Elevated Blood Glucose Levels Research Articles

Predijabetes - entitet savremenog doba sa brojnim faktorima rizika

Prediabetes (PreDM), the seventh leading cause of mortality, is constantly on the rise. It is estimated that by 2035, the number of people affected by prediabetes will reach 471 million people of the total population. Whether a person with prediabetes will develop type 2 diabetes within the next year, or later, or maybe never, depends on numerous factors, some of which are modifiable (body mass index (BMI), waist circumference (WC), lipid status, smoking habits, physical activity). If a person measures postprandial blood glucose levels higher than 7.8 mmol/L, they have twice the cardiovascular risk compared to someone with normal glycemic control. Hyperinsulinemia causes insulin resistance and endothelial dysfunction, while hyperglycemia leads to oxidative radicals forming and activating proinflammatory cytokines. Prediabetes is often associated with obesity and lipid disorders, which further contribute to elevated cardiovascular (CV) risk in individuals with prediabetes. There is a significant number of undiagnosed individuals with prediabetes. Therefore, screening all individuals with risk factors, including proper screening measures such as coronary artery calcium (CAC) scoring, is crucial to assess and prevent cardiovascular risk. It is important to correct all risk factors, and achieve normoglycemia in patients with mildly elevated blood glucose levels, initiate pharmacotherapy at the right time, and as a result, reduce the risk of cardiovascular diseases, cerebrovascular diseases, chronic kidney disease, cancer, and dementia.

The classical Biomarkers to Predict Diabetes Mellitus

Diabetes mellitus is metabolic disorders; depicted by elevated blood glucose levels ascribed to a futile, scanty or sojourns production of insulin. Enduring complications of the disease have been related to peripheral vascular problems, steering to cardiovascular diseases, stroke, diabetic retinopathy, nephropathy and foot. Precise monitoring of these complications and early therapy stages will allow improvement in prevention and treatment approaches. The availability of measurable, accurate and reproducible biomarkers allow the patient to receive timely enactment of personalized therapies and circumventing harmful blood sugar fluctuations that ultimately progress to life-threatening impediments. Profound knowledge of these biomarkers released by extracellular vesicles in metabolic diseases and other disease condition may guide the development of novel therapeutic approaches to restore the affected pathogenesis, rather than merely treating the symptoms. With advent of method that can isolate (ultracentrifugation, affinity-based capture, size exclusion chromatography/filtration, polymer precipitation) and characterize (protein quantification, transmission electron microscopy, atomic force microscopy, ELISA, nanoparticles tracking analysis, flow cytometry, western blot) from body fluids have become a major diagnostic and prognostic biomarkers not only in diabetes, in other conditions like cancer, neurodegradative disease.

Impact of butyric acid modification on the structural and functional properties of rice starch

Rice is a food with a high starch content, comprising over 75% of its composition. However, prolonged and excessive consumption of this cereal may lead to elevated blood glucose levels, which can increase the risk of obesity, type 2 diabetes, and cardiovascular disease. Butyric acid (BA), the primary energy source for colonic epithelial cells, exhibits the highest utilization rate among short-chain fatty acids, underscoring its importance for human health. In this study, rice starch butyrate (RSB) samples were synthesized using the aqueous phase process, with broken rice starch (RS) and butyric anhydride serving as the substrate. RSB samples with different degrees of substitution (DS) were produced by modulating the addition amount of butyric anhydride. The crystal structures, morphology of starch granules, pasting properties, thermal stability, and in vitro digestibilities of the RSB were investigated and compared with those of native rice starch. Fourier transform infrared (FTIR) spectroscopy confirmed the successful incorporation of butyryl into the starch molecules. With the increase in DS, the roughness of the RSB material's surface gradually increased, leading to the deterioration of the smooth structure on certain surfaces, which resulted in the appearance of cracks and collapses. Additionally, the crystallinity diminished from 24.77% to 7.41% with increasing DS. Concurrently, in vitro digestive characterisation revealed that the percentage of resistant starch increased from 24.33% to 47.72%. Thus, this study can provide a theoretical basis for the development of novel products of amyl butyrate.

Daphnetin ameliorates diabetic cardiomyopathy by regulating inflammation and endoplasmic reticulum stress-induced apoptosis.

Daphnetin has been demonstrated to exert beneficial effects on diabetes mellitus and renal complications. However, the role and molecular mechanism of daphnetin in diabetic cardiomyopathy (DCM) remain unclear. In this study, rats were injected with streptozotocin (STZ) to induce diabetes. The diabetic rats were then administered daphnetin (1 and 4 mg/kg) or dimethyl sulfoxide (DMSO) daily for 12 weeks. The results demonstrated that the diabetic rats exhibited elevated blood glucose levels, which were dose-dependently ameliorated by daphnetin. At 13 weeks following STZ injection, the rats exhibited typical diabetic signs, cardiac dysfunction, and evident pathological alterations in myocardial tissues. The administration of daphnetin to diabetic rats resulted in improvement in cardiac function, reductions in myocardial injury biomarkers, and the inhibition of myocardial fibrosis. Furthermore, daphnetin treatment suppressed inflammation and endoplasmic reticulum stress-induced apoptosis in a dose-dependent manner. Additionally, daphnetin exhibited partial blockade of the activation of mitogen-activated protein kinase pathways induced by diabetes. These findings indicate that daphnetin may be a promising therapeutic agent for the treatment of DCM.

Prediction of Diabetes Using Diverse Ensemble Learning Classifiers

Diabetes is classified as a chronic disorder characterized by elevated blood glucose levels resulting from insufficient insulin synthesis or inadequate responsiveness of body cells to insulin. The prevailing protocol at healthcare facilities involves the acquisition of necessary data for the diagnosis of diabetes through a range of diagnostic procedures, followed by the administration of treatment in accordance with the outcomes of those tests. The task of generating precise outcomes using diabetes prediction models is challenging due to limited data availability and the existence of outliers. This study presents a proposed prediction model for diabetes that involves preprocessing techniques applied to the raw data, followed by the utilization of Ensemble Classifiers. The Ensemble Classifiers consist of a combination of catboost, LDA, LR, Random Forest, and GBC. By employing pre-processing approaches and ensemble methodologies, we have achieved improved performance i.e. 90.62% accuracy. The weights of ML models are evaluated using their Area Under Curve (AUC) and receiver operating characteristic curve (ROC) results. This proposed approach helps for clinical trials and help to take precautions at early stage of diabetes.

The effect of Andaliman (Zanthoxylum acanthopodium DC.) fruit extracted with ethanol on TNF-α and TRPA-1 levels in type II diabetes-induced mice.

The present study investigated the effects of Andaliman fruit extract on tumor necrosis factor-alpha (TNF-α) and transient receptor potential ankyrin-1 (TRPA-1) levels in type 2 diabetes mellitus (T2DM) mouse models induced with streptozocin (STZ) and a high-fat diet (HFD). In this research, mice were allocated into six distinct groups: normal, negative control (HFD and STZ), positive control (metformin, HFD, and STZ), and three treatment groups (HFD, STZ, and Andaliman extract at varying dosages of 100, 300, and 500 mg/kg, respectively). Body weight and blood glucose levels (BGLs) were recorded at weeks 1 (baseline), 8, 12, and 16. The levels of TNF-α and TRPA-1 were measured during the 16th week. Phytochemical screening of the Andaliman extract revealed the presence of flavonoids, alkaloids, tannins, saponins, and glycosides. The one-way ANOVA revealed significantly elevated BGL at week 16 in the negative control group in comparison to the other groups (p < 0.05). The Kruskal-Wallis test followed by Bonferroni-corrected pairwise comparisons showed that the negative control had significantly higher TNF-α levels than the Andaliman-groups (z = 22.11, p < 0.01). TRPA-1 was significantly higher in the negative control group compared to the treatment groups (p < 0.05). Furthermore, Spearman's rho analysis revealed a statistically significant positive association between BGL and both TNF-α and TRPA-1, as well as between TNF-α and TRPA. Andaliman extract potentially serves as a therapy for diabetic neuropathy in T2DM by lowering BGL and inhibiting the expression of TNF-α and TRPA-1.

Sativoside Mitigates High-Fat Diet-Induced Inflammation and Type-2 Diabetes in Adipose Tissue of Wistar Rats

This study aimed to investigate the impact of Stevioside, on the biochemical changes in high-fat diet-fed Wistar rats. Adult male Wistar rats were induced into a diabetic state through the administration of a high-fat diet and sucrose for 60 days, followed by oral administration of stevioside (20 mg/kg/day) for 45 days. Various parameters, including fasting blood glucose, oral glucose tolerance, insulin, insulin tolerance, liver function (ALT, AST, ALP), kidney function (urea and creatinine), and lipid profiles (TC, TG, FFA, HDL-c and LDL-c), serum adipokines levels such as adiponectin, leptin, resistin were assessed. Stevioside treatment notably improved glucose and insulin tolerances in diabetic rats and normalized their elevated levels of fasting blood glucose, serum insulin, and lipid profile. In the high-fat diet-induced type 2 diabetes rat model, Stevioside effectively restored the altered blood serum levels, demonstrating efficacy comparable to that of metformin. Therefore, Stevioside displays promise as a potential phytomedicine for managing type 2 diabetes mellitus. Keywords: High-fat diet, Insulin tolerance, Type-2 diabetes, Stevia rebaudiana.

Formulation, Optimization, and Evaluation of Gliclazide loaded Nanosuspension for Dissolution Rate Enhancement

Diabetes mellitus is a prolonged metabolic condition categorized through elevated blood glucose levels. To treat this condition, oral antihyperglycemic medications like gliclazide, a second-generation sulfonylurea insulin secretagogue, are commonly used. Gliclazide comes into the biopharmaceutical classification system (BCS) class-II types, known for its lower solubility. To enhance its solubility, gliclazide was integrated into nanosuspensions. This study focused on formulating these gliclazide nanosuspensions using Kollicoat IR and Soluplus through the anti-solvent-precipitation method, through optimization achieved using the Box Behnken Design. Key parameters assessed included particle size (224 ± 1.23 nm) and entrapment efficiency (95.65 ± 0.12%). The drug release studies conducted on pH 7.4 indicated that over 95% of the drug was released within 30 minutes for the nanosuspension, whereas the pure drug solution released less than 70% in the same time frame, indicating immediate release with the nanosuspension. The morphology was examined using scanning electron microscopy (SEM), while fourier transform infrared (FTIR), X-Ray diffractometers (XRD), and differential scanning calorimeter (DSC) analyses confirmed the presence of the drug within the nanosuspension. In summary, the incorporation of gliclazide into nanosuspensions proved successful, resulting in enhanced release characteristics and ameliorated solubility.

Machine learning reveals neutrophil-to-lymphocyte ratio as a crucial prognostic indicator in severe Japanese encephalitis patients.

Japanese encephalitis (JE) is a severe infectious disease affecting the central nervous system (CNS). However, limited risk factors have been identified for predicting poor prognosis (PP) in adults with severe JE. In this study, we analyzed clinical data from thirty-eight severe adult JE patients and compared them to thirty-three patients without organic CNS disease. Machine learning techniques employing branch-and-bound algorithms were used to identify clinical risk factors. Based on clinical outcomes, patients were categorized into two groups: the PP group (mRs ≥ 3) and the good prognosis (GP) group (mRs ≤ 2) at three months post-discharge. We found that the neutrophil-to-lymphocyte ratio (NLR) and the percentage of neutrophilic count (N%) were significantly higher in the PP group compared to the GP group. Conversely, the percentage of lymphocyte count (L%) was significantly lower in the PP group. Additionally, elevated levels of aspartate aminotransferase (AST) and blood glucose were observed in the PP group compared to the GP group. The clinical parameters most strongly correlated with prognosis, as indicated by Pearson correlation coefficient (PCC), were NLR (PCC 0.45) and blood glucose (PCC 0.45). In summary, our findings indicate that increased serum NLR, N%, decreased L%, abnormal glucose metabolism, and liver function impairment are risk factors associated with poor prognosis in severe adult JE patients.

Synthesis of New Indole‐Based Thiazole Derivatives as Potential Antiglycation and Antiα‐Glucosidase Agents: In Vitro and In Silico Studies

AbstractDiabetes mellitus is a metabolic disease, characterized by the elevated levels of blood glucose, known as hyperglycemia. It is one of the serious health challenges, and is rapidly becoming a significant cause of morbidity, and mortality, worldwide. The persistent hyperglycemic state in diabetes mellitus leads to the formation of advanced glycation end products (AGEs), which is identified as a key factor involved in the progression of diabetes, and diabetes‐associated late complications. keeping in view the medicinal properties of indole, and thiazole, in the present study, novel indole‐based thiazoles (1–26) were synthesized, and evaluated for theirin vitro α‐glucosidase, and antiglycation activities. These indole‐based thiazoles were characterized from their spectral data. All these compounds showed moderate to excellent antiglycation activity (IC50between 642.2±0.013 to 46.93±0.003 μM) including compounds17,20,22–26which showed a significant antiglycation activity as the reference molecule, rutin (IC50=56±0.008 μM) used as standard. Further, these derivatives exhibited significantα‐glucosidase inhibition activity (P&lt;0.001) with IC50in the range of 111.8±0.9001 and 666.5±1.0111 μM (standard drug acarbose: IC50=855.8±1.2001 μM). Binding interactions of these compounds withα‐glucosidase enzyme were studiedin silico, which showed strong correlation with the experimental data. Inhibition ofα‐glucosidase enzyme, and AGEs formation by these compounds suggest them as promising scaffolds for further studies.

&lt;i&gt;In vivo&lt;/i&gt; study of the role of hydrogen peroxide in the development of ishemic stroke in a model of streptozotocin-induced type I diabetes in rats using genetically encoded biosensor HyPer7

Diabetes mellitus is a significant risk factor for the development of complications following ischemic stroke. However, the precise mechanisms through which elevated glycemic status impacts neuronal metabolism during ischemia remain unclear. One probable reason for the exacerbation of post-ischemic consequences under hyperglycemia is oxidative stress, the indicator of which may be H2O2. In this research, we used the genetically encoded fluorescent biosensor HyPer7 to exhibit the hydrogen peroxide dynamics in the matrix of neuronal mitochondria during ischemic stroke under hyperglycemic and normal glucose conditions. The research was conducted on SHR rats with normal and high blood glucose levels. Type I diabetes mellitus was induced by injecting streptozotocin, which is toxic to pancreatic β-cells. For the expression of the fluorescent biosensor HyPer7-mito in the neuronal mitochondria of the caudate nucleus region, a suspension of adeno-associated virus particles carrying the sensor gene under the neuronal promoter was administered under stereotactic control. After the rats were injected, optical fibers with a ceramic adapter were implanted directly into their brain striatum, enabling us to register the H2O2 indicator signal using a highly sensitive fluorescence excitation and detection system developed by the Institute of Photonics and Nonlinear Spectroscopy at Moscow State University. The biosensor signal recording was continuously performed in real-time from the moment the animal was anesthetized. While recording, anesthetized rats underwent middle cerebral artery occlusion, which supplies corpus striatum. Using HyPer7 in the ischemic stroke model described, we observed that the H2O2 concentration dynamics in the affected hemisphere of rats with normal and elevated blood glucose levels were similar during the acute phase of stroke and one day after occlusion. Oxidation of the biosensor was observed in both animal groups during both ischemia and reperfusion. However, HyPer7 exhibited the most marked response one day after the occlusion of the middle cerebral artery, indicating a significant rise in hydrogen peroxide concentration. Furthermore, the metabolic activity of brain tissue was evaluated through staining slices obtained 24 hours after occlusion with 2,3,5-triphenyltetrazolium chloride. Rats with diabetes exhibited 2.6 times larger brain damage, indicating that hyperglycemia exacerbates the consequences of ischemic stroke. Furthermore, there was a higher mortality rate in the hyperglycemic group following ischemic stroke. This indicates that the consequences of ischemic stroke were more severe under hyperglycemia, with 25% of the animals in the hyperglycemic group dying before the experiment ended, whereas none of the control group animals died. Our study found that an elevated glycemic status does not impact the creation of H2O2 during the acute phase of stroke or one day after occlusion. However, it significantly intensifies damage to brain tissue and raises mortality rates.

Laboratory Tests for the Early Detection of Adverse Drug Reaction

The Food and Drug Administration (FDA) of the United States has approved drugs for sale in the country only if they are both safe and effective, meaning that the advantages of the medication must outweigh any known hazards. But over-the-counter (OTC) and prescription medications also have negative effects. (FDA) reactions, sometimes referred to as side effects, are undesired side effects that may be connected to a medication. Side effects can range in severity from little issues like a runny nose to potentially fatal situations like heart attack and in some case may lead to death. Age, use of other drugs, vitamins, or diet supplement, amount of drug, and route of administration can affect on degree of side effect as in IM or IV adverse effect is faster and stronger to appear than in oral route. According to laboratory tests, many tests have been done to detect impact of drug on body. In drugs cause liver failure tests appear elevated in liver enzyme as alkaline phosphatase (ALP), alanine transaminase (ALT), aspartate aminotransferase (AST). In kidney failure laboratory test indicate elevated in lipase and amylase serum.in drugs high cholesterol level such beta blocker, prednisone, and anabolic steroid in lab test detect high cholesterol level above 200mg\dl. Drugs elevate blood glucose as statins, corticosteroid, and beta blocker indicated elevation of blood glucose level above the normal. Analytical methods can consider also laboratory method as have been done in labs, it help in identification and separation of drugs so identify the drug these analytical method as spectrophotometry, gas chromatography, high performance liquid chromatography (HPLC).

A novel evolutionary ensemble prediction model using harmony search and stacking for diabetes diagnosis

Diabetes is a dreaded disease that can be identified by elevated blood glucose levels in the blood, and undiagnosed diabetes can cause a host of related complications, such as retinopathy and nephropathy. In terms of type, the main categories are type 1 diabetes (T1DM), type 2 diabetes (T2DM) and gestational diabetes mellitus (GDM). Machine learning models and metaheuristic optimization algorithms can play an important role in the early detection, diagnosis and treatment of this disease. To this end, we propose AHDHS-Stacking, an ensemble learning framework for diabetes mellitus classification and diagnosis that is based on the harmony search (HS) algorithm and stacking and includes two stages of feature selection and optimization of base-learner combinations. To improve the model’s overall performance, the average performance of all base learners is used as the feature selection target, and an adaptive hyperparameter strategy is used to accelerate the iterative process. HS is then used to optimize to find the best combination of base learners, which improves model performance while reducing complexity. Following that, we conducted experiments on the Pima Indians Diabetes (PID) dataset and the Chinese and Western Medicine Diabetes (CWMD) dataset, achieving accuracy of 93.09%, precision of 93.22%, recall of 91.60% , F-measure of 92.25%, and MCC of 84.79% on PID dataset, which is better than all benchmark models and validated the model’s validity. CWMD dataset experimental results showed that AHDHS-Stacking screened for key features such as age, gender, urinary glucose, fasting glucose, BMI and cholesterol, and can be used as a practical and accurate method for early diabetes prediction.

Genetic predisposition of LEPR (rs1137101) gene polymorphism related to type 2 diabetes mellitus – a meta-analysis

Background: Type 2 diabetes mellitus (T2DM) is a multifaceted disease appropriate to elevated blood glucose levels resulting from decreased insulin and beta-cell activity. Using a case–control methodology, researchers have examined the relationship between polymorphisms in LEPR and T2DM in a population from south India. Materials and Methods: We conducted a genetic analysis of 311 participants, and results were accomplished using a case-control study, a meta-analysis of previous studies on LEPR was conducted, and type 2 diabetes genotype distribution across various geographical regions Malaysians, Chinese Han, Kuwait, Iran, Mongolia, and Han Chinese, Greece, Saudi, India (North India, Punjabi), (South India, Tamilnadu). The study involved 254 prospective investigations, and nine association studies were preferred according to preset criteria. Studies were assessed for quality using the Hardy-Weinberg equilibrium (HWE) and the Newcastle–Ottawa Scale (NOS). An analysis of the genetic models was conducted to determine their relationship, statistical analysis was utilized to calculate odds ratios (ORs) and matching 95% confidence intervals (CIs). Results: The LEPR-rs1137101 polymorphism in the case-control study was associated with a significant increase in the risk of type 2 diabetes. A meta-analysis revealed a connection between LEPR gene polymorphism (rs1137101) and type 2 diabetes risk. Investigators might gain a more profound thought on the significance of the identified genetic variation and its impact on the chance of developing type 2 diabetes by verifying and strengthening previously reported findings. The model of fixed effects was chosen due to the low heterogeneity, and significant associations were observed in the allelic (OR = 0.79, 95% CI [0.70–0.87]), homozygote (OR = 0.58, 95% CI [0.46–0.72]), dominant (OR = 0.66, 95% CI [0.56–0.79]), and recessive (OR = 0.83, 95% CI [0.71–0.96]) genetic models. A Begg’s funnel plot and Egger’s test indicated no publication bias. These findings suggest that the rs1137101 variant in the LEPR gene has been linked to a higher risk of T2DM. Conclusions: A larger sample size, however, is required for further research, and consideration of potential confounding factors is needed to validate these associations. Understanding the implications of LEPR gene polymorphisms in T2DM susceptibility may contribute to personalized treatment strategies for patients with T2DM.

Microplastics cause hepatotoxicity in diabetic mice by disrupting glucolipid metabolism via PP2A/AMPK/HNF4A and promoting fibrosis via the Wnt/β-catenin pathway.

In recent years, microplastics (MPs) have gained significant attention as a persistent environmental pollutant resulting from the decomposition of plastics, leading to their accumulation in the human body. The liver, particularly of individuals with type 2 diabetes mellitus (T2DM), is known to be more susceptible to the adverse effects of environmental pollutants. Therefore, to investigate the potential impact of MPs on the liver of diabetic mice and elucidate the underlying toxicological mechanisms, we exposed db/db mice to 0.5 μm MPs for 3 months. Our results revealed that MPs exposure resulted in several harmful effects, including decreased body weight, disruption of liver structure and function, elevated blood glucose levels, impaired glucose tolerance, and increased glycogen accumulation in the hepatic tissue of the mice. Furthermore, MPs exposure was found to promote hepatic gluconeogenesis by perturbing the PP2A/AMPK/HNF4A signaling pathway. In addition, MPs disrupt redox balance, leading to oxidative damage in the liver. This exposure also disrupted hepatic lipid metabolism, stimulating lipid synthesis while inhibiting catabolism, ultimately resulting in the development of fatty liver. Moreover, MPs were found to induce liver fibrosis by activating the Wnt/β-catenin signaling pathway. Furthermore, MPs influenced adaptive thermogenesis in brown fat by modulating the expression of uncoupling protein 1 (UCP1) and genes associated with mitochondrial oxidative respiration thermogenesis in brown fat. In conclusion, our study demonstrates that MPs induce oxidative damage in the liver, disturb glucose and lipid metabolism, promote hepatic fibrosis, and influence adaptive thermogenesis in brown fat in diabetic mice. These findings underscore the potential adverse effects of MPs on liver health in individuals with T2DM and highlight the importance of further research in this area.

Importance of Dyslipidaemia Treatment in Individuals with Type 2 Diabetes Mellitus—A Narrative Review

Type 2 diabetes mellitus (T2DM) is a common metabolic disease characterised by insulin resistance and elevated blood glucose levels, affecting millions of people worldwide. T2DM individuals with dyslipidaemia have an increased risk of cardiovascular disease (CVD). A complex interplay of risk factors such as hyperglycaemia, dyslipidaemia, hypertension, obesity, inflammation, and oxidative stress favour the development of atherosclerosis, a central mechanism in the pathogenesis of cardiovascular disease. Dyslipidaemia, a hallmark of T2DM, is characterised by elevated triglycerides, decreased high-density lipoprotein (HDL) cholesterol and the presence of small, dense low-density lipoprotein (LDL) particles, all of which promote atherosclerosis. In this article, we have attempted to present various treatment strategies that include pharmacological interventions such as statins, ezetimibe, PCSK9 inhibitors, fibrates, and omega-3 fatty acids. We have also tried to highlight the pivotal role of lifestyle modifications, including physical activity and dietary changes, in improving lipid profiles and overall cardiovascular health in T2DM individuals. We have also tried to present the latest clinical guidelines for the management of dyslipidaemia in T2DM individuals. In conclusion, the treatment of dyslipidaemia in T2DM individuals is of great importance as it lowers lipid particle levels, slows the progression of atherosclerosis, and ultimately reduces susceptibility to cardiovascular disease.

Nanocomposite Hydrogel‐Based Optical Fiber Probe for Continuous Glucose Sensing

Diabetes mellitus (DM) presents a substantial global health concern due to elevated blood glucose levels, necessitating an affordable, rapid, and reliable continuous glucose monitoring (CGM) solution. In this pursuit, a pioneering approach is introduced utilizing optical fiber (OF) sensors based on nanocomposite photonic hydrogel functionalized with phenylboronic acid (PBA) for precise CGM. The fabrication of OF sensors involves a streamlined process, involving one‐step polymerization of PBA‐based hydrogel onto a commercial fiber tip and the integration of gold nanoparticles (AuNPs) via a simple dipping process. These sensors offer robust performance within the physiological glucose range (0–20 mm), exhibiting a remarkable 25% increase in transmission intensity and a 4 nm blue shift in the surface plasmon resonance with increasing glucose concentration. Additionally, there is a noticeable elevation in reflection intensity, affirming the sensor's suitability for remote sensing applications. These results are further validated using a green laser, underlining the method's reliability. The sensors exhibit a swift 30 s response time, followed by a 5 min saturation period, for all measurements. Practicality is demonstrated through smartphone readouts, utilizing the phone's photodiode to measure optical power changes concerning various glucose concentrations. These OF sensors hold great promise for CGM integration, enhancing diabetic management.

P53: Brain, Diabetes and Cognition

Diabetes mellitus (DM) is a chronic metabolic disease, characterized mainly by elevated levels of blood glucose, associated with other important metabolic disturbances. Prevalence of DM is dramatically increasing worldwide, but especially in western countries, due to several factors as like diet, lifestyle and population aging.Recent studies demonstrate that some diabetic patients have an increased risk of developing cognitive decline and dementia compared with healthy individuals. Although this may reflect brain changes as a consequence of diabetes, the coexistence of diabetes and cognitive dysfunction suggest common risk factors and causative mechanisms.Cognitive dysfunction, including mild cognitive impairment and dementia, is increasingly recognized as an important comorbidity and complication of diabetes that affects patient’s health and diabetes management with several public health implications. The aim of our work is to give an overview of cognitive dysfunction in people with diabetes, describing its clinical features and their biochemical basis and future perspectives.

A quantile regression approach to identify risk factors for high blood glucose levels among Bangladeshi individuals.

Diabetes mellitus, characterized by high blood glucose, is an overwhelming public health concern globally, including in Bangladesh. The implication of this trend may pose a significant challenge to the health systems due to the lack of awareness and improper management of this chronic disease. To formulate strategies for public health planning, this study aims to explore the potential risk factors for elevated blood glucose levels among Bangladeshi individuals using advanced statistical methods and a nationally representative data set. This study utilized data from the 2017-18 Bangladesh Demographic and Health Survey and included 11,863 individuals. A nonparametric Kruskal-Wallis test assessed the significant association between fasting plasma glucose levelsand various risk factors. Additionally, a robust quantile regression model was applied to examine the net effects of each risk factor at different quantiles of the distribution. The prevalence of diabetes is 8.1% among individuals in the study population, with variations observed across different administrative divisions in the country. Respondents from the Dhaka division respondents had a higher likelihood (24.1%) of having elevated plasma glucose and the Rangpur division had a lower risk (10.3%) of developing diabetes disease. This study identified several potential risk factors associated with elevated blood glucose levels, including hypertensive disease, overweight and obese body mass index, higher economic status, reduced physical activities, and older age, significantly contributing to develop diabetes mellitus. This study recommends promoting healthy lifestyles, increased physical activity, effective hypertension management, obesity reduction, and nationwide screening programs to control diabetes and noncommunicable diseases in Bangladesh. These preventive measures are crucial for reducing the existing prevalence of diabetes and working towardachieving the Sustainable Development Goals by 2030.

Protective Effect of Hydroalcoholic Extract of Punica granatum Leaves on High Fructose Induced Insulin Resistance in Experimental Animals.

Insulin resistance (IR) is a condition characterized by reduced sensitivity of body tissues to insulin, leading to impaired regulation of downstream metabolic pathways and elevated blood glucose levels. Diets rich in fructose have been proven to cause insulin resistance in test rats, resulting in decreased insulin sensitivity, particularly in the liver, and compromised disposal of glucose from the body. In the search for effective treatments, Plant-derived formulations have gained popularity because to their ability for treating a variety of ailments. One such plant is Punica granatum Linn. from the Punicaceae family, which has long been used in the treatment of diabetes and its consequences. This study investigates the insulin-resistant activity of an extract from Punica granatum leaves. The study goal is to assess the possible protective role of Punica granatum against insulin resistance through various analyses, including serum glucose and insulin levels, lipid profile assessment, measurement of liver enzymes (ALP, SGOT, SGPT), and histopathological examination of liver sections. The study involves several key methods to evaluate the insulin-resistant activity of Punica granatum extract in high fructose diet induced insulin resistance animal model. The extract was administered orally to the experimental animals. These methods include the measurement of serum glucose and serum insulin levels, analysis of the lipid profile, quantification of liver enzymes such as ALP, SGOT, and SGPT, and a detailed histopathological examination of liver tissue sections. These analyses collectively provide insights into the impact of Punica granatum extract on insulin resistance and related metabolic parameters. Findings of this study provide insight on the possible benefits of Punica granatum extract on insulin resistance. Through the assessment of serum glucose and insulin levels, lipid profile analysis, and measurement of liver enzymes, the study elucidates the impact of the extract on key metabolic indicators. Additionally, the histopathological examination of liver sections provides visual insights into the structural changes that may occur as a result of the treatment. In conclusion, this study highlights the ability of Punica granatum extract as a candidate for addressing insulin resistance. The findings suggest that the extract may have a protective role against insulin resistance, as evidenced by improvements in serum glucose and insulin levels, lipid profile, liver enzyme levels, and histopathological characteristics. Further research and investigations are warranted to fully understand the mechanisms underlying these observed effects and to validate the potential of Punica granatum extract as a therapeutic option for managing insulin resistance and its associated complications.