Dietary intakes of branched-chain amino acids and plasma lipid profiles among filipino women in Korea: the Filipino Womens Diet and Health Study (FiLWHEL)

Abstract Background The potential role of dietary branched-chain amino acids (BCAA) in metabolic health, including cardiovascular disease and diabetes, is evolving, and it is yet to be understood if dietary BCAA intakes are associated with plasma lipid profiles or dyslipidaemia. This study tested the association of dietary BCAA intakes with plasma lipid profiles and dyslipidaemia among Filipino women in Korea. Methods Energy-adjusted dietary BCAA intakes (isoleucine, leucine, valine, and total BCAA) and fasting blood profiles of triglycerides (TG), total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), and low-density lipoproteincholesterol (LDL-C) were determined in a sample of 423 women enrolled in the Filipino Womens Diet and Health Study (FiLWHEL). The generalized linear model was applied to estimate least-square (LS) means and 95% confidence intervals (CIs) and compare plasma TG, TC, HDL-C, and LDL-C across tertile distribution of energy-adjusted dietary BCAA intakes at P<0.05. Results Mean of energy-adjusted dietary total BCAA intake was 8.3±3.9 g/d. Average plasma lipid profiles were 88.5±47.4 mg/dl for TG, 179.7±34.5 mg/dl for TC, 58.0±13.7 mg/dl for HDL-C, and 104.0±30.5 mg/dl for LDL-C. LS means, and 95% CIs across tertiles of energy-adjusted total BCAA intakes were 89.9 mg/dl, 88.8 mg/dl and 85.8 mg/ dl (P-trend=0.45) for TG, 179.1 mg/dl, 183.6 mg/dl and 176.5 mg/dl (P-trend=0.48) for TC, 57.5 mg/dl, 59.6 mg/dl and 57.1 mg/dl (P-trend=0.75) for HDL-C and 103.6 mg/dl, 106.2 mg/dl and 102.3 mg/dl (P-trend=0.68) for LDL-C. Furthermore, the multivariable-adjusted prevalence ratios and 95% confidence intervals for dyslipidaemia across increasing tertile distribution of energy-adjusted total BCAA intake were; 1.00, 0.67 (0.40, 1.13) and 0.45 (0.16, 1.27; P-trend=0.03) for the first, second and third tertile, respectively. Conclusions Higher dietary intakes of BCAA presented a statistically significant inverse trend with the prevalence of dyslipidaemia among Filipino women in this study and testing these associations in longitudinal studies may be necessary to confirm these findings.This research work was supported by the Brain Pool Program through the National Research Foundation of Korea, funded by the Ministry of Science and ICT (2020H1D3A1A04081265), Hanmi Pharmaceutical Co. Ltd. (No. 201300000001270), Chong Kun Dang Pharm., Seoul, Korea (No. 201600000000225), Handok Inc., Seoul, Korea and the Research Grants from Asian Studies funded by Seoul National University Asia Center (0448 A-2021077). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript

Associations of Dietary Intakes of Total and Specific Types of Fat with Blood Lipid Levels in the Filipino Women’s Diet and Health Study (FiLWHEL)

Background: Limited evidence exists on the association between dietary fat intake and lipid profiles in Southeast Asian populations. Objectives: We aimed to examine the cross-sectional associations of dietary intake of total and specific types of fat with dyslipidemia in Filipino immigrant women in Korea. Methods: We included 406 Filipino women married to Korean in the Filipino Women’s Diet and Health Study (FiLWHEL). Dietary fat intake was assessed using 24-hour recalls. Impaired blood lipid profiles were defined as high total cholesterol (TC) (≥200 mg/dL), high triglyceride (TG) (≥150 mg/dL), high LDL Cholesterol (LDL-C) (≥ 130 mg/dL), or low HDL cholesterol (HDL-C) (<50 mg/dL). The genomic DNA samples were genotyped using DNA chip. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using multivariate logistic regression. Results: Substituting carbohydrates with dietary saturated fat (SFA) intake was associated with increased prevalence of dyslipidemia; ORs (95% CIs) for subsequent tertiles compared to the first tertile were 2.28 (1.19–4.35), and 2.88 (1.29–6.39) (P for trend = 0.02). When we examined individual markers, ORs (95% CIs, P for trend) comparing the third to the first tertile were 3.62 (1.53–8.55, 0.01) for high TC, 1.46 (0.42–5.10, 0.72) for high TG, 4.00 (1.48–10.79, 0.02) for high LDL-C, and 0.69 (0.30–1.59, 0.36) for low HDL-C. When we examined the interaction by LDL-C-related polymorphisms, the association with dyslipidemia was more pronounced among participants with CC alleles than among those with T alleles of rs6102059 (P for interaction = 0.01). Conclusions: High dietary SFA intake was significantly associated with a high prevalence of dyslipidemia in Filipino women in Korea. Further prospective cohort studies are warranted to determine risk factors for CVD in Southeast Asian populations

Comparison of cardiovascular disease risk factors among FiLWHEL (2014–2016), NNS (2013) and KNHANES (2013–2015) women

Objectives This study assessed the CVD risk factors among Filipino women (FW) in Korea and compared them with FW in the Philippines and women in Korea (KW). Methods A cohort of 504 women from the Filipino Women's Health and Diet Study (FiLWHEL) aged 20–57years old were age-matched (1:1 ratio) with women from the 2013 National Nutrition Survey in the Philippines and the 2013–2015 Korean National Health and Nutrition Examination Survey. Anthropometric data, blood pressure (BP), lipid and glucose levels were compared across the four populations by calculating the odds ratio (OR)s and 95% confidence interval (CI)s using conditional logistic regression models. Results Compared to KW, FW in Korea and FW in the Philippines were more than 2 and 3 times higher odds of having obesity for BMI ≥ 30kg/m2 and waist circumference ≥ 88cm, respectively. However, FW in Korea had the highest odds (OR 5.51, 95% CI 3.18–9.56) of having hypertension compared to KW. FW in the Philippines had the highest odds of having dyslipidemia (compared to KW,total cholesterol ≥ 200mg/dL: OR 8.83, 95% CI 5.30–14.71; LDL-C ≥ 130mg/dL: OR 3.25, 95% CI 2.13–4.98; and triglyceride ≥ 150mg/dL: OR 2.59, 95% CI 1.59–4.22), but FW in Korea and KW had similar prevalence of dyslipidemia. Conclusions FW in Korea had higher prevalence of obesity and hypertension, with similar prevalence of dyslipidemia compared to KW in this sample. FW in the Philippines had higher prevalence of dyslipidemia compared to FW in Korea. Further prospective studies are warranted to examine the CVD risk factors among continental and native-born Filipino women.Hanmi Pharmaceutical Co., Ltd., (No. 201300000001270), Chong Kun Dang Pharm, Seoul, Korea, (No. 201600000000225) and Yuhan Corporation supported the study. APO is supported by the Brain Pool Program through the National Research Foundation of Korea, funded by the Ministry of Science and ICT (2020H1D3A1A04081265). The funding agencies played no role in the study design and data collection, data analyses, and interpretations, or in preparing and submitting this manuscript for publication

Comparison of the outcomes between sorafenib and lenvatinib as the first-line systemic treatment for HBV-associated hepatocellular carcinoma: a propensity score matching analysis

In a randomized controlled trial, lenvatinib was non-inferior to sorafenib in overall survival (OS) of patients with unresectable hepatocellular carcinoma (uHCC). This study aimed to compare the effects of sorafenib and lenvatinib as first-line systemic therapy against uHCC with real-world data in chronic hepatitis B patients. This retrospective single-center study involved 132 patients with HBV-related uHCC. Propensity score matching (PSM) was used to balance the baseline characteristics, including age, sex, serum alpha-fetoprotein levels, Child–Pugh class, tumor size, and tumor stage. The primary endpoint was overall survival (OS), and the secondary endpoints included progression-free survival (PFS), time to progression (TTP), and tumor response. After PSM, the final analysis included 44 patients treated with lenvatinib and 88 with sorafenib. The OS (7.0 vs 9.2months, p = 0.070) and PFS (4.6 vs 2.4months, p = 0.134) were comparable between the two drugs. Multivariable analysis showed that lenvatinib and sorafenib were not independent prognostic factors of OS (adjusted hazard ratio = 1.41, 95% confidence interval = 0.96–2.08, p = 0.077) after adjustment for baseline alpha-fetoprotein levels, total bilirubin levels, alanine aminotransferase level, performance status, tumor stage, and tumor size. However, the lenvatinib group had a significantly prolonged TTP (5.2 vs 2.5months, p = 0.018) and a higher objective response rate (18.2% vs 4.5%, p = 0.020) and disease control rate (77.3% vs 47.7%, p = 0.001) than the sorafenib group. Our study demonstrated that lenvatinib had a comparable OS and PFS but longer TTP and better tumor response compared to sorafenib in patients with HBV-related uHCC

Laboratory information management system for COVID-19 non-clinical efficacy trial data

Background : As the number of large-scale studies involving multiple organizations producing data has steadily increased, an integrated system for a common interoperable format is needed. In response to the coronavirus disease 2019 (COVID-19) pandemic, a number of global efforts are underway to develop vaccines and therapeutics. We are therefore observing an explosion in the proliferation of COVID-19 data, and interoperability is highly requested in multiple institutions participating simultaneously in COVID-19 pandemic research. Results : In this study, a laboratory information management system (LIMS) approach has been adopted to systemically manage various COVID-19 non-clinical trial data, including mortality, clinical signs, body weight, body temperature, organ weights, viral titer (viral replication and viral RNA), and multiorgan histopathology, from multiple institutions based on a web interface. The main aim of the implemented system is to integrate, standardize, and organize data collected from laboratories in multiple institutes for COVID-19 non-clinical efficacy testings. Six animal biosafety level 3 institutions proved the feasibility of our system. Substantial benefits were shown by maximizing collaborative high-quality non-clinical research. Conclusions : This LIMS platform can be used for future outbreaks, leading to accelerated medical product development through the systematic management of extensive data from non-clinical animal studies.This research was supported by the National research foundation of Korea(NRF) grant funded by the Korea government(MSIT) (2020M3A9I2109027 and 2021M3H9A1030260)

Synthesis of Pt-CeVO4 nanocomposites and their enhanced photocatalytic hydrogen evolution activity under sunlight

The environmental pollution problem caused by fossil fuels, a nonrecyclable resource, becomes more serious every year. Therefore, the development of technology to produce alternative energy in a carbon–neutral way is urgent. In this regard, solar-powered H2 production from water using particulate photocatalysts is considered the most economical and robust approach to producing carbon–neutral H2 fuels. Using Pt-CeVO4 nanocomposites with controllable amounts of Pt nanoparticles (NPs) on CeVO4 as a photocatalyst, a superior H2 production rate of 220.68 mmol g-1h−1 was achieved, which was five times higher than that of Pt NPs. In the Pt-CeVO4 catalyst, CeVO4 affected the electron density of Pt through upward band bending, which dramatically improved the H2 generation ability. Our research is a competent study that satisfies the dual purpose of 1) achieving maximum reaction efficiency using a small amount of noble metal while providing important insights that 2) proper contact of metal and semiconductor materials can exponentially enhance photocatalytic performance. © 2023 The Korean Society of Industrial and Engineering ChemistryFALS

Interpretable Deep-Learning Approaches for Osteoporosis Risk Screening and Individualized Feature Analysis Using Large Population-Based Data: Model Development and Performance Evaluation

BackgroundOsteoporosis is one of the diseases that requires early screening and detection for its management. Common clinical tools and machine-learning (ML) models for screening osteoporosis have been developed, but they show limitations such as low accuracy. Moreover, these methods are confined to limited risk factors and lack individualized explanation. ObjectiveThe aim of this study was to develop an interpretable deep-learning (DL) model for osteoporosis risk screening with clinical features. Clinical interpretation with individual explanations of feature contributions is provided using an explainable artificial intelligence (XAI) technique. MethodsWe used two separate data sets: the National Health and Nutrition Examination Survey data sets from the United States (NHANES) and South Korea (KNHANES) with 8274 and 8680 respondents, respectively. The study population was classified according to the T-score of bone mineral density at the femoral neck or total femur. A DL model for osteoporosis diagnosis was trained on the data sets and significant risk factors were investigated with local interpretable model-agnostic explanations (LIME). The performance of the DL model was compared with that of ML models and conventional clinical tools. Additionally, contribution ranking of risk factors and individualized explanation of feature contribution were examined. ResultsOur DL model showed area under the curve (AUC) values of 0.851 (95% CI 0.844-0.858) and 0.922 (95% CI 0.916-0.928) for the femoral neck and total femur bone mineral density, respectively, using the NHANES data set. The corresponding AUC values for the KNHANES data set were 0.827 (95% CI 0.821-0.833) and 0.912 (95% CI 0.898-0.927), respectively. Through the LIME method, significant features were induced, and each feature’s integrated contribution and interpretation for individual risk were determined. ConclusionsThe developed DL model significantly outperforms conventional ML models and clinical tools. Our XAI model produces high-ranked features along with the integrated contributions of each feature, which facilitates the interpretation of individual risk. In summary, our interpretable model for osteoporosis risk screening outperformed state-of-the-art methods