scholarly journals Role of Folic Acid in Type 2 Diabetes

2021 ◽  
pp. 137-143
Author(s):  
Akshunna Keerti ◽  
Jayshri Jankar
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Coronary Heart Disease ◽  
Folic Acid ◽  
No Synthase ◽  
The Other ◽  
Endothelial Layer ◽  
Pteroylglutamic Acid ◽  
Total Homocysteine

The metabolic condition known as diabetes mellitus is marked by hyperglycemia, a host of symptoms affecting the heart, kidneys, nerves, and other organs. Diabetes nephropathy is one of the leading causes of diabetic impermanence and morbid state. Low parameters of pteroylglutamic acid in the blood are associated with Diabetic Nephropathy, whereas endothelial dysfunction increases the risk for T2D. Endothelial dysfunction is associated with diabetes, which perhaps is caused by the disjunction of the endothelial nitric oxide (NO) synthase enzyme, which reduces NO availability. Because folic acid can repair the disjunction of NO synthase, we sought to see if pteroylglutamic acid supplementation may affect the function of the endothelial layer and inflammatory indicators in type 2 diabetes patients who did not have vascular disease. Recent studies have shown that pteroylglutamic acid also has direct benefits on the function of endo, in addition to its natural function of lowering homocysteine. Folic acid might serve as a "biomarker" for the function of endothelial cells. Many mechanisms have been linked to higher total homocysteine levels and type 2 diabetes risk in diabetic patients. Higher folic acid levels altered endothelial-dependent vasodilation in T2D patients. In patients with coronary heart disease (CAD), folic acid supplementation has been found to reduce homocysteine parameters and improve the function of the endothelial layer. On the other hand, RCTs looking at IR and T2D outcomes have shown mixed results. Several mechanisms link higher total homocysteine levels to increased risk of insulin resistance (IR) and type 2 diabetes mellitus (T2D). Treatment with folate has been shown to bring down homocysteine parameters and improve the endothelium functions in people with coronary heart disease (CAD). Randomized controlled trials (RCTs) on IR and T2D outcomes, on the other hand, have produced a wide range of results.

Mutations of mtDNA in some vascular and metabolic diseases

2020 ◽  
Vol 26 ◽  
Author(s):  
Margarita A. Sazonova ◽  
Anastasia I. Ryzhkova ◽  
Vasily V. Sinyov ◽  
Marina D. Sazonova ◽  
Tatiana V. Kirichenko ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Coronary Heart Disease ◽  
Type 2 Diabetes Mellitus ◽  
Heart Disease ◽  
Chronic Diseases ◽  
Metabolic Diseases ◽  
Present Review ◽  
Mtdna Mutations

Background: The present review article considers some chronic diseases of vascular and metabolic genesis, the causes of which may be mitochondrial dysfunction. Very often, in the long course of the disease, complications may occur, leading to myocardial infarction or ischemic stroke and as a result, death.In particular, a large percentage of human deaths nowadays belongs to cardiovascular diseases such as coronary heart disease (CHD), arterial hypertension, cardiomyopathies and type 2 diabetes mellitus. Objective: The aim of the present review was the analysis of literature sources, devoted to an investigation of a link of mitochondrial DNA mutations with chronic diseases of vascular and metabolic genesis, Results: The analysis of literature indicates the association of the mitochondrial genome mutations with coronary heart disease, type 2 diabetes mellitus, hypertension and various types of cardiomyopathies. Conclusion: The detected mutations can be used to analyze the predisposition to chronic diseases of vascular and metabolic genesis. They can also be used to create molecular-cell models necessary to evaluate the effectiveness of drugs developed for treatment of these pathologies. MtDNA mutations associated withthe absence of diseases of vascular and metabolic genesis could be potential candidates for gene therapy of diseases of vascular and metabolic genesis.

scholarly journals Development of Type 2 Diabetes Mellitus Phenotyping Framework Using Expert Knowledge and Machine Learning Approach

2016 ◽  
Vol 11 (4) ◽  
pp. 791-799 ◽  
Author(s):  
Rina Kagawa ◽  
Yoshimasa Kawazoe ◽  
Yusuke Ida ◽  
Emiko Shinohara ◽  
Katsuya Tanaka ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Machine Learning ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Expert Knowledge ◽  
The Other ◽  
Learning Approach ◽  
Research Subjects ◽  
Machine Learning Approach

Background: Phenotyping is an automated technique that can be used to distinguish patients based on electronic health records. To improve the quality of medical care and advance type 2 diabetes mellitus (T2DM) research, the demand for T2DM phenotyping has been increasing. Some existing phenotyping algorithms are not sufficiently accurate for screening or identifying clinical research subjects. Objective: We propose a practical phenotyping framework using both expert knowledge and a machine learning approach to develop 2 phenotyping algorithms: one is for screening; the other is for identifying research subjects. Methods: We employ expert knowledge as rules to exclude obvious control patients and machine learning to increase accuracy for complicated patients. We developed phenotyping algorithms on the basis of our framework and performed binary classification to determine whether a patient has T2DM. To facilitate development of practical phenotyping algorithms, this study introduces new evaluation metrics: area under the precision-sensitivity curve (AUPS) with a high sensitivity and AUPS with a high positive predictive value. Results: The proposed phenotyping algorithms based on our framework show higher performance than baseline algorithms. Our proposed framework can be used to develop 2 types of phenotyping algorithms depending on the tuning approach: one for screening, the other for identifying research subjects. Conclusions: We develop a novel phenotyping framework that can be easily implemented on the basis of proper evaluation metrics, which are in accordance with users’ objectives. The phenotyping algorithms based on our framework are useful for extraction of T2DM patients in retrospective studies.

scholarly journals Circulating miRNAs as Predictive Biomarkers of Type 2 Diabetes Mellitus Development in Coronary Heart Disease Patients from the CORDIOPREV Study

2018 ◽  
Vol 12 ◽  
pp. 146-157 ◽  
Author(s):  
Rosa Jiménez-Lucena ◽  
Oriol Alberto Rangel-Zúñiga ◽  
Juan Francisco Alcalá-Díaz ◽  
Javier López-Moreno ◽  
Irene Roncero-Ramos ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Coronary Heart Disease ◽  
Type 2 Diabetes Mellitus ◽  
Heart Disease ◽  
Predictive Biomarkers ◽  
Circulating Mirnas

Medical service demands of older patients in different age groups in a new model of free Telemedicine

2020 ◽  
Author(s):  
Yu Gong ◽  
Jianyuan Zhou
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Coronary Heart Disease ◽  
Type 2 Diabetes Mellitus ◽  
Heart Disease ◽  
Older Patients ◽  
Medical Service ◽  
Age Groups ◽  
New Model

Abstract Background Medical service for the older patients is a worldwide challenge for public health system. Telemedicine can provide convenient and effective medical service for older patients. But the existing telemedicine models rely upon a direct communication between a doctor and a patient via the Internet but the doctor would be unable to give the patient a direct physical examination, it may lead to diagnostic errors. A new model of telemedicine jointly performed by general practitioners in community health centers and specialists in a university teaching hospital has been established. It is supervised by the government health department and is free for older patients. However, medical service demands of older patients in different age groups applying the new telemedicine are not well characterized. This study is to analyze medical service demands of older patients in different age groups applying the new telemedicine. Methods 472 older patients (aged ≥ 60) were enrolled and were divided into the young older group (aged 60 to 74), the old older group (aged 75 to 89) and the very old group (aged ≥ 90) according to the age stratification for older people defined by World Health Organization. Proportion of the top 10 diseases of older patients of different age groups was analyzed. Results Coronary heart disease and type 2 diabetes mellitus were identified as the top two diseases in the older patients and the young older patients as well as the old older patients applying the new telemedicine. Conclusions The new telemedicine model can provide effective free medical services to older patients. Different medical service demands were identified in different age groups of older patients. Coronary heart disease and type 2 diabetes mellitus were the main diseases of the older patients and young older patients as well as the old older patients applying the new telemedicine. Results of this study will provide basis for the health administrative departments to formulate health policies for older patients. Familiar with the main diseases in different age groups of older patients may provide better medical services to older patients.

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