• Biomolecules & Therapeutics
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• v.30 no.6
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• pp.490-500
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• 2022

Aging is defined as physiological dysfunction of the body and a key risk factor for human diseases. During the aging process, cellular senescence occurs in response to various extrinsic and intrinsic factors such as radiation-induced DNA damage, the activation of oncogenes, and oxidative stress. These senescent cells accumulate in many tissues and exhibit diverse phenotypes, such as resistance to apoptosis, production of senescence-associated secretory phenotype, cellular flattening, and cellular hypertrophy. They also induce abnormal dysfunction of the microenvironment and damage neighboring cells, eventually causing harmful effects in the development of various chronic diseases such as diabetes, cancer, and neurodegenerative diseases. Thus, pharmacological interventions targeting senescent cells, called senotherapeutics, have been extensively studied. These senotherapeutics provide a novel strategy for extending the health span and improving age-related diseases. In this review, we discuss the current progress in understanding the molecular mechanisms of senotherapeutics and provide insights for developing senotherapeutics.

• Journal of Biomedical Engineering Research
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• v.40 no.2
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• pp.62-67
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• 2019

The purpose of this study was to evaluate the performance of deep neural network model in order to determine whether there is a risk factor for coronary artery disease based on the cardiac variation parameter. The study used unidentifiable 297 data to evaluate the performance of the model. Input data consists of heart rate parameters, which are SDNN (standard deviation of the N-N intervals), PSI (physical stress index), TP (total power), VLF (very low frequency), LF (low frequency), HF (high frequency), RMSSD (root mean square of successive difference) APEN (approximate entropy) and SRD (successive R-R interval difference), the age group and sex. Output data are divided into normal and patient groups, and the patient group consists of those diagnosed with diabetes, high blood pressure, and hyperlipidemia among the various risk factors that can cause coronary artery disease. Based on this, a binary classification model was applied using Deep Neural Network of deep learning techniques to classify normal and patient groups efficiently. To evaluate the effectiveness of the model used in this study, Kernel SVM (support vector machine), one of the classification models in machine learning, was compared and evaluated using same data. The results showed that the accuracy of the proposed deep neural network was train set 91.79% and test set 85.56% and the specificity was 87.04% and the sensitivity was 83.33% from the point of diagnosis. These results suggest that deep learning is more efficient when classifying these medical data because the train set accuracy in the deep neural network was 7.73% higher than the comparative model Kernel SVM.

• Tuberculosis and Respiratory Diseases
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• v.59 no.6
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• pp.600-605
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• 2005

Background : Primary multidrug-resistant tuberculosis is defined as Mycobacterium tuberculosis isolates that are resistant to at least isoniazid and rifampin in never-been-treated tuberculosis patients, and this malady is caused by the transmission of a resistant strain from one patient, who is infected with a resistant Mycobacterium tuberculosis strain, to another patient. The prevalence of primary multidrug-resistant tuberculosis could be a good indicator of the performance of tuberculosis control programs in recent years. We conducted a case-control study to identify the risk factors for primary multidrug-resistant tuberculosis. Methods : From January 1, 2001 to, June 30, 2003, by conducting prospective laboratory-based surveillance, we identified 29 hospitalized patients with P-MDRTB and these patients constituted a case group in this study. The controls were represented by all the patients with culture-confirmed drug susceptible tuberculosis who were admitted to National Masan Hospital during the same study period. The odds ratios for the patients with primary multidrug-resistant tuberculosis, as compared with those of the patients with drug susceptible tuberculosis, were calculated for each categorical variable with 95% confidence intervals. Results : Multivariate logistic regression showed that the presence of diabetes mellitus (odds ratio 2.68; 95% confidence interval, 1.05-6.86) was independently associated with having primary multidrug-resistant tuberculosis. Conclusion : This study has shown that diabetes mellitus might be one of the risk factors for primary multidrug-resistant tuberculosis.

• Journal of muscle and joint health
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• v.29 no.1
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• pp.1-10
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• 2022

Purpose: Metabolic syndrome is known as a factor that increases the incidence of chronic diseases, such as diabetes and cardiovascular disease. In particular, the metabolic syndrome among a middle-aged population is rapidly increasing from 15.6% to 31.9%. The purpose of this study was to investigate the effect of muscle strength exercise on the metabolic syndrome in middle aged. Methods: This study was a secondary data analysis using National Health and Nutrition Survey 8th, including 2,739 middle aged people (40~64 years old). We used multivariate logistic regression to identify risk factors associated with metabolic syndrome. Statistical analysis was performed using the SPSS 23.0 program. Results: There were 772 patients in the group with metabolic syndrome and 1,967 patients in the non-metabolic syndrome group. The risk of metabolic syndrome was 1.29 times higher in those who did not do muscle strength exercise than those who did exercise (OR=1.29, 95% CI=1.01~1.66). Conclusion: We have found that muscle strength exercise was effective in lowering the risk of developing metabolic syndrome in middle aged. Thus, it is necessary to develop practical muscle strength exercise and education programs.

• The Journal of Internal Korean Medicine
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• v.28 no.2
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• pp.262-274
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• 2007

Objective : It has been reported that two-repeats ($IL1RN^{\ast}2$) of interleukin-1 receptor antagonist (IL-1Ra) gene is associated with ischemic stroke, and that Ala allele of the common Pro12Ala polymorphism in $PPAR-{\gamma}2$ isoform is associated with reduced risk for type 2 DM and its complications. The aim of the present study is to assess the association of IL-1Ra and $PPAR-{\gamma}2$ Pro12Ala polymorphism with the presence of ischemic stroke in the case of diabetic and non-diabetic patients. Methods : Genomic DNA was obtained from 373 healthy subjects, 157 DM subjects without ischemic stroke (known DM duration ${\ge}10$ years) and 302 ischemic stroke patients (including with DM). IL-1Ra polymorphism was analysed by polymerase chain reaction (PCR), and $PPAR-{\gamma}2$ polymorphism by restriction fragment length polymorphism after PCR. Results : $IL1RN^{\ast}1/IL1RN^{\ast}2$ genotype was associated with significantly increased risk for DM (OR=2.86, P = 0.0008) and ischemic stroke (OR=2.74, P = 0.0016). Pro/Ala genotype was associated with the reduced risk for DM (OR=0.53, P = 0.0491) and ischemic stroke (OR=0.38, P = 0.0039). They were also associated with the reduced risk for ischemic stroke in the DM patients compared with DM without ischemic stroke (OR=0.25, P = 0.0321). Conclusions : $IL1RN^{\ast}2$ allele could be an accelerating factor, not a predictive marker for ischemic stroke in type 2 DM. The Pro/Ala genotype of $PPAR-{\gamma}2$ Pro12Ala polymorphism may be associated with reduced risk for ischemic stroke with type 2 DM. Therefore it could be a useful predictive marker for ischemic stroke in Korean type 2 DM.

• Communications for Statistical Applications and Methods
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• v.25 no.3
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• pp.297-306
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• 2018

Cardiovascular disease (CVD) is the leading cause of death worldwide and has a high mortality rate after onset; therefore, the CVD management requires the development of treatment plans and the prediction of prevalence rates. In our study, age, income, education level, marriage status, diabetes, and obesity were identified as risk factors for CVD. Using these 6 factors, we proposed a nomogram based on a $na{\ddot{i}}ve$ Bayesian classifier model for CVD. The attributes for each factor were assigned point values between -100 and 100 by Bayes' theorem, and the negative or positive attributes for CVD were represented to the values. Additionally, the prevalence rate can be calculated even in cases with some missing attribute values. A receiver operation characteristic (ROC) curve and calibration plot verified the nomogram. Consequently, when the attribute values for these risk factors are known, the prevalence rate for CVD can be predicted using the proposed nomogram based on a $na{\ddot{i}}ve$ Bayesian classifier model.

• Journal of the Korean Society of Radiology
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• v.14 no.4
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• pp.495-502
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• 2020

Kidney stones are a common disease with an annual prevalence of about 30,000 people in Korea, and are deeply related to an increase in chronic kidney disease, high blood pressure, coronary artery disease, metabolic syndrome, type 2 diabetes, hyperlipidemia, and abdominal obesity. Therefore, in this study, 135 examinees who visited a general hospital in Dalseong-gun from May 2019 to June 2020 for a medical examination were examined. The relationship between kidney stones and factors related to obesity and metabolic syndrome were found in abdominal ultrasound. I tried to find out the relevance. As a result of the study, the risk of kidney stones in the abnormal group was increased by 4.255 times compared to the normal group in total cholesterol factor, and the risk of kidney stones in the abnormal group was increased by 2.072 times compared to the normal group in the low-density lipoprotein cholesterol factor. Total cholesterol factor and low-density lipoprotein cholesterol It was found that the factor affects the prevalence of kidney stones and metabolic syndrome. Since the risk of kidney stones is related to total cholesterol and low-density lipoprotein cholesterol factors, active attention should be paid to preventive purposes through health check-ups.

• The Korean Journal of Medicine
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• v.93 no.6
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• pp.501-508
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• 2018

Obesity is a chronic disorder that is a significant risk factor for diabetes, cardiovascular diseases, malignancy, and other chronic diseases. Lifestyle modifications form the basis of most treatments for obesity, but it has become clear that such modifications alone are not enough for many obese patients. When a behavioral approach is insufficient, pharmacological treatment may be recommended. In recent years, the US Food and Drug Administration (FDA) has withdrawn several therapeutic options for obesity due to their side effects, but has approved four novel anti-obesity agents. Until recently, orlistat was the only drug approved for the management of long-term obesity, but the US FDA approved the novel anti-obesity drugs lorcaserin and phentermine/topiramate in 2012, and naltrexone/bupropion and liraglutide in 2014. The present review discusses the different pharmacotherapeutic options for the treatment of obesity.

• Korean Journal of Community Nutrition
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• v.19 no.2
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• pp.176-186
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• 2014

Objectives: Epidemiological studies have suggested that a higher consumption of whole grain foods can significantly reduce the risk of chronic diseases including cardiovascular diseases, type 2 diabetes and obesity. The objective of the current study was to examine associations among the consumption of whole grains and nutrient intakes and biochemical indicators associated with chronic diseases among generally healthy middle-aged Korean women. Methods: Using 24-hour recall data from the 2008-2009 National Health and Nutrition Examination Surveys, whole grain intake (g/day) was calculated for a total of generally healthy 1,953 subjects. The subjects were divided into three groups by the level of whole grain consumption (0 g/day, > 0 and < 20 g/day or ${\geq}20g/day$). Mean values or proportions of various nutrient intakes and metabolic risk factors were compared according to the level of whole grain consumption. All statistical analysis was conducted using SAS software version 9.2. Results: We observed that the overall consumption of whole grains was quite low. Specifically, 58.2% of subjects reported no whole grain consumption on the day of the survey, and the mean whole grain intake was only 15.3 g/day. The whole grain consumption was positively associated with intakes of various macro and micronutrients, namely, plant proteins and fats, dietary fiber, calcium, plant iron, potassium, zinc, vitamin A, ${\beta}$-carotene, thiamin, riboflavin, niacin, vitamin $B_6$ and folic acid. In addition, we found significantly decreasing trends in abdominal obesity and hypertriglyceridemia as whole grain intake levels increase. Conclusions: The study findings suggested the importance of promoting whole grain consumption as an efficient tool for improving various dietary aspects and preventing chronic diseases.

• Nutrition Research and Practice
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• v.2 no.4
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• pp.289-294
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• 2008

Pre-B-cell leukemia transcription factor 1 (PBX1), which is located on chromosome 1q23, was recently reported to be associated with type 2 diabetes mellitus. We examined whether single nucleotide polymorphisms (SNPs) of the PBX1 gene are associated with overweight/obesity in a Korean population. We genotyped 66 SNPs in the PBX1 gene and investigated their association with clinical phenotypes found in 214 overweight/obese subjects and 160 control subjects using the Affymetrix Targeted Genotyping chip array. Seven SNPs (g.+75l86C>T, g.+78350C>A, g.+80646C>T, g.+138004C>T, g.+185219G>A, g.+191272A>C, and g.+265317T>A) were associated with the risk of obesity in three models (codominant, dominant, and recessive) (P=0.007-0.05). Haplotype 1 (CAC) and 3 (TAC) of block 3 and haplotype 2 (GGAAT) of block 10 were also strongly associated with the risk of obesity. In the control group, subjects that had homozygote for the major allele for both g.+185219G>A and g.+191272A>C showed lower high density lipoprotein-cholesterol (HDL-C) level compared to those possessing the minor allele, suggesting that the association between the homozygote for the major allele for both g.+185219G>A and g.+191272A>C and HDL-C is attributable to the increased risk of obesity. This study suggests that the PBX1 gene is a possible risk factor in overweight/obese patients.