• Proceedings of the Korean Society of Applied Pharmacology
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• 2003.11a
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• pp.3-4
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• 2003

Body weight is maintained at a relatively constant level over days and months despite variability in food intake and physical activity. To achieve energy homeostasis, the hypothalamus receives information related to energy surplus or shortage from the periphery and controls food intake and energy expenditure. Leptin, an adipocyte derived hormone, is a principal mediator that signals the brain about the stored energy status. Increased leptin signaling in the brain prevents excess energy stores by suppressing food intake and increasing energy expenditure. In addition, insulin and nutrients themselves, such as glucose and free fatty acids, also regulate food intake.

• Journal of Digital Policy
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• v.2 no.4
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• pp.25-32
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• 2023

This paper is a study to develop a deep neural network (DNN) blood glucose prediction model based on heart rate (HR) and heart rate variability (HRV) data measured by PPG-based sensors. MLP deep learning consists of an input layer, a hidden layer, and an output layer with 11 independent variables. The learning results of the blood glucose prediction model are MAE=0.3781, MSE=0.8518, and RMSE=0.9229, and the coefficient of determination (R²) is 0.9994. The study was able to verify the feasibility of glycemic control using non-blood vital signs using PPG-based digital devices. In conclusion, a standardized method of acquiring and interpreting PPG-based vital signs, a large data set for deep learning, and a study to demonstrate the accuracy of the method may provide convenience and an alternative method for blood glucose management in dogs.

• Journal of Digital Convergence
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• v.21 no.3
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• pp.33-39
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• 2023

This study is a performance evaluation of a blood sugar monitoring system that combines a PPG sensor, which is an evaluation device for blood glucose monitoring, and a DNN algorithm when monitoring capillary blood glucose. The study is a researcher-led clinical trial conducted on participants from September 2023 to November 2023. PPG-BGMS compared predicted blood sugar levels for evaluation using 1-minute heart rate and heart rate variability information and the DNN prediction algorithm with capillary blood glucose levels measured with a blood glucose meter of the standard personal blood sugar management system. Of the 100 participants, 50 had type 2 diabetes (T2DM), and the average age was 67 years (range, 28 to 89 years). It was found that 100% of the predicted blood sugar level of PPG-BGMS was distributed in the A+B area of the Clarke error grid and Parker(Consensus) error grid. The MARD value of PPG-BGMS predicted blood glucose is 5.3 ± 4.0%. Consequentially, the non-blood-based PPG-BGMS was found to be non-inferior to the instantaneous blood sugar level of the clinical standard blood-based personal blood glucose measurement system.

• Journal of Preventive Medicine and Public Health
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• v.35 no.3
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• pp.214-220
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• 2002

Objectives : To investigate the relationship of serum uric acid to cardiovascular risk factors in Korean male workers. Methods : We screened 522 male workers at an electrical manufacturing company by a periodic health examination and a questionnaire survey in 2000. We collected data relating to age, smoking status, alcohol drinking status, body mass index (BMI), blood pressure, serum lipid, fasting blood glucose and serum uric acid. The data were analyzed using a variety of methods, including ANOVA, Pearson's correlation, and multivariate regression analyses. to examine the association between uric acid and cardiovascular risk factors with a cross-sectional study design. Results : The concentration of serum uric acid showed positive associations with BMI, total cholesterol, triglyceride, and LDL-cholesterol; it was also significantly correlated to systolic and diastolic blood pressures. Life-style characteristics, such as smoking and alcohol drinking showed no significant association. From the multivariate regression analyses, BMI, total cholesterol and fasting blood glucose levels were found to be independent positive predictors of uric acid; while age, blood pressure and smoking status give no independent contribution explaining the variability of serum uric acid levels. Conclusions : This study demonstrates that serum uric acid level have a significant association with cardiovascular risk factors, such as BMI, total cholesterol and blood glucose in some Korean male workers.

• Korean Journal of Biological Psychiatry
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• v.15 no.3
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• pp.186-193
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• 2008

Objectives : The authors tried to investigate the characteristics of Heart Rate Variability(HRV) among the subjects with metabolic syndrome for testing the possibility of clinical application of HRV in evaluating metabolic syndrome. Methods : We examined the difference of the means of HRV between 122 subjects of metabolic syndrome and 1057 healthy controls using T-test, and the change of means in HRV according to increasing risk factors of metabolic syndrome. Using multiple regression analysis, we examined the association of HRV with the risk factors of metabolic syndrome. Results : The HRV indices including SDNN(Standard Deviation of all normal NN intervals), RMSSD(the square Root of the Mean Squared Differences of successive all normal NN interval), TP(Total Power), LF(Low Freuency), and HF(High Frequency) were significantly lower in the metabolic syndrome group than in the normal control group, and the means of all HRV indices except LF/HF were decreased consistently according to increasing risk factors of metabolic syndrome. The fasting glucose, triglyceride, and waist circumference were dependent factors that contributed significantly to the change of HRV. Conclusion : These findings suggest metabolic syndrome adversely affects cardiac autonomic system and HRV could be a useful method for evaluating metabolic syndrome.

• Journal of Korean Medicine for Obesity Research
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• v.8 no.1
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• pp.81-88
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• 2008

Objectives To investigate the relationship between Heart Rate Variability and menopause among obese middle-aged women in Korea. Subjects and Methods Forty middle-aged women (age 49.05 $\pm$ 2.64 years) with BMI > $23kg/m^2$ were recruited by local advertisement. Blood profiles of estrogen, FSH, LH, glucose, total cholesterol, HDL-cholesterol, and triglyceride were measured. Autonomic Nervous System (ANS) was estimated by short-term spectral analysis of heart rate variability (HRV). Visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were accessed using Computerized Tomography (CT), Bioimpedance Analysis (BIA), and anthropometry. To scrutinize the influence of ANS on obesity-related factors, we divided the subjects into pre- and post-menopausal women. Results The total cholesterol, FSH and LH were significantly higher in post-menopausal obese women group. The estradiol and standard deviation of all normal R-R intervals (SDNN), high-frequency components (HF) of the HRV were significantly lower in postmenopausal obese women group (P<0.05). Adipose tissue distribution and blood profiles were not significantly different between two groups. Conclusion Menopause induced a decrease in SDNN and HF values and increase in total cholesterol level in obese women although the VAT itself was not related with ANS in obese women.

• Journal of Ginseng Research
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• v.44 no.2
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• pp.179-193
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• 2020

Ginseng products on the market show high variability in their composition and overall quality. This becomes a challenge for both consumers and health-care professionals who are in search of high-quality, reliable ginseng products that have a proven safety and efficacy profile. The botanical extract standardization is of crucial importance in this context as it determines the reproducibility of the quality of the product that is essential for the evaluation of effectiveness and safety. This review focuses on the well-characterized and standardized ginseng extract, G115, which represents an excellent example of an herbal drug preparation with constant safety and efficacy within the herbal medicinal products. Over the many decades, extensive preclinical and clinical research has been conducted to evaluate the efficacy and safety of G115. In vitro and in vivo studies of G115 have shown pharmacological effects on physical performance, cognitive function, metabolism, and the immune system. Furthermore, a significant number of G115 clinical studies, most of them double-blind placebo-controlled, have reinforced the findings of preclinical evidence and proved the efficacy of this extract on blood glucose and lipid regulation, chronic obstructive pulmonary disease, energy, physical performance, and immune and cognitive functions. Clinical trials and 50 years of presence on the market are proof of a good safety profile of G115.

• The Korean Journal of Mycology
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• v.27 no.5 s.92
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• pp.328-336
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• 1999

Isozyme comparisons of mycelial extracts from Pleurotus ostreatus were undertaken using isoelectric focusing. Enzyme isozyme patterns were Used to describe the extent of geographical diversity and degree of intraspecific variation in these extracts. A total of 77 bands were resolved from six different enzymes. Cluster analyses were performed using the zymograms for esterase (EST), glucose phosphate isomerase (GPI), leucine aminopeptidase (LAP), malate dehydrogenase(MDH), peroxidase (POX), and phosphoglucomutase (pGM). EST gave multiple banding patterns, while less variability was observed for GPI, MDH, and PGM. Cluster analyses demonstrated that strains of P. ostreatus from geographically different origins are genetically divergent, supporting the idea that there is little or no gene flow between these geographically distant population groups.

• Mycobiology
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• v.33 no.4
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• pp.215-222
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• 2005

Variability in growth and sporulation of five isolates of Arthrobotrys dactyloides was studied on five agar, 6 bran and 5 grain media. Potato dextrose agar (PDA) supported maximum growth of isolate A, C and E, while growth of isolate Band D was significantly lower on this medium. On Czapek's agar and yeast glucose agar media the differentiation in the isolates in relation to growth was poor than PDA. The other two media showed much poorer differentiation. On Czapek's agar medium, sporulation was recorded in isolate B only, whereas other isolates showed rare sporulation. Among the bran media, pea bran agar medium supported maximum growth of all the isolates except isolate B. Gram and rice bran agar media were next best. However, the growth of isolate B on the gram bran agar medium was more or less equal as other isolates. On pigeon pea bran agar medium, isolate E failed to grow while other isolates recorded poor growth. On lentil bran agar medium, only isolate Band D recorded little growth, whereas other isolates failed to grow. All the isolates recorded good sporulation on bran agar media except pigeon pea and lentil bran agar media. The grain agar media supported moderate to very good growth of all the isolates. In general isolate B remained slow growing on these media except gram grain and sorghum grain agar media on which growth of this isolate was comparable to other isolates. Sporulation in general, was good on all the grain agar media. Among different substrates screened, barley grain and pea bran were found superior to others for mass culture of isolate A of A. dactyloides.

• Journal of Korean Medicine Rehabilitation
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• v.24 no.4
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• pp.155-162
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• 2014

Objectives Advanced researches on the relationship between obesity and heart rate variability (HRV), heretofore, focused on characteristics of HRV depending on the state of obesity. However, the previous researches have not quantified predictive power of HRV toward the obesity-related variables, which is rather more meaningful for clinicians who regularly treat obese patients. Hence, we designed a research to investigate whether HRV could predict serum levels of obesity-related metabolites. Methods Ninety obese premenopausal women meeting the inclusion criteria were recruited. The HRV test, blood sampling, and measurement of physical traits were conducted. Multiple regression analysis of the measurement data was carried out, putting obesity-related metabolites (insulin, glucose, triglyceride, hs-CRP, HDL, LDL, total cholesterol) as outcome variables and the others as predictors. To select appropriate predictive variables, the Akaike's Information Criterion (AIC) was applied. Normality and homoskedasticity of residuals for each model were tested to identify if there were any violations of the regression analysis's basic assumption. Logarithm transformation was used for the values of the concentration of metabolites and the HRV. Results The regression model including Total Power (TP) value and BMI had significant predictive power for serum insulin concentration (F(2, 88)=835.7, p<0.001, $R^2=0.95$). The regression coefficient of ln (TP) was -0.1002. However, it was not sure if the HRV could predict concentrations of other metabolites. Conclusions The results suggest that the Total Power (TP) value of the HRV can predict the level of serum insulin. If the BMI could be assumed as being constant, when the TP value is multiplied by n, the predicted change of insulin could be drawn by multiplying $n^{-0.1002}$. The uncertainty of this model can be assumed as approximately 5%.