Metabolic syndrome (MS) refers to a clustering of specific cardiovascular disease (CVD) risk factors whose underlying pathology is thought to be related to insulin resistance. The risk factors include insulin resistance, obesity, dyslipidemia, and hypertension and it is known to increase the risk for CVD and type II diabetes. Since MS helps to identify individuals at high risk for both CVD and type II diabetes, it has become a major public healthcare issue in many countries. There has been much effort to establish diagnostic criteria for MS, but the current diagnostic criteria of MS have weaknesses, such as binary decision based on diagnostic criteria, equal weight among risk factors, and difficulty in estimating the temporal progress of the risk factors. To resolve these problems, this paper proposes a risk quantification model for MS, which is based on areal similarity degree analysis between weighted radar charts comprising MS diagnostic criteria and examination results of risk factors. The clinical effectiveness of the proposed model is extensively evaluated by using data of a large number of subjects obtained from the third Korea National Health and Nutrition Examination Survey. The evaluation results show that the proposed model can quantify the risk of MS and effectively identify a group of subjects who might be classified into a potential risk group for having MS in the future.

No abstract

BACKGROUND/OBJECTIVESIndirect calorimetry is the gold-standard method for the measurement of resting energy expenditure. However, this method is time consuming, expensive, and requires highly trained personnel. To overcome these limitations, various predictive equations have been developed. The objective of this study was to assess the validity of predictive equations for resting energy expenditure (REE) in Korean non-obese adults.SUBJECTS/METHODSThe present study involved 109 participants (54 men and 55 women) aged between 20 and 64 years. The REE was measured by indirect calorimetry. Nineteen REE equations were evaluated for validity, by comparing predicted and measured REE results. Predictive equation accuracy was assessed by determining percent bias, root mean squared prediction error (RMSE), and percentage of accurate predictions.RESULTSThe measured REE was significantly higher in men than in women (P < 0.001), but the difference was not significant after adjusting for body weight (P > 0.05). The equation developed in this study had an accuracy rate of 71%, a bias of 0%, and an RMSE of 155 kcal/day. Among published equations, the FAOweight equation gave the highest accuracy rate (70%), along with a bias of −4.4% and an RMSE of 184 kcal/day.CONCLUSIONSThe newly developed equation provided the best accuracy in predicting REE for Korean non-obese adults. Among the previously published equations, the FAOweight equation showed the highest overall accuracy. Regardless, at an individual level, the equations could lead to inaccuracies in a considerable number of subjects.

Background:Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is a cytokine that activates apoptosis through death receptors on the cell surface and is regarded as a potential anticancer agent. However, many cancer cells are resistant to TRAIL-induced apoptosis.Objective:The aim is to identify the herbal medicines that could help overcome resistance in TRAIL-resistant lung cancer cells.Materials and Methods;TRAIL-resistant A549 cells and 13 herbal medicines with known apoptosis-related anticancer effects were used in this study: Clematidis Radix, Corydalis Tuber Rhizoma, Paeoniae Radix Rubra, Corni Fructus, Curcumae longae Rhizoma (CLR), Moutan Cortex, Salviae miltiorrhizae Radix, Phellodendri Cortex, Farfarae Flos, Paeoniae Radix Alba, Angelicae gigantis Radix, Coptidis Rhizoma (CR), and Taraxaci Herba. Cytotoxic effects were investigated after a 48-h incubation, using an 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay, to identify the herbal medicines with the most potent synergistic effects with TRAIL.Results:The majority of the 13 medicines exhibited concentration-dependent cytotoxicity against A549 cells. Among them, CR and CLR showed the most potent cytotoxic effects, based on the IC50. We then investigated the use of these two medicines in combination with TRAIL and identified synergistic cytotoxic effects against TRAIL-resistant A549 cells.Conclusion:Synergistic cytotoxic effects of the combination of TRAIL and herbal medicines, in particular, CR and CLR, were confirmed in A549 cells. Therefore, CR and CLR showed potential to be used as candidates to overcome TRAIL resistance. Future studies to identify their underlying mechanism of action are required.SUMMARY Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is an attractive anticancer agent which can induce apoptosis in tumor cells without causing cytotoxicity to normal cellsHowever, resistance to TRAIL is often observed in some tumor cells, including nonsmall cell lung cancers, which may limit its cytotoxic efficacy in cancer treatmentThe combination treatment of TRAIL and herbal medicines, particularly Coptidis Rhizoma (CR) and Curcumae longae Rhizoma (CLR), can induce the synergistic cytotoxic effects against TRAIL-resistant A549 cells, indicating that TRAIL resistance was reduced by combination therapy. Abbreviations used: TRAIL: Tumor necrosis factor-related apoptosis-inducing ligand; CLR: Curcumae longae Rhizoma; CR: Coptidis Rhizoma; NSCLC: non-small cell lung cancer.

The purpose of this study was to assess the physical activity of preschool children using an accelerometer and investigate differences related to epoch length setting during use of the accelerometer. Subjects of the study were 26 children (12 boys and 14 girls) at the age of 5, enrolled in one preschool located in Gangneung. From 9:00 a.m. to 4:00 p.m. (7 hours period), every child wore a total of four accelerometers (ActiGraph GT3X + , USA), including three attached to the left hip (with epoch length set at 5 seconds, 15 seconds, and 30 seconds). For comparison purposes, a forth was attached to the opposite position, with epoch length set at 5 seconds. Data collected using 15s epoch and 30s epoch (single larger epoch) were compared with those obtained after reintegration of 5s to 15s epoch, 5s to 30s epoch, and 15s to 30s epoch, respectively (smaller epochs reintegrated). According to the results of this study, there were no significant differences in VM between 30s epoch and 5s to 30s epoch reintegrated and in MVPA (moderate-to-vigorous physical activity), between 15s epoch and 5s to 15s epoch reintegrated. From the Bland-Altman plot, reintegration of 15s to 30s epoch in VM and reintegrations of 15s to 30s epoch and 5s to 15s epoch in MVPA can be recommended for assessing physical activity in preschool children. Further research is needed into the reintegration method while using an accelerometer for assessment of energy expenditure in children.