• Journal of Nutrition and Health
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• v.52 no.1
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• pp.1-5
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• 2019

Purpose: This review describes the historical changes in nutrition philosophy from a reductionist to a holistic approach during the $20^{th}$ century. Also, the role and efficient use of a holistic approach to precision nutrition are discussed. Results: Over the past century, significant progress has been made in human nutrition research, unraveling fundamental mechanisms of single nutrients on single targets or pathways. This kind of a reductionist approach has helped to save populations from nutrient deficiency diseases and improve associated health outcomes in large parts of the world. However, a new set of nutrition problems, like obesity and diet-related chronic diseases, are growing each year worldwide, increasing the financial burden on the health care system. A linear cause-effect association between single nutrients and a single physiologic effect, is insufficient to solve the complex nutrition-health relationships. Research that involves a more holistic rather than reductionist approach is needed to tackle a new set of nutrition problems. Recent advances in technology, informatics, and statistical methods are enabling an understanding of the diversity of individuals and the complex interactions between foods and human bodies, leading to the concept of "precision nutrition." Conclusion: The emerging goal of precision nutrition is to provide tailored dietary advice for maintaining health and preventing obesity and diet-related chronic diseases. The parts are already being installed. To grab the complexity, reductionism and holism must be used interdependently.

• Journal of Nutrition and Health
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• v.55 no.1
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• pp.1-9
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• 2022

In the past few decades, great progress has been made on understanding the interaction between nutrition and health status. But despite this wealth of knowledge, health problems related to nutrition continue to increase. This leads us to postulate that the continuing trend may result from a lack of consideration for intra-individual biological variation on dietary responses. Precision nutrition utilizes personal information such as age, gender, lifestyle, diet intake, environmental exposure, genetic variants, microbiome, and epigenetics to provide better dietary advices and interventions. Recent technological advances in the artificial intelligence, big data analytics, cloud computing, and machine learning, have made it possible to process data on a scale and in ways that were previously impossible. A big data platform is built by collecting numerous parameters such as meal features, medical metadata, lifestyle variation, genome diversity and microbiome composition. Sophisticated techniques based on machine learning algorithm can be used to integrate and interpret multiple factors and provide dietary guidance at a personalized or stratified level. The development of a suitable machine learning algorithm would make it possible to suggest a personalized diet or functional food based on analysis of intra-individual metabolic variation. This novel precision nutrition might become one of the most exciting and promising approaches of improving health conditions, especially in the context of non-communicable disease prevention.

• Animal Bioscience
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• v.34 no.3_spc
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• pp.354-362
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• 2021

Broiler chickens grow rapidly, and their nutrient requirements change daily. However, broilers are fed three to five diet phases, meaning nutrients are under or oversupplied throughout production. Increasing diet phases improves production efficiency as there is less time in the production cycle that nutrients are in under or over-supply. Nevertheless, the process of administering four or more diets is costly and often impractical. New technologies are now available to blend feed to match the daily nutrient requirements of broilers. Thus, the aim of this review is to evaluate previous studies measuring the impact of increasing feed phases on nutrient utilisation and growth performance, and review recent studies taking this concept to the extreme; precision nutrition - feeding a new diet for each day of the production cycle. This review will also discuss how modern precision feeding technologies have been utilised and the potential that new technologies may bring to the poultry industry. The development of a precision nutrition regime which targets daily requirements by blending dietary components on farm is anticipated to improve the efficiency of production, reduce production cost and therefore improve sustainability of the industry. There is also potential for precision feeding technology along with precision nutrition strategies to deliver a plethora of other management and economic benefits. These include increased fluidity to cope with sudden environmental or market changes, and the ability to alter diets on a farm by farm level in a large, integrated operation. Thus, the future possibilities and practical implications for such technologies to generate a paradigm shift in feed formulation within the poultry industry to meet the rising demand for animal protein is also discussed.

• Journal of Nutrition and Health
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• v.54 no.1
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• pp.1-9
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• 2021

This review describes the risk factors of the nutrition crisis in coronavirus disease 2019 (COVID-19) infections and suggests precision nutrition against long-term psychological and physiological stress. The mandatory quarantine and the social distancing are associated with an interruption of the lifestyle routine, resulting in psychological (i.e., boredom) and physiological stress. The stress with multiple causes and forms induces over-compensation of energy-dense food, such as sugary comfort food, and is defined as "food craving" because carbohydrates positively affect the psychological stability with serotonin secretion. The consumption of foods that promote an immune response against viral infections (vitamins & minerals; Cu, folate, Fe, Se, Zn, and Vit A, B6, B12, C, and D), reduce inflammatory cytokines (w-3 fatty acids, Vit D, fibers, and Mg), contain antioxidants (beta-carotene, Vit E, C, Se, and phenolics), and sleep-inducing proteins (serotonin, melatonin, and milk products) is essential. In addition, a reduced Vit D deficiency in winter due to less time spent outdoors under quarantine has been reported to be associated with viral infections. The case fatality rate of COVID-19 was significantly dependent on age, sex, race, and underlying health condition. To prevent malnutrition and cachexia in elderly people, weight loss and muscle wasting should be monitored and controlled. Inadequate protein intake, sedentary lifestyle, and inflammation are significant risk factors for sarcopenia. Moreover, relatively high intakes of fat or carbohydrate compared to low protein intake result in abdominal obesity, which is defined as "sarcopenic obesity." Keeping the food-safety guidelines of COVID-19, this study recommends the consumption of fresh and healthy foods and avoiding sugar, fat, salt, alcohol, and commercially frozen foods.

• Nutrition Research and Practice
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• v.16 no.2
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• pp.272-283
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• 2022

BACKGROUND/OBJECTIVES: Most child and adolescent food literacy measurement tools focus on nutrition and food safety. However, the importance of aspects related to the food system such as food distribution and food waste and their effects on environmental sustainability is growing. We therefore developed and validated a two-dimensional tool for children (8-12 years old) and adolescents (13-18 years old) that can comprehensively measure food literacy. The association of food literacy with diet quality and self-reported health was assessed. SUBJECTS/METHODS: First, we developed a food literacy conceptual framework that contains food system and literacy dimensions through a literature review, focus group interviews, and expert review. After a face validity study, we conducted the main survey (n = 200) to validate the questionnaire. Construct validity and reliability were assessed using exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and Cronbach's alpha. RESULTS: As a result of the Delphi study, content validity was confirmed for the remaining 30 items after two items were excluded (content validity ratio = 0.86). Eleven items were excluded from the EFA results, while the CFA results indicated appropriate fit indices for the proposed model (comparative fit index = 0.904, root mean square error of approximation = 0.068). The final food literacy questionnaire consisted of 19 questions and comprised 5 factors: production, distribution, selection, preparation and cooking, and intake. Food literacy was positively associated with diet quality, as assessed by the Nutrition Quotient score, in both children and adolescents and with self-reported health in adolescents.

• Clinical Nutrition Research
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• v.12 no.2
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• pp.138-153
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• 2023

The prevalence of metabolic syndrome (MetS) and its cost are increasing due to lifestyle changes and aging. This study aimed to develop a deep neural network model for prediction and classification of MetS according to nutrient intake and other MetS-related factors. This study included 17,848 individuals aged 40-69 years from the Korea National Health and Nutrition Examination Survey (2013-2018). We set MetS (3-5 risk factors present) as the dependent variable and 52 MetS-related factors and nutrient intake variables as independent variables in a regression analysis. The analysis compared and analyzed model accuracy, precision and recall by conventional logistic regression, machine learning-based logistic regression and deep learning. The accuracy of train data was 81.2089, and the accuracy of test data was 81.1485 in a MetS classification and prediction model developed in this study. These accuracies were higher than those obtained by conventional logistic regression or machine learning-based logistic regression. Precision, recall, and F1-score also showed the high accuracy in the deep learning model. Blood alanine aminotransferase (β = 12.2035) level showed the highest regression coefficient followed by blood aspartate aminotransferase (β = 11.771) level, waist circumference (β = 10.8555), body mass index (β = 10.3842), and blood glycated hemoglobin (β = 10.1802) level. Fats (cholesterol [β = -2.0545] and saturated fatty acid [β = -2.0483]) showed high regression coefficients among nutrient intakes. The deep learning model for classification and prediction on MetS showed a higher accuracy than conventional logistic regression or machine learning-based logistic regression.

• Journal of the East Asian Society of Dietary Life
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• v.14 no.6
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• pp.561-570
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• 2004

This study was conducted to investigate the effect of the nutrition education on the nutrition knowledge, eating behaviour and nutrient intake of the children. Questionnaire and dietary record were executed to 105 children in the 4th and 5th grade in elementary school with nutrition education and 107 in the same grade without nutrition education. The results were as follows; In nutrition aspect, higher acknowledgement and precision level was observed(p<0.001) in the educated group. Higher practice will of nutrition knowledge, lower rate of skipping meal, better appetite were also observed in the educated group. In the aspect of food group intake, meatㆍfishㆍegg, tofu and bean, fruits, milk and milk products intake frequency were higher in the educated group. Most nutrient intake except fat and vitamin B₂ were observed to be higher in the educated group. Therefore, it was concluded that continuous nutrition education was recommended in order to put positive effect on the eating behaviour and nutrient intake of the children.

• Journal of Microbiology and Biotechnology
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• v.33 no.12
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• pp.1552-1562
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• 2023

Soybean (Glycine max) is an important ingredient of cuisines worldwide. While there is a wealth of evidence that soybean could be a good source of macronutrients and phytochemicals with healthpromoting effects, concerns regarding adverse effects have been raised. In this work, we reviewed the current clinical evidence focusing on the benefits and risks of soybean ingredients. In breast, prostate, colorectal, ovarian, and lung cancer, epidemiological studies showed an inverse association between soybean food intake and cancer risks. Soybean intake was inversely correlated with risks of type 2 diabetes mellitus (T2DM), and soy isoflavones ameliorated osteoporosis and hot flashes. Notably, soybean was one of the dietary protein sources that may reduce the risk of breast cancer and T2DM. However, soybean had adverse effects on certain types of drug treatment and caused allergies. In sum, this work provides useful considerations for planning clinical soybean research and selecting dietary protein sources for human health.

• Preventive Nutrition and Food Science
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• v.14 no.3
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• pp.260-264
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• 2009

A high-performance liquid chromatography method was applied to determine the contents of tocopherols in edible oils using a LiChrosorb DIOL HPLC column and hexane fortified with 0.1% acetic acid in an isocratic mode. The validation of the method included tests for linearity, sensitivity, accuracy, precision, and recovery. All calibration curves showed good linear regression ($r^2$>0.9995) within the tested ranges. The established method offered good precision and accuracy with overall intra-day and inter-day variations of 0.94$\sim$4.27 and 1.77$\sim$ 4.88%, respectively. The tocopherol recoveries ranged from 91.44$\sim$108.90%. Subsequently, the method was successfully applied to qualitatively and quantitatively determine the total contents of $\alpha$, $\gamma$, and $\delta$-tocopherols in 12 selected refined edible oils, showing a range of 0.92 to 188.71 mg/100 g.

• Journal of Nutrition and Health
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• v.57 no.1
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• pp.75-87
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• 2024

Purpose: Dietary habits are strongly related to the symptoms of people with irritable bowel syndrome (IBS). Therefore, personalized nutrition management can help reduce symptoms and improve the quality of life of people with IBS. This study assessed the effectiveness of a personalized web-based nutrition management based on the types of food that trigger IBS symptoms. Methods: Sixty Korean adults with IBS according to Rome IV criteria in their 20s and 30s were enrolled in this study. The data from the final 49 patients who completed a three-month personalized nutrition intervention were analyzed. The general information, anthropometry, dietary intake survey, and gut microbiota were examined pre and post-intervention. The gut microbiota analysis included the relative abundance and the Shannon index. The food intake was recorded for two days for personalized nutrition education, followed by three months of personalized nutrition intervention. Statistical analysis was performed using the Wilcoxon signed-rank test in SPSS 26.0, with the significance set to p < 0.05. Results: The relative abundance of the gut microbiota changed after personalized nutrition management, with a significant decrease in the presence of Veillonella (p = 0.048). Furthermore, when the gut microbiota was analyzed according to the type of food that triggers symptoms, the diversity was increased significantly in the high fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAPs) type (p = 0.031) and FODMAPs-containing gluten-type personalized nutrition intervention types (p < 0.001). Conclusions: Gut microbial diversity and gut microbiota distribution changed after using web-based personalized nutrition management. Hence, personalized nutrition management that considers trigger foods may improve IBS symptoms.