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Review of Deep Learning Techniques for Prognosis and Monitoring of Diabetes Mellitus
Published in Archana Mire, Vinayak Elangovan, Shailaja Patil, Advances in Deep Learning for Medical Image Analysis, 2022
C. Muthamizhchelvan, K. A. Sunitha, M. Saranya, B. Venkatraman, M. Menaka, Sridhar P. Arjunan
Artificial intelligence (AI) is a scientific prediction system that systematizes learning and recognizes patterns for diagnosing pre-diabetes and diabetes [18]. A few blood tests can be done to detect diabetes, including: Fasting plasma glucose: this assists in predicting blood glucose levels after an 8-hour fast.HbA1C test: this assists in predicting glucose levels over a quarter-year period.Blood tests, as well as a glucose challenge test and a 3-hour glucose resilience test, are performed in the 24th and 28th weeks of pregnancy to detect gestational diabetes [19].
Effects of WBV in Individuals with Diabetes and Diabetic Neuropathy
Published in Redha Taiar, Christiano Bittencourt Machado, Xavier Chiementin, Mario Bernardo-Filho, Whole Body Vibrations, 2019
However, exercise must be undertaken regularly for continued benefits (Colberg et al., 2010; Suh et al., 2007; Hayashino et al., 2012). In order to achieve all the benefits, metabolic (better glycemic control) or not, related to physical exercise, the ADA recommends that physical exercise should be performed for at least 150 minutes per week, with moderate intensity (50%–70% of maximal heart rate), and should be performed three days a week at intervals of no more than two days (Colberg et al., 2010). Data from meta-analysis investigating patients with T2DM who performed aerobic exercise compared to those who did not perform any intervention, showed that this type of exercise is able to reduce HbA1c effectively by approximately 0.5%, in addition to improving response to insulin, decreases lipids levels in the blood, reduces visceral adipose tissue and triglycerides, but without changes in cholesterol (Boulé et al., 2001).
Role of marine polysaccharides in treatment of metabolic disorders
Published in Antonio Trincone, Enzymatic Technologies for Marine Polysaccharides, 2019
Manigandan Venkatesan, Velusamy Arumugam, Rathinam Ayyasamy, Karthik Ramachadran, Subhapradha Namasivayam, Umamaheswari Sundaresan, Archunan Govindaraju, Ramachandran Saravanan
Glycated hemoglobin (HbA1c) requires only a single-point blood draw and is more advantageous because it does not require fasting blood samples and has higher repeatability. HbA1c is an indicator of the average blood glucose concentration over the preceding 3 months and has been proposed as a useful alternative test for screening for type 2 diabetes as it overcomes many of the obstacles associated with the OGTT. Glycated hemoglobin is better than fasting glucose for determining risks of cardiovascular disease and death from any cause. HbA1c should be considered in the clinical setting because of the greater ease and lower cost of measurement (Reddigan et al. 2010; Goldstein et al. 2004). HbA1c has been suggested as being superior to fasting plasma glucose (FPG) for the prediction of vascular disease and death from any cause among nondiabetic subjects (Al-Akour et al. 2011; Kaneko et al. 2011). The latest methods for diagnosis include continuous monitoring of interstitial glucose (CGMS), and more recently proposed methods include seven-point self-monitored blood glucose (SMBG) profiles along with calculation of weekly mean blood glucose (WMG) and glycemic variability (GV) (Lemos Costa et al. 2011). A positive association between obesity and the risk of developing T2D has been consistently observed in many populations. Usual anthropometric parameters used to measure obesity are body mass index (BMI), waist circumference (WC), and waist hip ratio (WHR). The most commonly used criteria to diagnose obesity are National Cholesterol Education Program (NCEP), and ATP III criteria. The American Diabetes Association suggests that pseudomotor function assessing small-fiber status should be included in the diagnostic tests for the detection of neuropathies in diabetes (Figure 15.2) (Ramachandran et al. 2011).
Ambient air pollution exposure association with diabetes prevalence and glycosylated hemoglobin (HbA1c) levels in China. Cross-sectional analysis from the WHO study of AGEing and adult health wave 1
Published in Journal of Environmental Science and Health, Part A, 2020
Mona Elbarbary, Trenton Honda, Geoffrey Morgan, Patrick Kelly, Yuming Guo, Joel Negin
The associations between long-term exposure to ambient air pollution and HbA1c have been poorly investigated in previous epidemiological studies, especially in developing countries. HbA1c is an important clinical measure, providing information on long-term average blood glucose concentrations.[58] In a cross-sectional study in a Chinese population,[48] Liu et al. found an IQR (41.1 µg/m3) increase in PM2.5 to be associated with an 0.08 (95% CI: 0.06, 1.0) higher HbA1c level. It is difficult to compare our results with the ones from this study since HbA1c was presented as an absolute value, rather than a percent increase. A recent large (n = 4121) study in older American adults found that rises in annual averages of PM2.5 and NO2 were associated with significant increases in HbA1c of 1.4% and 2.0%, respectively.[4]
Genetic Folding (GF) Algorithm with Minimal Kernel Operators to Predict Stroke Patients
Published in Applied Artificial Intelligence, 2022
A model In 2018 (Almadani and Alshammari 2018) was developed using the J48 (C4.5), JRip, and MLP algorithms on the stroke dataset. Weka Software was utilized to develop all data mining algorithms. CKMB was placed first on the critical laboratory test results for stroke detection, followed by lymph auto, eGFR, and HbA1C. The CKMB test is used to identify whether an increase in creatine kinase is due to cardiac or skeletal muscle damage. It determines the number of white blood cells in the blood to rule out immune system problems. The glomerular filtration rate (eGFR) tests and evaluates renal function. Finally, the HbA1C test determines the average blood glucose level over three months.
Bio-inspired multifunctional zinc oxide nanoparticles by leaf extract of Andrographis serpilifolia and their enhanced antioxidant, antimicrobial, and antidiabetic activity—a 3-in-1 system
Published in Particulate Science and Technology, 2022
Venkata S. Kotakadi, Susmila Aparna Gaddam, Peddana Kotha, Rajesekhar Allagadda, Appa Rao Ch., Sai Gopal D. V. R.
The beneficial role of zinc in diabetes has been established by supplementation studies in diabetic rats. Several zinc complexes have been synthesized and proven to be effective in rodent models of diabetes. In previous studies, ZnO nanoparticles as novel agents for zinc delivery have been synthesized and assessed for their possible anti-diabetic effects in streptozotocin-induced diabetic rats. Although the potent anti-diabetic activity of ZnO was observed in those studies, the influence of this nanoparticle on oxidative stress parameters was not fully determined. Increased fasting blood glucose levels are the common character of diabetes mellitus due to the deficiency of insulin secretion or its action. In the present study, diabetic rats showed hyperglycemia due to the destruction of pancreatic beta-cells by streptozotocin. Zn plays important role in the structural integrity of insulin its storage and secretion. Oral administration of As-ZnONPs reduced the fasting blood glucose levels in diabetic rats. Insulin promotes protein synthesis in muscle, liver, and adipose tissue. Deficiency of insulin in diabetes mellitus also causes loss of body weight due to muscular proteins being used as energy sources. In our study, decreased body weights in diabetic rats were associated with increased muscle wasting and due loss of tissue proteins. The treatment of As-ZnONPs reduces the loss of body weights in diabetic rats, which indicates that muscle protein degradation is prevented. Reduction of hemoglobin protein content and increased levels of HbA1c in diabetes mellitus is a good diagnostic marker. The present results correlate with a reduction of total Hb and increased levels of HbA1c in diabetic control rats. On the other hand, As-ZnONPs have decreased the levels of HbA1C in diabetic rats due to the decrease in blood glucose levels. Insulin is an anabolic hormone on lipid metabolism, which stimulates cholesterol and fatty acid biosynthesis and inhibits lipolysis. Deficiency of insulin was also associated with abnormal levels of serum lipid profiles or dyslipidemia. Treatment with insulin or oral hypoglycemic agents decreases the serum lipid profile levels in diabetes. The present study on diabetic rats also showed increased serum lipid profiles and treatment with As-ZnONPs nanoparticles reduced the serum lipid profiles in diabetic-treated rats. As-ZnONPs could be involved in insulin secretion, which helps in inhibition of the lipolysis pathway, which leads to further control of diabetics.