Background: Our purpose in this study was to evaluate any deficiency of protein intake for different types of sarcopenia, including osteosarcopenia and sarcopenic obesity and to establish a cut-off value for the relationship between malnutrition, sarcopenia, and osteosarcopenia. Methods: The cross-sectional study was performed using data from the Korea National Health and Nutrition Examination Survey. A total of 4,020 participants (men, 1,698 and women, 2,322) were analyzed in the present study. Sarcopenia is defined according to the criteria for the Asia Working Group for Sarcopenia. To evaluate the adequacy of protein intake, the value obtained by dividing the amount of protein consumed through food by the daily recommended protein amount (50 g/day) of Korean males was defined as the nutrient intake ratio. Results: Total protein (P<0.001 in men, P<0.001 in women) and low dietary intake protein (P<0.001 in men, P=0.046 in women) were significantly lower in the sarcopenia group than in the normal group, and were significantly lower in the osteosarcopenia group than in the normal group for both men and women. The cut-off value of the adjusted weight of protein intake for sarcopenia was 0.58 g/kg/day in men and 0.98 g/kg/day in women. The cut-off value for adjusted weight of protein intake for osteo-sarcopenia was 0.8 g/kg/day in men and 0.5 g/kg/day in women. Conclusions A comprehensive dietary assessment to detect nutritional deficits that predispose one to or aggravate muscle atrophy is important for establishing a treatment plan for patients with malnutrition.

Glutathione (GSH) is a major antioxidant in cells, and plays vital roles in the cellular defense against oxidants and in the regulation of redox signals. In a previous report, we demonstrated that stem cell function is critically affected by heterogeneity and dynamic changes in cellular GSH concentration. Here, we present a detailed protocol for the monitoring of GSH concentration in living stem cells using FreSHtracer, a real-time GSH probe. We describe the steps involved in monitoring GSH concentration in single living stem cells using confocal microscopy and flow cytometry. These methods are simple, rapid, and quantitative, and able to demonstrate intracellular GSH concentration changes in real time. We also describe the application of FreSHtracer to the sorting of stem cells according to their GSH content using flow cytometry. Typically, microscopic or flow cytometric analyses of FreSHtracer and MitoFreSHtracer signals in living stem cells take ~2~3 h, and the fractionation of stem cells into subpopulations on the basis of cellular GSH levels takes 3~4.5 h. This method could be applied to almost every kind of mammalian cell with minor modifications to the protocol described here.
Flow Cytometry ; Fluorescent Dyes ; Glutathione ; Methods ; Microscopy, Confocal ; Oxidants ; Oxidation-Reduction ; Population Characteristics ; Stem Cells

Purpose: Diagnostic biomarkers of pancreatic ductal adenocarcinoma (PDAC) have been used for early detection to reduce its dismal survival rate. However, clinically feasible biomarkers are still rare. Therefore, in this study, we developed an automated multi-marker enzyme-linked immunosorbent assay (ELISA) kit using 3 biomarkers (leucine-rich alpha-2-glycoprotein [LRG1], transthyretin [TTR], and CA 19-9) that were previously discovered and proposed a diagnostic model for PDAC based on this kit for clinical usage. Methods: Individual LRG1, TTR, and CA 19-9 panels were combined into a single automated ELISA panel and tested on 728 plasma samples, including PDAC (n = 381) and normal samples (n = 347). The consistency between individual panels of 3 biomarkers and the automated multi-panel ELISA kit were accessed by correlation. The diagnostic model was developed using logistic regression according to the automated ELISA kit to predict the risk of pancreatic cancer (high-, intermediate-, and low-risk groups). Results: The Pearson correlation coefficient of predicted values between the triple-marker automated ELISA panel and the former individual ELISA was 0.865. The proposed model provided reliable prediction results with a positive predictive value of 92.05%, negative predictive value of 90.69%, specificity of 90.69%, and sensitivity of 92.05%, which all simultaneously exceed 90% cutoff value. Conclusion This diagnostic model based on the triple ELISA kit showed better diagnostic performance than previous markers for PDAC. In the future, it needs external validation to be used in the clinic.

A clinical practice guideline for patients in the dying process in general wards and their families, developed through an evidence-based process, is presented herein. The purpose of this guideline is to enable a peaceful death based on an understanding of suitable management of patients’ physical and mental symptoms, psychological support, appropriate deci-sion-making, family care, and clearly-defined team roles. Although there are limits to the available evidence regarding medical issues in patients facing death, the final recommendations were determined from expert advice and feedback, considering values and preferences related to medical treatment, benefits and harms, and applicability in the real world. This guideline should be applied in a way that takes into account specific health care environments, including the resources of medical staff and differences in the available resources of each institution. This guideline can be used by all medical institutions in South Korea.