Current diabetes reviews最新文献

Recent studies have found that a link between people with type 1 diabetes mellitus (T1DM) are at higher risk of morbidity as well as mortality from COVID-19 infection, indicating a need for vaccination. T1DM appears to impair innate and adaptive immunity. The overabundance of pro-inflammatory cytokines produced in COVID-19 illness that is severe and potentially fatal is known as a "cytokine storm." Numerous cohorts have revealed chronic inflammation as a key risk factor for unfavorable COVID-19 outcomes. TNF-α, interleukin (IL)-1a, IL-1, IL-2, IL-6, and other cytokines were found in higher concentrations in patients with T1DM. Even more importantly, oxidative stress contributes significantly to the severity and course of COVID- 19's significant role in the progression and severity of COVID-19 diseases. Severe glucose excursions, a defining characteristic of type 1 diabetes, are widely recognized for their potent role as mediating agents of oxidative stress via several routes, such as heightened production of advanced glycation end products (AGEs) and activation of protein kinase C (PKC). Furthermore, persistent endothelial dysfunction and hypercoagulation found in T1DM may impair microcirculation and endothelium, which could result in the development of various organ failure and acute breathing syndrome.

Background: Gestational diabetes mellitus (GDM) constitutes a common metabolic disorder that could lead to deleterious short- and long-term complications in both the mother and her infant. Probiotic supplementation seems to exert diverse, healthy effects by acting as a preventive agent against various human diseases, including GDM.

Objective: The purpose of the current narrative review was to critically summarize and scrutinize the available clinical studies during the last 15 years (2008-2023) concerning the use of probiotic supplementation during pregnancy as a protecting agent against GDM.

Methods: A thorough and in-depth search was performed in the most accurate scientific databases, e.g., PubMed., Scopus, Web of Science, and Google Scholar applying effective, and relevant keywords.

Results: There are currently some clinical studies suggesting the potential beneficial impact of probiotic supplementation in the prevention and/or co-treatment of GDM. Nevertheless, there is a high heterogeneity amongst the available clinical studies concerning the dosage, the administration duration, the probiotic species types, the method designs and protocols, and the study populations.

Conclusion: Probiotic supplementation at conventional dosages and in combination with a balanced healthy diet, and lifestyle seems to reduce the the risk of developing GDM, while ameliorating the severity of its symptoms. Further clinical studies taking into account the above considerations should be performed to establish conclusive results, while the future meta-analyses should include studies with the feasibly lowest heterogeneity.

Background: Diabetes Mellitus is a chronic health condition (long-lasting) due to inadequate control of blood levels of glucose. This study presents a prediction of Type 2 Diabetes Mellitus among women using various Machine Learning Algorithms deployed to predict the diabetic condition. A University of California Irvine Diabetes Mellitus Dataset posted in Kaggle was used for analysis.

Methods: The dataset included eight risk factors for Type 2 Diabetes Mellitus prediction, including Age, Systolic Blood Pressure, Glucose, Body Mass Index, Insulin, Skin Thickness, Diabetic Pedigree Function, and Pregnancy. R language was used for the data visualization, while the algorithms considered for the study are Logistic Regression, Support Vector Machines, Decision Trees and Extreme Gradient Boost. The performance analysis of these algorithms on various classification metrics is also presented here, considering the Area Under the Curve and Receiver Operating Characteristics score is the best for Extreme Gradient Boost with 85%, followed by Support Vector Machines and Decision Trees.

Results: The Logistic Regression is showing low performance. But the Decision Trees and Extreme Gradient Boost show promising performance against all the classification metrics. But the Support Vector Machines offers a lower support value; hence it cannot be claimed to be a good classifier. The model showed that the most significant predictors of Type 2 Diabetes Mellitus were strongly correlated with Glucose Levels and mediumly correlated with Body Mass Index, whereas Age, Skin Thickness, Systolic Blood Pressure, Insulin, Pregnancy, and Pedigree Function were less significant. This type of real-time analysis has proved that the symptoms of Type 2 Diabetes Mellitus in women fall entirely different compared to men, which highlights the importance of Glucose Levels and Body Mass Index in women.

Conclusion: The prediction of Type 2 Diabetes Mellitus helps public health professionals to help people by suggesting proper food intake and adjusting lifestyle activities with good fitness management in women to make glucose levels and body mass index controlled. Therefore, the healthcare systems should give special attention to diabetic conditions in women to reduce exacerbations of the disease and other associated symptoms. This work attempts to predict the occurrence of Type 2 Diabetes Mellitus among women on their behavioral and biological conditions.

Background: Metabolic syndrome comprises various conditions like abdominal obesity, insulin resistance, elevated triglyceride levels, reduced HDL, and high blood pressure, which pose significant health challenges globally. It's imperative to determine its prevalence in specific populations to formulate effective preventive measures.

Objective: This systematic review and meta-analysis aimed to determine the prevalence of metabolic syndrome in the Qatari population.

Methods: Using the PRISMA guidelines, a systematic search was executed on PubMed until July 2023 with keywords "Metabolic syndrome" and "Qatar." Eligibility criteria included human subjects, studies assessing metabolic syndrome components, and research conducted in Qatar or on Qatari subjects. The quality of the studies was evaluated using the Newcastle-Ottawa Scale (NOS). Pooled prevalence rates were calculated using the inverse variance weighting metaanalysis.

Results: Out of 237 studies, 14 met our inclusion criteria, with a combined sample size of 14,772 from the Qatari population. The overall pooled prevalence of metabolic syndrome was 26%. The ATP III and IDF criteria exhibited significant differences in prevalence rates, with the IDF criteria showing a higher prevalence. Patients in the age of 40 or older demonstrated a higher prevalence compared to the younger group. Studies post-2018 reported a decreasing trend in metabolic syndrome prevalence.

Conclusion: The prevalence of metabolic syndrome in the Qatari population is comparable to rates in the Middle East. The study underscores the need for tailored interventions and strategies, especially targeting the older age group. Continuous research and monitoring are essential to track and understand the disease's progression in Qatar.

Introduction: Diabetes Mellitus (DM) is a metabolic disorder characterized by persistent hyperglycemia and/or insulin resistance. If left uncontrolled, it can lead to a combination of cardiac and renal alterations known as cardiorenal syndrome. Additionally, oxidative stress and inflammation contribute to tissue damage, thereby reducing the life expectancy of individuals with diabetes.

Aim: The aim of this study was to identify early molecular markers associated with cardiorenal syndrome, oxidative stress, and inflammation, and to investigate their correlation with the duration of exposure to DM.

Methods: An experimental DM model was employed using Wistar rats. The rats were divided into four groups: diabetic rats at 7 days (DM7), diabetic rats at 30 days (DM30), control sham at 7 days (CS7), and control sham at 30 days (CS30). Blood and brain tissue from the brainstem region were collected at 7 and 30 days after confirming DM induction. Gene expression analysis of Bnp, Anp, Cat, Gpx, Sod, Tnf-α, and Il-6 was performed.

Results: The analysis revealed lower expression values of Cat in the brainstem tissue of the DM7 group compared to the NDS7 group. Moreover, diabetic animals exhibited statistically lower levels of Tnf-α in their peripheral blood compared to the control animals.

Conclusion: This study concluded that DM alters the oxidative balance in the brainstem after 7 days of DM induction, resulting in lower Cat expression levels. Although some genes did not show statistical differences after 30 days of DM induction, other genes exhibited no expression values, indicating possible gene silencing. The study identified an imbalance in the studied pathways and concluded that the organism undergoes a compensatory state in response to the initial metabolic alterations caused by DM.

Background: DPP-4 inhibitors, or gliptins, are new oral antidiabetic drugs for type 2 diabetes. They help to regulate insulin and glucagon. These drugs have the advantage of a lower risk of hypoglycemia compared to some other diabetes medications and are typically prescribed when metformin and sulphonylureas have become less effective.

Objective: This review analyses a range of analytical and bioanalytical methods for DPP-4 inhibitors, that use spectroscopic techniques, chromatographic, and hyphenated techniques for analysis. So far, no review comprising all DPP-4 inhibitors has been presented. The primary objective of this review is to present the analysts with various analytical and bioanalytical methods for the quantification and estimation of DPP-4 inhibitors in different matrices.

Methods: To improve understanding, a review was carried out by creating a database of pre-existing research from digital sources such as ScienceDirect, and PubMed. The methodology is shown in the flowchart of the literature selection process.

Conclusion: The comprehensive assessment of methods for analysing DPP-4 inhibitors can be a valuable resource for researchers and healthcare practitioners. Hitherto, no review encompassing all DPP-4 inhibitors has been presented. Therefore, gaps in the data available on a particular subject, need to be required to collect data on a particular construct. The review suggests that chromatographic techniques were majorly used for analysis wherein solvents like acetonitrile, methanol, and buffer solutions were used as mobile phases that can deteriorate HPLC columns and equipment. So, scientists could investigate new methods for the assessment of DPP-4 inhibitors using more eco-friendly solvents.

Diabetic Foot Ulcer (DFU) is a major complication of diabetes that mostly affects the lower extremities, with a high incidence and recurrence rate in approximately 15% of patients with diabetes. The complexity of diabetic wounds poses a substantial challenge for clinical recovery, underscoring the need to investigate novel therapeutic approaches. Medicinal plants have been used to treat ulcers for centuries. Recently, there has been a growing focus on the development of topical preparations derived from medicinal plants that target macrophages as an adjuvant therapy for DFU. Macrophages have been identified as crucial factors in the DFU healing process. This review aims to introduce the latest evidence and insights into the role of medicinal plants in promoting DFU recovery by targeting macrophages. The molecular mechanisms underlying the preventive effects of medicinal plants on DFU primarily involve promoting M2 polarization of macrophages, inhibition of M1 polarization, and regulation of macrophage function. This review highlights the substantial potential of advancing the field of DFU management by medicinal plants and lays the groundwork for novel therapeutic interventions.

Chrysin, a flavone nutraceutical, possesses several beneficial pharmacological properties, which has gained much emphasis in recent years. The biological effects of chrysin are exerted due to impeding or activating multifarious cellular and molecular pathways. Our findings indicated that chrysin inhibited tumor progression in various cancer cell lines by repressing the formation of a sphere and upregulated protein expression of Src homology region 2 domain-containing phosphatase-1 (SHP-1), alleviating phosphorylated-signal transducer and activator of transcription 3 (p-STAT3) and transaction workflow innovation standards team1 (Twist1), sustaining phosphorylation of extracellular signal-regulated kinase 1/2 (ERK1/2) and endorsing mitogen-activated protein kinase kinase1 (MEK1) overexpression, increasing the cytochrome c release, mitochondrial reactive oxygen species (ROS) formation, matrix metalloproteinases (MMP) collapse, and caspase-3 activity, modulating p53/ B-cell lymphoma-2 (Bcl-2)/caspase-9 cascade, cyclooxygenase- 2 (COX-2), nuclear factor kappa B proposition 65 (NF-kB p65) expression and also decreasing the expression of nuclear factor erythroid 2-related factor 2 (Nrf2). Chrysin prevented cyclophosphamide, doxorubicin, cisplatin, methotrexate, paracetamol, alcohol, carbon tetrachloride, tert-butyl hydroperoxide (tBHP) and thioacetamide. Chrysin has protective properties against oxidative stress, inflammation, hepatotoxicity, liver fibrosis, steatosis, and hepatocellular carcinoma. Chrysin's most common hepatoprotective biochemical and molecular mechanisms involve the ability to control enzyme synthesis, scavenge free radicals, boost the antioxidant response, induce apoptosis, and modify the synthesis of proinflammatory and profibrotic cytokines.Chrysin is a valuable nutraceutical with broad therapeutic feasibility, but to confirm its representative hepatoprotective potential, clinical studies are advised. It would also be interesting to use cutting-edge drug delivery techniques or include bio-enhancers.

Background: Patients with high-risk feet and diabetes are prone to develop diabetes-related foot ulcers (DFUs). To prevent DFUs and their costs and impacts on diabetes mellitus (DM) patients' productivity and quality of life, patients' foot self-care (FSC) practices are essential to screen for DFUs. Our study aimed to assess the self-efficacy and outcome expectations about FSC and evaluate the knowledge about DFUs among patients with DM in Jordan.

Methods: A cross-sectional study was conducted with DM patients who attended two diabetes clinical centers in Jordan in the period from October 2022 to April 2023 in which data were collected through a self-administered questionnaire developed to assess patients' understanding of DFUs, foot care outcomes expectations (FCOE), and self-efficacy about FSC.

Results: The final sample included data from 107 patients. Patient awareness of DFUs and FCOE was good, and the level of self-efficacy for FSC was moderate to high. Multiple linear regression revealed that age was negatively associated with lower self-efficacy for FSC (β = -0.22, p = 0.03) and both confidence (self-efficacy) in FSC and living arrangements (i.e., living with family) were positively associated with higher FCOE (β = 0.19, p = 0.04 and β = 0.39, p <0.001, respectively). Diagnosis of renal failure, diagnosis of retinopathy, elevated levels of glycated hemoglobin, and the settings in which the patient is receiving care for DM were positively associated with an understanding of DFUs. Both age and history of heart attacks and coronary artery disease were negatively associated with realizing DFUs (β = -0.26, p = 0.007, and β = -0.18, p = 0.045, respectively).

Conclusion: Patients with diabetes mellitus in Jordan have good FCOE, good awareness of DFUs, and a moderate degree of self-efficacy to execute FSC. Health education and self-efficacy programs should focus on older adults with a history of heart attacks to boost their understanding of DFUs and raise their sense of self-efficacy around FSC.

Diabetes, regarded as a prevalent metabolic disorder with multifactorial origins, contributes to a myriad of global complications. These cumulate an elevated susceptibility to kidney failure, nerve impairment, blindness, atherosclerosis, heart ailments, and even strokes. Recent investigations underscore the diverse roles of associated biomarkers in diabetes progression. Among these are biomarkers for diabetes mellitus such as DPP-4, PPAR-ϒ, SGLT-2, α-amylase, and α-glucosidase, which are linked to the onset of diabetes and its related problems. As a result of undesirable adverse consequences linked to extant synthetic antidiabetic medications, research attention is increasingly directed towards formulating natural antidiabetic drugs, aiming for enhanced efficacy and reduced complications. Cyanobacteria stand out as a pivotal repository of natural bioactive metabolites extensively harnessed for pharmaceutical and nutraceutical development. The potent bioactive compounds sourced from cyanobacteria hold substantial promise, kindling high expectations in scientific research and presenting vast prospects for drug discovery and advancement. Some of these bioactive compounds have demonstrated impressive effectiveness, displaying successful applications across various phases of clinical trials. This review strives to provide a more precise understanding of diabetes mellitus, encompassing its clinical manifestation, epidemiological data, complications, and prevailing treatment modalities. The objective of this review is to contribute researchers and readers an enhanced and accurate understanding of diabetes mellitus by covering its clinical manifestation, epidemiological evidence, difficulties, and prevailing therapeutics possibilities.