05). In stepwise multiple binary logistic regression analyses, the main factors associated with anxiety were depression (P < 0.001, OR=117.581) and gender (P < 0.001, OR=9.466), and the main factors related to depression included anxiety (P < 0.001, OR=49.424), smoking (P=0.042, OR=2.728), HVS (P=0.004, OR=8.664), and SII (P=0.014, OR=1.002). Persistent fluctuations in blood glucose levels have been linked to anxiety and depression. Consequently, maintaining an optimal level of glycemic control and minimizing fluctuations becomes imperative in the comprehensive management of diabetes.

Implementation of LoRa Wireless Communication in Smart Diabetic Shoes Design

Diabetes is a widespread medical condition affecting a substantial portion of the global population. It is a metabolic disorder known as diabetes mellitus, characterized by severe fluctuations in blood glucose levels due to inadequate insulin production in the human body. The effective monitoring of diabetes is of paramount importance to researchers as it holds the potential to enhance the quality of healthcare services. Among the challenges faced by individuals with diabetes, one prevalent issue is the development of ulcers, which can be challenging to detect promptly. Technological advancements offer a promising avenue for cost-effective and continuous monitoring of chronic diseases like diabetes. This study centers on the development of IoT-based intelligent diabetic footwear that incorporates pressure sensors and temperature monitoring for individuals with diabetic feet. In the evaluation of SX1278 (Ra-02) Lora Module communication, deployed at eight different locations, it was observed that two of these points achieved a flawless transmission success rate of 100%. Conversely, the communication failed at points 6 and 7, with a success rate falling below 50%. Some of these failures can be attributed to signal obstructions, including natural elements such as trees and terrain, as well as man-made structures like buildings and machinery workshops, which hinder the efficient transmission of signals from the end node to the gateway. The results of this research provide positive implications in the form of developing IoT-based diabetes shoes that can be applied with alternative Lora communication connections in areas with poor internet signal.

The effect of sodium-glucose cotransporter 2 inhibitors as an adjunct to insulin in patients with type 1 diabetes assessed by continuous glucose monitoring: A systematic review and meta-analysis

AimsPatients undergoing insulin-based therapy for type 1 diabetes often experience poor glycemic control characterized by significant fluctuations. This study was undertaken to analyze the effect of sodium-glucose cotransporter 2 inhibitors (SGLT2Is), as an adjunct to insulin, on time in range (TIR) and glycemic variability in patients with type 1 diabetes, using continuous glucose monitoring (CGM). In addition, we examined which type of SGLT2I yielded a superior effect compared to others. MethodsWe conducted a comprehensive search of PubMed, EMBASE, the Cochrane Library, Web of Science, and clinical trial registry websites, retrieving all eligible randomized clinical trials (RCTs) published up until February 2023. We analyzed the mean TIR, mean amplitude of glucose excursions (MAGE), mean daily glucose (MDG), diabetic ketoacidosis (DKA), standard deviation (SD), total insulin dose, and severe hypoglycemia to evaluate the efficacy and safety of SGLT2Is. A random-effects model was also employed. ResultsThis study encompassed 15 RCTs. The meta-analysis revealed that the use of SGLT2Is as an adjuvant therapy to insulin led to a significant increase in TIR (MD = 10.78, 95%CI = 9.33–12.23, I2 = 42 %, P < 0.00001) and a decrease in SD (MD = −0.38, 95%CI = −0.50 to −0.26, I2 = 0 %, P < 0.00001), MAGE (MD = −0.92, 95%CI = −1.17 to −0.67, I2 = 19 %, P < 0.00001), MDG(MD = −1.01, 95%CI = −1.32 to −0.70, I2 = 48 %, P < 0.00001), and total insulin dose (MD = −5.81, 95%CI = −7.81 to −3.82, I2 = 32 %, P < 0.00001). No significant increase was observed in the rate of severe hypoglycemia (RR = 1.04, 95 % CI = 0.76–1.43, P = 0.80). However, SGLT2I therapy was associated with increased DKA occurrence (RR = 2.79, 95 % CI = 1.42–5.48; P = 0.003, I2 = 16 %). In addition, the subgroup analyses based on the type of SGLT2Is revealed that dapagliflozin might exhibit greater efficacy compared to other SGLT2Is across most outcomes. ConclusionsSGLT2Is exhibited a positive effect on improving blood glucose level fluctuations. Subgroup analysis showed that dapagliflozin appeared to have more advantages. However, giving due consideration to preventing adverse effects, particularly DKA, is paramount. RegistrationProspero CRD42023408276.

THU362 A Diagnostic Dilemma: Type 1 Diabetes Vs. Pancreatic Diabetes

Abstract Disclosure: U. Rafat: None. R. Alshantti: None. M. Kim: None. J.L. Gilden: None. Background: Several presentations of diabetes mellitus (DM) do not fit the classic descriptions. Type 1 DM, characterized by immune-mediated destruction of insulin-secreting cells of the pancreas, typically appears before age 40. The first antibodies described associated with development of Type 1 DM were islet cell autoantibodies, and later antibodies to insulin, glutamic acid decarboxylase, protein tyrosine phosphatase, and Zinc transporter 8. Pancreatic DM or type 3c, is characterized by functional deficiency of the pancreas to secrete insulin and maintain glucose homeostasis. It may be caused by acute or chronic pancreatitis, trauma, neoplasia, hemochromatosis, fibrocalculous pancreatopathy, genetics, or idiopathic, and is commonly misdiagnosed as type 2 DM. Case Presentation: We present a 73-year-old Caucasian male with Type 1 DM and retinopathy, neuropathy, hypertension, hyperlipidemia, benign prostatic hyperplasia, obstructive sleep apnea. He was diagnosed with Type 1 DM at age 33 with BMI=29 and hospitalization for diabetic ketoacidosis, and symptoms of polyuria, weight loss, and visual disturbances. He was started with insulin injections. Antibodies were not measured, as they were not widely available at that time. Family history: MI in father and brother and type 2 DM in grandfather. He later started using insulin pump at age 58 for wide fluctuations in blood glucose levels. At age 64, he presented to our endocrine clinic for continued management of assumed autoimmune Type 1 DM. Physical examination: BMI 36, abdominal lipodystrophy, abnormal monofilament with decreased sensations in the left foot. Laboratory: HbA1c=6.7%. c-peptide was low (0.09 ng/mL; normal range: 0.81 - 3.85) with a concomitant BG of 243 mg/dL suggestive of low insulin reserves. After several years, with the development of increased trust, the patient felt confident to reveal a hidden history of extensive alcohol abuse in his 20s, resulting in recurrent episodes of symptoms suggestive of pancreatitis, which required extensive rehabilitation for his drinking problem. He admitted that he had not divulged this history previously. This additional history proved critical to acquiring a correct diagnosis. With this in mind, we deduced that it is highly probable this patient's recurrent bouts of subacute pancreatitis due to alcohol consumption resulted in development of pancreatic DM. Conclusion: Our patient initially presented with the diagnosis of autoimmune type 1 DM. However, after many visits, he first admitted to a past history of long-standing alcohol abuse, which now suggests that he actually has pancreatic DM. Correctly classifying DM can prove crucial to formulating an individualized treatment plan. It is important to note that the classification of DM is not always clear-cut and involves a periodic review of the medical history and clinical characteristics, besides review of laboratory data. Presentation: Thursday, June 15, 2023

Anaesthetic challenges in surgical enucleation of pancreatic insulinoma

Insulinoma is a very rare tumour occurring in 1-4 persons per million per year. It is a functional endocrine tumour of the pancreas characterized by repeated attacks of hypoglycaemia presenting as adrenergic or neuroglycopenic symptoms. Surgical management of insulinoma is the mainstay of treatment which can be done by either laparoscopic or open approach. There is occurrence of rapid and wide fluctuations of blood glucose levels in the intraoperative as well as perioperative period. Intraoperative hypoglycaemia is critical due to masking of symptoms by the effect of anaesthesia and if not detected and treated promptly may lead to permanent neurological insult. We here-in describe the challenges of anaesthetic management in a case of functional pancreatic insulinoma undergoing open surgical enucleation with the help of intraoperative ultrasonography.

Effect of Repeated Bolus and Continuous Glucose Infusion on DNA Damage and Oxidative Stress Biomarkers in Healthy Male Volunteers.

Glucose variability (GV), which describes fluctuations in blood glucose levels within the day, is a phenomenon that is increasingly becoming the target of scientific attention when it comes to increased risk of coronary heart disease. Effects of GV may contribute to the development of metabolic syndrome and type 2 diabetes. Hyperglycemia can lead to oxidative stress resulting in molecular damage due to accumulation of reactive oxygen species (ROS). To discover more about the immediate effects of GV, continuous vs. bolus intravenous glucose administration was applied to 10 healthy men aged 21-30 years over a time frame of 48 h. Whole blood and plasma were analyzed for DNA damage using a comet assay with 3 different treatments (lysis buffer, H2O2, and the lesion-specific enzyme formamidopyrimidine DNA glycosylase (FPG)) as well as for the oxidative stress markers protein carbonyls (PC), unconjugated bilirubin (UCB), and ferric reducing antioxidant power (FRAP). A significant time effect was found in the three DNA damage treatments as well as in PC and UCB possibly due to circadian changes on oxidative stress, but no intervention group effect was observed for any of the markers. In conclusion, bolus vs. continuous glucose administration had no significant acute effect on DNA damage and markers of oxidative stress in healthy men.

Can Enzyme‐Resistant Starch Snack Prevent Blood Glucose Fluctuations? A Pilot Trial in Patients with Insulin‐Treated Type 2 Diabetes

AbstractThis study aims to compare the effect of enzyme‐resistant starch flour (ERSF) and standard wheat flour (SWF) bagels given as a mid‐afternoon snack on blood glucose (BG) levels in patients with insulin‐treated type 2 diabetes mellitus (T2DM). First, bagels containing 15 g of carbohydrates are prepared using ERSF or SWF. Then, the effect of bagels prepared using SWF or ERSF on BG levels is examined through clinical research. A continuous glucose monitoring system (CGMS) device is placed and then, the patients are given three packages of bagels that are visually similar and are asked to consume the red package (SWF bagel) on the first day and blue packages (ERSF bagels) on the second and third days as a mid‐afternoon snack, without consuming anything else. The increase in BG from ERSF is less than that caused by SWF bagel consumption, and SWF is found to have higher BG averages than ERSF (ERSF: 150 mg dL−1, SWF: 170 mg dL−1). Patients stated that they like the taste and do not feel any discomfort while consuming ERSF bagels. ERSF bagels have higher fiber content and cause more even fluctuations in BG levels than SWF bagels. Food fortification using ERSF foods can be recommended for patients with T2DM.

An overview of complications associated with type 1 and type 2 diabetes.

Elevated blood glucose levels (hyperglycaemia) and insulin resistance over time are determinants of the onset and progression of a range of complications associated with diabetes mellitus, including cardiovascular disease, neuropathy (nerve damage), diabetic kidney disease and eye conditions. Maintaining optimal glycaemic control may reduce the risk of developing such complications and has been shown to reduce the severity of some renal and eye conditions. However, achieving optimal glycaemic control can be challenging because of various physical and psychological factors that can cause fluctuations in blood glucose levels. This article provides an overview of some of the complications associated with type 1 and type 2 diabetes.

Correlation Between Time in Range and HbA1c in People with Type 2 Diabetes on Basal Insulin: Post Hoc Analysis of the SWITCH PRO Study.

Use of continuous glucose monitoring (CGM) in people with diabetes may provide a more complete picture of glycemic control than glycated hemoglobin (HbA1c) measurements, which do not capture day-to-day fluctuations in blood glucose levels. The randomized, crossover, phase IV SWITCH PRO study assessed time in range (TIR), derived from CGM, following treatment with insulin degludec or insulin glargine U100 in patients with type 2 diabetes at risk for hypoglycemia. This post hoc analysis evaluated the relationship between TIR and HbA1c, following treatment intensification during the SWITCH PRO study. Correlation between absolute values for TIR (assessed over 2-week intervals) and HbA1c, at baseline and at the end of maintenance period 1 (M1; week 18) or maintenance period 2 (M2; week 36), were assessed by linear regression and using the Spearman correlation coefficient (rs). These methods were also used to assess correlation between change in TIR and change in HbA1c from baseline to the end of M1, both in the full cohort and in subgroups stratified by baseline median HbA1c (≥ 7.5% [≥ 58.5mmol/mol] or < 7.5% [< 58.5mmol/mol]). A total of 419 participants were included in the analysis. A moderate inverse linear correlation was observed between TIR and HbA1c at baseline (rs -0.54), becoming stronger following treatment intensification during maintenance periods M1 (weeks 17-18: rs -0.59) and M2 (weeks35-36: rs -0.60). Changes in TIR and HbA1c from baseline to end of M1 were also linearly inversely correlated in the full cohort (rs -0.40) and the subgroup with baseline HbA1c ≥ 7.5% (rs -0.43). This was less apparent in the subgroup with baseline HbA1c < 7.5% (rs -0.17) (p-interaction = 0.07). Results from this post hoc analysis of data from SWITCH PRO, one of the first large interventional clinical studies to use TIR as the primary outcome, further support TIR as a valid clinical indicator of glycemic control. ClinicalTrials.gov identifier, NCT03687827.

Sucraid (sacrosidase) is the only treatment for CSID: should there be a better option?

Sucraid (sacrosidase) is the only treatment for CSID: should there be a better option?

Effect of Gplife Advance Diabetic Support on Time in Range in Type 2 Diabetes Mellitus Patients: A Case Report

This case report documents 20 patients suffering from uncontrolled type 2 diabetes mellitus, presenting complaints of fluctuating blood glucose levels. The parameters like fasting and postprandial blood glucose, HbA1c and C- peptide levels of patients were evaluated. These patients were then advised an adjuvant therapy of Gplife advanced diabetic support tablets along with their daily insulin injections. After 60 days of treatment, the therapy was discontinued, and patients were subjected to continuous glucose monitoring for 8 days and time in range (TIR) percentage was calculated. Also, the fasting and postprandial blood glucose, HbA1c and C-peptide levels were estimated. The average TIR percentage was found to be 93.2%, whereas the time above range (TAR) and time below range (TBR) was 6.8 % and 0 % respectively, which indicates that the patients had a negligible incidence of hyper and hypoglycemia after 60 days of treatment. There was a significant decrease by 61 % in HbA1c levels, 40.05 % in fasting blood glucose levels and 34.29 % in postprandial blood glucose levels (p&lt;0.001). C-peptide levels increased by 1.38 folds after 60 days of treatment. Also, there were no evidence of diabetic comorbidities. Thus, indicating a marked improvement in the diabetic condition and overall quality of life in patients.

Fuzzy, Graphical Model of Diabetic Therapy

In our previous works we introduced a graphical model representing the diabetic therapy at the onset called MTG (Medical Treatment Graph). One of its advantage is the possibility to follow the consequences of changing the therapy to avoid the incidents of hypo- or hyperglycemia. The definition of these notions are coming from medical norms, however, they introduce the strict borders. In this paper we propose Fuzzy MTG that allows to model the diabetic therapy. By introducing the proper membership function the physician can concentrate only on excessive fluctuations of blood glucose level (BGL) and intervene only when it is necessary. At diabetes onset the individual reaction of the human body to insulin is not stable, therefore, establishing insulin therapy must be done very carefully. We propose the decision support system based on Fuzzy MTG to visually assess the treatment and help the physician in proposing best therapy. The model has been positively validated by a diabetology expert.

Flexible Antenna Sensor in Thumb Spica Splint for Noninvasive Monitoring of Fluctuating Blood Glucose Levels

Antenna is used as a sensor in wearable technology because of its small size. Reduced flexible antenna size avoids mounting problems and crumbling effects on the human skin region during signal acquisition. Moreover, continuous diabetes monitoring needs an efficient antenna sensor design. In this article, we develop a continuous glucose monitoring device using a flexible antenna sensor planted inside the thumb spica splint glove. The flexible antenna sensor comprises polyimide substrate with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\xi _{r}$ </tex-math></inline-formula> = 3.5, tan <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\delta $ </tex-math></inline-formula> = 0.0027, and a thickness of 0.1 mm. The proposed flexible antenna sensor senses dielectric radiations from glucose in the blood and improves the accuracy of glucose-level prediction. Traditional antenna sensor methods use skin layers and muscles as sources of permittivity, resulting in errors in diabetic value measurement. The acquired antenna sensor signal from the designed thumb spica splint glove is processed using the tunable <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${Q}$ </tex-math></inline-formula> -factor wavelet transform (TQWT) algorithm. It differentiates the dielectric properties of glucose in the blood, skin, and muscle through subband energy levels. The subband energy level of glucose from the proposed antenna sensor and the quadratic regression algorithm is used to predict the human glucose level. The predicted glucose levels using the proposed flexible antenna are validated through Accu-Chek Active Glucometer. From experimental results, the proposed method-based glucose prediction-level accuracy achieved about 96.8% compared to traditional methods.

Glucose-responsive microneedle patch for closed-loop dual-hormone delivery in mice and pigs

Insulin and glucagon secreted from the pancreas with dynamic balance play a vital role in regulating blood glucose levels. Although distinct glucose-responsive insulin delivery systems have been developed, the lack of a self-regulated glucagon release module limits their clinical applications due to the potential risk of hypoglycemia. Here, we describe a transdermal polymeric microneedle patch for glucose-responsive closed-loop insulin and glucagon delivery to achieve glycemic regulation with minimized risk of hypoglycemia. The glucose-responsive phenylboronic acid units can bind to glucose to reversibly shift the net charge (from positive to negative) of the entire polymeric matrix within microneedles. Therefore, the release ratio of the negatively charged insulin and the positively charged glucagon analog from the patch can be dynamically tuned upon the fluctuation of blood glucose levels to realize glycemic homeostasis. In both chemically induced type 1 diabetic mouse and minipig models, this glucose-responsive dual-hormone microneedle patch demonstrated tight long-term regulation in blood glucose levels (>24 hours in minipigs).

Simvastatin Therapy Increased miR-150-5p Expression in the Patients with Type 2 Diabetes and COVID-19.

Corona virus disease 2019 (COVID-19) has become a deadly infectious disease, especially for those with co-morbidities such as diabetes. People with diabetes developing a viral infection, seem to have harder treatments due to fluctuations in blood glucose levels therefore, effective therapeutic approaches need to be considered for them. Statins are well-known lipid-lowering drugs; they also have anti-inflammatory and immunomodulatory effects and can impact on expression of microRNAs (miRNAs). In this study we investigate the effects of simvastatin on the expression of miR-150-5p as a famous regulator of inflammationand its association with multiple cancers in 30 patients with Type 2 diabetes mellitus (T2DM) and COVID-19 compared to the COVID-19 hospitalized patients before and after treatment with simvastatin with real-time-PCR after 2month, and evaluate its targets gens and functions with the help of bioinformatics and GO enrichment analysis respectively. Our results showed that simvastatin can increase miR-150-5p and therefore down regulate expression of its target genes involving in immune stimulation and decrease lipid profile including LDL-C, total cholesterol, and ApoB, especially in the group with type 2 diabetes mellitus (T2DM) and COVID-19 compared to the patients with only COVID-19. Simvastatin as an anti-inflammatory agent can modulate miRNAs expression; it can be suggested as an adjunct therapy especially for T2DM patients with COVID-19. Further studies may help us for developing better treatments about therapeutic manipulation of miRNAs in vivo.