Blood Sugar Levels Research Articles

Sugary drink consumption and tooth decay relationship in diabetes mellitus patients

Introduction: Diabetes mellitus is a chronic metabolic disorder characterized by high blood sugar levels. It is a global health problem that can increase the risk of tooth decay and requires conservative dental treatment. Several factors impact the severity of tooth decay, sugary drink consumption is one of them. This study aimed to investigate the association between tooth decay in patients with diabetes mellitus who regularly consume sugary drink versus those who do not. These patients visited Conservative Dentistry Section, Universitas Airlangga Dental Hospital Surabaya, Indonesia, during Jan-Mar 2023. Methods: This study involved 37 patients with diabetes mellitus and posterior tooth decay. Demographic data were gathered from personal interview and dental records. Statistical analysis was done using chi-square analysis. Results: sugary drink consumption has a significant difference (p<0.05) among the patients with posterior tooth decay and diabetes mellitus. Conclusion: sugary drink consumption influences the severity of tooth decay in diabetes mellitus patients.

Exploring the silent epidemic: investigating the hidden burden of normal weight obesity in type 2 Diabetes Mellitus in India - a cross-sectional study

ObjectiveThis study aimed to determine the prevalence of Normal Weight Obesity (NWO) and evaluate its association with cardiometabolic risk factors among patients with Type 2 Diabetes Mellitus (T2DM) in Gujarat, India.MethodsThis cross-sectional study included 432 adults with T2DM attending a Non-Communicable Disease clinic. Anthropometric measurements, body composition analysis using bioelectrical impedance, and clinical parameters were assessed. NWO was defined as normal BMI (18.5–24.9 kg/m²) with high body fat percentage (≥ 25% for men, ≥ 32% for women). Cardiometabolic risk factors, including blood glucose, blood pressure, and lipid profile, were evaluated. Statistical analyses included descriptive statistics, correlation analysis, and multivariate logistic regression.ResultsThe prevalence of NWO was 33% among the study population. Significant discordance was observed between BMI classification and body fat percentage, with 91% of males and 51.8% of females with normal BMI having obese levels of body fat. Individuals with NWO demonstrated higher cardiometabolic risk profiles compared to non-obese counterparts, including elevated random blood glucose levels (290 ± 110 mg/dL vs. 180 ± 80 mg/dL, p < 0.001), higher systolic (148.8 ± 25.4 mmHg vs. 122.5 ± 19.5 mmHg, p < 0.001) and diastolic blood pressure (98.5 ± 55.6 mmHg vs. 78.6 ± 36.6 mmHg, p < 0.001), and increased prevalence of hypertension (61% vs. 15%, p < 0.001). A moderate positive correlation was found between body fat percentage and random blood sugar levels (r = 0.504, p < 0.001). Multivariate analysis identified age, duration of diabetes, blood glucose levels, and blood pressure as independent factors associated with NWO.ConclusionThe high prevalence of NWO and its significant association with adverse cardiometabolic risk factors in T2DM patients underscores the limitations of using BMI alone for obesity assessment. These findings highlight the need for incorporating body composition analysis in routine clinical practice to improve risk stratification and management strategies in T2DM patients, particularly in the Asian Indian population.

Review Paper for Diabetes Mellitus

Diabetes mellitus (DM), a chronic metabolic disorder characterized by hyper-glycemia, has its roots in ancient times. Originating from the Greek words "diabetes" (siphon) and "mellitus" (sweet), DM has plagued humanity for millennia. The condition is marked by the body's inability to produce or effectively use insulin, leading to elevated blood sugar levels. The global prevalence of DM is alarming, with an estimated 463 million individuals affected worldwide in 2019. Type 2 diabetes accounts for the majority of cases, and the disease is a significant contributor to mortality and morbidity. DM imposes a substantial economic burden on healthcare systems globally, with billions of dollars spent annually on treatment and management. The long-term complications of DM are severe and can include cardiovascular disease, kidney disease, nerve damage, and eye problems. Effective management of DM is crucial to prevent these complications and improve quality of life.

Empiric gram-negative antibiotics usage among critically ill patients across 13 ICUs of Nepal: A retrospective cohort study

Background This study aims to investigate the associations between patient characteristics and the receipt of empiric broad-spectrum gram-negative antimicrobials among adult patients admitted to ICUs in Nepal. Methods A retrospective cohort study was conducted in 13 ICUs in Nepal between January 1st, 2020, and December 31st, 2022. Empiric antibiotic use was defined as receiving gram-negative antibiotics within the first two days of ICU admission without evidence of infection from culture. Patient characteristics between patients receiving narrow-spectrum antibiotics and broad-spectrum gram-negative antibiotics were compared. Continuous variables were compared using mean and standard deviation, with mean differences and 95% confidence intervals calculated. Categorical variables were compared using the chi-square test. A multi-level multivariable regression model assessed the relationship between selected variables and broad-spectrum antibiotic usage, treating admitting ICU as a random factor. Results Among 12,349 eligible patients, 8720 (70.6%) received Empiric gram-negative antibiotics. Of those, 3240 (37.15%) received empiric narrow-spectrum gram-negative antibiotics, and 5480 (62.8%) received Empiric broad-spectrum gram-negative antibiotics. Patients receiving broad-spectrum gram-negative antibiotics were older (57.4 vs 53.8 yrs); had higher mean heart rates (97.3 vs 89.5 bpm), respiratory rates (24 vs 21.9), a fraction of inspired oxygen ( 50% vs 40%), blood sugar levels (163.4 vs 153.9 mg/dl), total leucocyte counts (12,685 vs 10,647 cells/cu mm) and serum creatinine (2.06 vs 1.03 umol/l) compared to narrow spectrum antibiotics. Similarly, patients receiving broad-spectrum gram-negative antibiotics had lower systolic blood pressure (122.6 vs 126.5 mm Hg), partial pressure of oxygen (96.7 vs 105.3), and pH ( 7.33 vs 7.36) compared to narrow-spectrum antibiotics. On multivariable regression; patients with readmission, cardiac support, and mechanical ventilation were more likely to receive broad-spectrum antibiotics. Conclusion The rate of empiric broad-spectrum gram-negative antibiotics usage in intensive care units is significantly high and associated with features of increased severity of illness.

Evaluation of the Use of Anti-Diabetic Drugs in Outpatient Type II Diabetes Mellitus Patients at Lasinrang Regional General Hospital, Pinrang Regency in 2023

Diabetes Mellitus (DM), including a disease in the form of metabolic disorders characterized by impaired insulin secretion, impaired insulin production and insulin sensitivity, causing an increase in blood sugar levels (hyperglycemia). This study aims to determine the use of antidiabetic drugs which include the right drug, the right dose, the right indication and the right frequency of administration in outpatient type II diabetes mellitus patients at Lasinrang Regional General Hospital, Pinrang District in 2023. This study is a non-experimental research with a descriptive design retrospectively. The sample in this study is all outpatients with a diagnosis of type II diabetes mellitus at the Lasinrang Regional General Hospital, Pinrang District in 2023. The sampling technique used is purposive sampling. The sample of this study is medical record data of patients with type II diabetes mellitus in 2023, which is adjusted to the inclusion criteria. The results of the study showed that of 87 samples consisting of 55 women and 32 men, all of which met the inclusion and exclusion criteria, and showed that the prevalence of age was more susceptible to be affected at the age of 46-55 years as many as 40 patients (45.98%). In the analysis of the accuracy of drug use, outpatient type II diabetes mellitus patients at the Lasinrang Regional General Hospital, Pinrang regency in 2023 have an indication accuracy of 100%, 100% drug accuracy, 100% dose accuracy, and 100% accuracy frequency of drug administration.

Rationality of using Ayurvedic interventions in Diabetic Neuropathy in Geriatric age group

Diabetic Neuropathy is a damaging of Nervous system associated with Diabetes Mellitus. It occurs due to microvascular injury involving small blood vessels in addition to macrovascular conditions with a prevalence rate of almost 50% in individual with long standing type 1 and type2 Diabetes[1]. Symptoms may include tingling sensation, numbness, burning that starts from feet and spreads proximally etc. In Ayurveda there is no direct reference of Diabetic Neuropathy but it is mentioned as a symptom and complication of Prameha. Hence the most important thing is to be done in Diabetic Neuropathy is to maintain the blood sugar level to normal limits with proper medication, diet, and adequate physical exercises. This review article is to enlighten what ayurvedic interventions including dietary regimen (Ahara), medications (Aushadha) and purificatory method (Shamsodhana) has been used in Prameha to control and prevent its further complications

Heart Failure in Diabetes Mellitus: the Pathogenesis and Treatment

People with diabetes mellitus are more likely to develop heart failure, and those with both conditions often experience a worse prognosis compared to heart failure patients without diabetes. This paper will summarize the pathogenesis of diabetic heart failure and propose treatment and prevention options for diabetic patients with heart failure based on the existing literature and data results. Both types of diabetes lead to high blood sugar levels, which, along with diabetes itself, exert different effects on the heart. As time goes on, it causes heart failure. The outcome demonstrates how chronically elevated blood sugar levels can lead to inflammation and accelerate the development of heart failure. Significant roles are also played by oxidative damage, insulin resistance, and other variables. It has been demonstrated that altering one's lifestyle can avoid diabetic heart failure and improve the quality of life for individuals with asymptomatic diastolic dysfunction and heart failure with preserved ejection fraction (HFpEF).

Assessment of factors affecting anterior chamber depth from data obtained from health checkup participants in Japan

Measurement of anterior chamber depth (ACD), an important marker for the screening of primary angle-closure glaucoma, requires biometry, which is not readily used. This study assessed the relationship between ACD and health check-up data findings from participants with good corrected visual acuity in Japan. Participants underwent ophthalmic, anthropometric, and hematological assessments. The mean ACD of all 3060 participants was 3.33 ± 0.34 mm [2.22–4.72 mm]. Multivariable linear regression analysis was performed to determine factors that were significantly correlated with ACD, and logistic regression analysis was performed to predict ACD < 2.70 mm. Multivariable linear regression analysis showed that age, sex, intraocular pressure, spherical equivalent refractive error (SER), height, and fasting blood sugar levels significantly correlated with ACD (P < 0.05). Logistic regression analysis showed that age, sex, and SER were the best predictors of ACD < 2.70 mm. The area under receiving operator characteristic curves of ‘age and SER’ and ‘age, SER, and sex’ were 0.821 and 0.835, respectively, with no significant difference (P = 0.122). In conclusion, ACD correlates with several parameters, and age and SER may be particularly important for predicting ACD in participants undergoing health checkups.

Investigating the Relationship Between the Levels of Hematological and Biochemical Parameters of COVID-19 Patients with the Length of Hospitalization

Background: Identifying and treating patients with COVID-19 requires the use of quick and precise laboratory diagnostic techniques that assess the patient's health and identify the illness. Aim: This study was conducted to determine the relationship between hematological and biochemical parameters and length of hospitalization in patients with COVID-19. Methods: This is a cross-sectional study of a descriptive-analytical type, which was conducted by census method on 360 medical records of patients with COVID-19 in Imam Khomeini Hospital in Jiroft in 2022. Data were analyzed using descriptive and inferential statistics tests. Results: The average number of days of hospitalization in the present study was 4 days. The rate of COVID-19 was higher in men than in women. The most common underlying diseases in the patients were heart, pulmonary, and diabetes. Among the biochemical parameters, only lactate dehydrogenase (LDH), blood urea nitrogen (BUN), aspartate aminotransferase (AST), alanine transaminase (ALT), platelet (PLT), and erythrocyte sedimentation rate (ESR) parameters had a statistically significant relationship with the total length of hospitalization (P-value&lt;0.001). LDH, AST, ALT, creatinine (Cr), creatine phosphokinase (CPK), blood sugar (BS), total bilirubin, and direct bilirubin parameters were higher than normal in hospitalized patients. Conclusion: The results showed that there is a relationship between LDH, BUN, AST, ALT, PLT, and ESR parameters and the length of hospitalization of patients. The levels of LDH, AST, ALT, Cr, CPK, BS, total bilirubin, and direct bilirubin parameters in patients were higher than normal.

The Impact of Clinical Parameters on LSTM-based Blood Glucose Estimate in Type 1 Diabetes

Accurate forecasting of blood sugar levels is essential for managing diabetes, especially Type-1 reducing incidences, and diminishing care, costs in patients. In this study, a Long Short-Term Memory Recurrent Neural Network (LSTM) model has been employed to predict blood glucose levels using clinical data. The research focuses on identifying and analyzing several key parameters that play a significant role in determining future blood glucose levels, ensuring a robust and reliable prediction framework. We have considered patient-specific features: Insulin-Sensitivity-Factor (ISF), total daily dose (TDD) of insulin, HbA1C levels, height and weight of a patient, and age and gender while analyzing the prediction performance for Blood Glucose. We thought training LSTM models on a large dataset and studying the most important predictors with their predictive power would be beneficial. The results indicate that including these clinical parameters improves the accuracy of blood glucose prediction and provides valuable information for individuals to control diabetes. This analysis highlights the efficiency of LSTM networks in making use of patient data to improve prediction models, eventually aiding more effective and individualized treatment strategies for Type 1 diabetic patients (T1D). This work also examines the extent to which each parameter influences the prediction of future blood glucose levels, providing deeper insights into their relative impact and significance in the predictive model.

Dual Multi Scale Attention Network Optimized With Archerfish Hunting Optimization Algorithm for Diabetics Prediction

ABSTRACTDiabetes is a chronic disease that occurs when the body cannot regulate blood sugar levels. Nowadays, the screening tests for diabetes are developed using multivariate regression methods. An increasing amount of data is automatically collected to provide an opportunity for creating challenging and accurate prediction modes that are updated constantly with the help of machine learning techniques. In this manuscript, a Dual Multi Scale Attention Network optimized with Archerfish Hunting Optimization Algorithm is proposed for Diabetes Prediction (DMSAN‐AHO‐DP). Here, the data is gathered through PIMA Indian Diabetes Dataset (PIDD). The collected data is fed towards the preprocessing to remove the noise of input data and improves the data quality by using Contrast Limited Adaptive Histogram Equalization Filtering (CLAHEF) method. Then the preprocessed data are fed to Multi‐Level Haar Wavelet Features Fusion Network (MHWFFN) based feature extraction. Then the extracted data is supplied to the Dual Multi Scale Attention Network (DMSAN) for diabetic or non‐diabetic classification. The hyper parameter of Dual Multi Scale Attention Network is tuned with Archerfish Hunting Optimization (AHO) algorithm, which classifies diabetic or non‐diabetic accurately. The proposed DMSAN‐AHO‐DP technique is implemented in Python. The efficacy of the DMSAN‐AHO‐DP approach is examined with some metrics, like Accuracy, F‐scores, Sensitivity, Specificity, Precision, Recall, Computational time. The DMSAN‐AHO‐DP technique achieves 23.52%, 36.12%, 31.12% higher accuracy and 16.05%, 21.14%, 31.02% lesser error rate compared with existing models: Enhanced Deep Neural Network based Model for Diabetes Prediction (EDNN‐DP), Indian PIMA Dataset using Deep Learning for Diabetes Prediction (ANN‐DP), and Enhanced Support Vector Machine with Deep Neural Network Learning strategies for Diabetes Prediction (SVM‐DNN‐DP).

Optimal control of glucose-insulin dynamics via delay differential model with fractional-order

This paper proposes a delay differential model with fractional order for glucose-insulin endocrine, metabolic regulation model, incorporating beta-cell dynamics to regulate and maintain bloodstream insulin concentration. In the model, two time delays are involved, namely δg and δι, which represent delayed insulin secretion and delayed glucose reduction. A moderate hyperglycemia results in beta-cell growth (negative feedback), while a severe hyperglycemia results in beta-cell reduction (positive feedback). When a time delay passes a bifurcation point, Hopf bifurcation occurs. It is evident from biological findings that the model exhibits periodic oscillations. Furthermore, we present an optimal control problem for external insulin infusions to minimize prolonged high blood sugar levels. Numerical simulations have validated the theoretical results.

Role of Sodium-Glucose Co-Transporter-2 (SGLT2) Inhibitors in Weight Loss: Understanding the Clinical Evidence

Obesity is ubiquitous, affecting millions of people all over the world. Its prevalence is increasing day by day in all age groups, ranging from children to adolescents to adults. It has a significant impact on the overall quality of life. Obesity has a strong relationship with various chronic conditions, including type 2 diabetes mellitus. The risk of developing diabetic mellitus considerably increases in obese individuals. Similarly, obesity in diabetic patients increases their probability of developing serious complications. Moreover, the optimal approach to managing diabetes mellitus (type 2) and obesity should be carried out by means of sustained weight loss and glycemic control. Sodium-glucose cotransporter 2 (SGLT2) inhibitors have been shown to be a revolutionary class of medications with noteworthy weight-loss benefits in addition to their ability to lower blood sugar levels. These remarkable benefits are mentioned in detail in several different clinical trials. Additionally, diverse mechanisms have also been demonstrated comprehensively via which SGLT-2 inhibitors put forth their function of weight loss. FDA-approved SGLT2 inhibitors show a unique mechanism of action by inhibiting the reabsorption of glucose in the renal proximal tubule. By excreting glucose in the urine and by visceral fat lipolysis, these drugs provide a new avenue for weight reduction. SGLT2 inhibitors are now fundamental parts of weight-loss regimens in patients with type 2 diabetes, going beyond their original role as anti-diabetic medications. This article attempts to review the up-to-date literature on the effectiveness of this particular contemporary function of SGLT2 inhibitors.

Relationship of visceral adiposity index (VAI) and visceral body fat among metabolically obese normal weight individuals from Pakistan

BackgroundAn increasing number of people throughout the world are suffering with visceral obesity. Accumulation of visceral fat is a pathogenic manifestation of global fat dysfunction, that leads to inflammation, atherosclerosis, abnormal lipid levels, and high blood pressure. MethodsThis association study was conducted at Department of Medicine, Mayo Hospital Lahore, Pakistan. 30 participants who meet the selection criteria were recruited after taking written consent. Then patients were evaluated for their height, weight and waist circumference body mass index. Visceral fat was calculated by using machine for bio-impendence analysis. Visceral adiposity index was calculated. 5cc venous blood sample was’ collected under aseptic measures and all samples were sent to the hospital’s laboratory for assessment of lipid profile and blood sugar levels. ResultsWe have studied 30 patients (43.8% female and 56.3% male), mean age of study population calculated was 40.6 ±11.80 years. The mean Visceral Body Fat was found to be 13.53 ± 1.41, High-Density Lipoprotein cholesterol mean calculated was 36.91 ± 9.18 mg/dL, and mean Visceral Adiposity Index calculated was 16.75 ± 7.55. Pearson Correlation was used, to find correlation between Visceral Adiposity Index and Visceral Body fat. The value turned out to be .899** shows positive correlation, p- value was 0. 001 significant. ConclusionIn this study we found positive correlation of visceral adiposity index and visceral body fat by use of Bio impedance analysis machine among metabolically obese normal weight individuals. Visceral adiposity index requires many blood tests while Bio impedance analysis machine can be used in simple outdoor settings hence, we can isolate high risk patient in outdoor settings without any invasive procedures or laboratory investigations.

Micromolar-level glucose detection using a colorimetric sensor based on imprinted polymer-coated Fe3O4 nanoparticles

The glucose concentration in the blood, commonly referred to as blood sugar level, typically ranges from 3.9 to 5.6 mmol/L. It is one of the most critical physiological parameters in the human body, requiring strict regulation to maintain proper bodily function. There is a strong demand for glucose sensors that are highly sensitive, user-friendly, and exhibit high selectivity towards glucose molecules, even in challenging environments. In this study, a colorimetric sensor based on imprinted polymer and Fe3O4 nanoparticles (NPs) was developed, enabling the detection of glucose at micromolar levels, observable by the naked eye. Fe3O4 NPs were prepared using a sol–gel method and served as cores for the deposition of polydopamine (PDA) via in situ polymerization. An imprinting process created glucose-imprinted PDA, resulting in molecular cavities on the PDA surface, with the polymeric layer approximately 25 nm thick. The surface of the Fe3O4 NPs facilitated the degradation reaction of H2O2 to produce hydroxyl radicals (•OH), which subsequently oxidized 3,3′,5,5′-Tetramethylbenzidine (TMB) to its oxidized form (TMB+), causing a color change from colorless to blue. The cavities played a crucial role in the sensing mechanism, connecting the catalytic surface of the Fe3O4 NPs to the surrounding environment. When glucose molecules occupied the cavities, the catalytic activity decreased, leading to a corresponding variation in color change depending on glucose concentration. Leveraging these advantages, the imprinted PDA was applied to detect glucose in aqueous solutions and human plasma with a limit of detection as low as 10 µM. The sensor exhibited high selectivity towards glucose over other common analytes in human blood, such as lysine, Ca2+, and K+, along with reproducibility, maintaining approximately 73 % of its sensing signal after six cycles of reuse. This study demonstrates the detection of glucose by the naked eye at micromolar levels. The detection procedure can be conducted outside of laboratory settings, presenting a highly promising approach for glucose detection in real-world applications, particularly in remote areas.

Diabetic foot ulcer healing potential of Tagetes erecta L. flower extract on successive administration in alloxan-induced diabetic rats via modulation of liver functions

Diabetes mellitus is a prevalent endocrine disorder characterized by inadequate insulin production by the pancreas or improper utilization of insulin by the body, which imposes severe health complications, including cardiovascular, kidney, and neurological disorders with a high potential of foot ulcers. Globally, diabetes is responsible for over 70 % of limb amputations. Alloxan was used to induce diabetes in rats while foot ulcers were induced by the excision method in diabetic rats. Diabetes was confirmed by measuring the parameters like blood glucose, body weight changes, urine excretion, and other biomarker levels after oral administration of Tagetes erecta L. flower extract (TEFE) at different doses. During the work, it was observed that TEFE demonstrated a dose-dependent effect on blood sugar level from 370.2 mg/dl to 113.00 mg/dl and healing of diabetic foot ulcers in a 13 days animal model (p < 0.01). There is significant decline in SGOT, SPGT and ALP levels when compared with diseased group animals. Decrease in wound size was observed when TEFE was administered to diabetic foot ulcer rats. These exciting results steered to enumerate the possible role of TEFE in Diabetes mellitus through a panel of mechanisms of action like inhibition of free radical generation, modulation of liver enzymes and metabolism of glucose etc. The above findings support the hypoglycaemic and diabetic foot ulcer healing potential of TEFE. Moreover, further investigation is required to completely understand the possible mechanism of TEFE.

Research Progress on the Anticancer Activity of Plant Polysaccharides.

Tumor is a serious threat to human health, with extremely high morbidity and mortality rates. However, tumor treatment is challenging, and the development of antitumor drugs has always been a significant research focus. Plant polysaccharides are known to possess various biological activities. They have many pharmacological properties such as immunomodulation, antitumor, antiviral, antioxidative, antithrombotic, and antiradiation effects, reduction of blood pressure and blood sugar levels, and protection from liver injury. Among these effects, the antitumor effect of plant polysaccharides has been widely studied. Plant polysaccharides can inhibit tumor proliferation and growth by inhibiting tumor cell invasion and metastasis, inducing cell apoptosis, affecting the cell cycle, and regulating the tumor microenvironment. They also have the characteristics of safety, high efficiency, and low toxicity, which can alleviate, to a certain extent, the adverse reactions caused by traditional tumor treatment methods such as surgery, radiotherapy, and chemotherapy. Therefore, this paper systematically summarizes the direct antitumor effects of plant polysaccharides, their regulatory effects on the tumor microenvironment, and intervening many common high-incidence tumors in other ways. It also provides data support for the administration of plant polysaccharides in modern tumor drug therapy, enabling the identification of new targets and development of new drugs for tumor therapy.

Therapeutic and Health Promoting Potential of Terminalia chebula: An Exploratory Literature Review

: The plant Terminalia chebula has been used traditionally in many regions of the world for its therapeutic properties, especially in India. Its therapeutic and health-promoting potential has been recognized for centuries, and modern research continues to unveil its numerous benefits. One of the most significant applications of this plant is its antimicrobial and antioxidant potential. The plant contains high levels of phenolic compounds and flavonoids, which scavenge harmful free radicals in the body, reducing oxidative stress and cellular damage. This antioxidant action contributes to its anti-inflammatory effects, making it beneficial for a wide range of conditions, including arthritis, cardiovascular diseases, and neurodegenerative disorders. Furthermore, Terminalia chebula exhibits antimicrobial activity against various bacteria and fungi, including those responsible for common infections. It has been used to treat respiratory infections, urinary tract infections, and skin ailments. Its broad-spectrum antimicrobial effects make it a valuable natural remedy for combating microbial pathogens. Moreover, Terminalia chebula shows potential in managing diabetes and promoting cardiovascular health. Studies have indicated its ability to regulate blood sugar levels, improve insulin sensitivity, and reduce lipid abnormalities. These properties make it a promising adjunct therapy for individuals with diabetes or at risk of heart disease. In conclusion, Terminalia chebula possesses remarkable therapeutic and health-promoting potential. Its antioxidant, anti-inflammatory, antimicrobial, and digestive benefits make it a valuable natural remedy for various ailments. While research on Terminalia chebula is ongoing, its long-standing use in traditional medicine and emerging scientific evidence solidify its status as a potent medicinal plant with diverse applications in promoting overall well-being.

Synergistic effect of Wharton's jelly-derived mesenchymal stem cells and insulin on Schwann cell proliferation in Charcot-Marie-Tooth disease type 1A treatment

Charcot-Marie-Tooth disease type 1A (CMT1A) is a demyelinating disease caused by PMP22 duplication and an exceedingly rare hereditary peripheral neuropathy, with an incidence of 1 in 2500. Currently, no cure exists for CMT1A; however, various therapeutic approaches are under development. Considering the known therapeutic effects of mesenchymal stem cells (MSCs) and the relation of blood sugar levels with nerve damage in CMT, this study aimed to confirm the therapeutic effects of MSCs and insulin on CMT, using both in-vitro and in-vivo models. CMT1A in-vitro models were exposed to Wharton's jelly-derived MSCs (WJ-MSCs) or insulin, and the resulting proliferation changes were measured. CMT1A mice were treated with WJ-MSCs or insulin, and their phenotypic changes were observed. We observed improvements in myelination of Schwann cells in vitro and motor function in vivo. Insulin also showed therapeutic efficacy by promoting Schwann cell proliferation. Furthermore, combination therapy using insulin and WJ-MSCs was more effective than WJ-MSCs or insulin alone. Insulin promoted the proliferation of Schwann cells and WJ-MSCs through activation of the ATK and PI3K-MAPK signaling pathways. Overall, this study is the first to confirm the therapeutic efficacy of WJ-MSCs and insulin in CMT1A, and their synergistic effect without causing insulin resistance.

A novel electrochemical high-performance non-enzymatic glucose sensing based on face-centred cubic FeCoNiMnCr high entropy nano alloys encapsulated in NCNTs

Here, we report a novel approach for non-enzymatic glucose sensing, utilizing a FeCoNiMnCr High Entropy Nano Alloy (HENA) encapsulated within N-doped carbon nanotubes (NCNT). The encapsulation of HENA within NCNT offers multiple advantages such as high sensitivity, low Limit of Detection (LOD), and fast response time. A step forward, the practical viability of the sensor has been demonstrated by detecting glucose in saliva medium. This non-invasive method for monitoring blood sugar levels highlights the potential of HENA@NCNT for wearable or portable glucose monitoring devices. The material also serves as a highly effective electrocatalyst for the oxygen evolution reaction (OER), with performance comparable to state-of-the-art catalyst RuO2. This makes HENA@NCNT a promising candidate for fuel cell applications and other energy storage systems. Density Functional Theory (DFT) analysis provides a deeper understanding of the advantages conferred by NCNT encapsulation. The encapsulation enhances the stability, efficiency, and durability of HENA by optimizing electronic structure and charge transfer processes making it more effective for both glucose sensing and OER