Globally,type 2 diabetes mellitus(T2DM)is one of the most common metabolic disorders.T2DM physiopathology is influenced by complex interrelationships between genetic,metabolic and lifestyle factors(including diet),whi...Globally,type 2 diabetes mellitus(T2DM)is one of the most common metabolic disorders.T2DM physiopathology is influenced by complex interrelationships between genetic,metabolic and lifestyle factors(including diet),which differ between populations and geographic regions.In fact,excessive consumptions of high fat/high sugar foods generally increase the risk of developing T2DM,whereas habitual intakes of plant-based healthy diets usually exert a protective effect.Moreover,genomic studies have allowed the characterization of sequence DNA variants across the human genome,some of which may affect gene expression and protein functions relevant for glucose homeostasis.This comprehensive literature review covers the impact of gene-diet interactions on T2DM susceptibility and disease progression,some of which have demonstrated a value as biomarkers of personal responses to certain nutritional interventions.Also,novel genotype-based dietary strategies have been developed for improving T2DM control in comparison to general lifestyle recommendations.Furthermore,progresses in other omics areas(epigenomics,metagenomics,proteomics,and metabolomics)are improving current understanding of genetic insights in T2DM clinical outcomes.Although more investigation is still needed,the analysis of the genetic make-up may help to decipher new paradigms in the pathophysiology of T2DM as well as offer further opportunities to personalize the screening,prevention,diagnosis,management,and prognosis of T2DM through precision nutrition.展开更多
Artificial intelligence, often referred to as AI, is a branch of computer science focused on developing systems that exhibit intelligent behavior. Broadly speaking, AI researchers aim to develop technologies that can ...Artificial intelligence, often referred to as AI, is a branch of computer science focused on developing systems that exhibit intelligent behavior. Broadly speaking, AI researchers aim to develop technologies that can think and act in a way that mimics human cognition and decision-making [1]. The foundations of AI can be traced back to early philosophical inquiries into the nature of intelligence and thinking. However, AI is generally considered to have emerged as a formal field of study in the 1940s and 1950s. Pioneering computer scientists at the time theorized that it might be possible to extend basic computer programming concepts using logic and reasoning to develop machines capable of “thinking” like humans. Over time, the definition and goals of AI have evolved. Some theorists argued for a narrower focus on developing computing systems able to efficiently solve problems, while others aimed for a closer replication of human intelligence. Today, AI encompasses a diverse set of techniques used to enable intelligent behavior in machines. Core disciplines that contribute to modern AI research include computer science, mathematics, statistics, linguistics, psychology and cognitive science, and neuroscience. Significant AI approaches used today involve statistical classification models, machine learning, and natural language processing. Classification methods are widely applicable to problems in various domains like healthcare, such as informing diagnostic or treatment decisions based on patterns in data. Dean and Goldreich, 1998, define ML as an approach through which a computer has to learn a model by itself from the data provided but no specification on the sort of model is provided to the computer. They can then predict values for things that are different from the values used in training the models. NLP looks at two interrelated concerns, the task of training computers to understand human languages and the fact that since natural languages are so complex, they lend themselves very well to serving a number of very useful goals when used by computers.展开更多
Food and nutrition are essential parts for the management of blood glucose of patients with diabetes and other metabolic diseases.The results of recent human clinical studies have shown that the blood glucose levels c...Food and nutrition are essential parts for the management of blood glucose of patients with diabetes and other metabolic diseases.The results of recent human clinical studies have shown that the blood glucose levels change differently in different people in response to the same standardized meals.This phenomenon shows the challenges to find a one-size-fits-all approach to combat diabetes.With the development of technologies,personalized nutrition/precision nutrition has gradually become more practical in order to treat individual diabetes.The aim of this review article is to summarize personalized nutrition’s progress and potential in treating the diabetes epidemic.We have searched PubMed to identify relevant articles and found that personalized nutrition on multiple factors associated with an individual has started to draw attention to scientifi c communities.Two seminal studies have shown that healthy adults show differential responses of postprandial blood glucose levels to the same standardized meals.Human clinical trials have started to integrate sensor technologies such as continuous glucose monitoring and personal data such as genomic sequences and microbiome to provide personalized nutrition advice,and shown promises in intervention and management of type 2 diabetes.It appears that the interplays of diets and genomes,gut microbiome,gut transit time,insulin sensitivity,cultural,social,and economic factors should all be considered to create a personalized treatment for an individual’s chronic metabolic disease.This probably can be achieved through the integration of personalized nutrition and personalized food intervention with the development of technologies and advances in food and nutrition sciences.More research should be anticipated soon.展开更多
文摘Globally,type 2 diabetes mellitus(T2DM)is one of the most common metabolic disorders.T2DM physiopathology is influenced by complex interrelationships between genetic,metabolic and lifestyle factors(including diet),which differ between populations and geographic regions.In fact,excessive consumptions of high fat/high sugar foods generally increase the risk of developing T2DM,whereas habitual intakes of plant-based healthy diets usually exert a protective effect.Moreover,genomic studies have allowed the characterization of sequence DNA variants across the human genome,some of which may affect gene expression and protein functions relevant for glucose homeostasis.This comprehensive literature review covers the impact of gene-diet interactions on T2DM susceptibility and disease progression,some of which have demonstrated a value as biomarkers of personal responses to certain nutritional interventions.Also,novel genotype-based dietary strategies have been developed for improving T2DM control in comparison to general lifestyle recommendations.Furthermore,progresses in other omics areas(epigenomics,metagenomics,proteomics,and metabolomics)are improving current understanding of genetic insights in T2DM clinical outcomes.Although more investigation is still needed,the analysis of the genetic make-up may help to decipher new paradigms in the pathophysiology of T2DM as well as offer further opportunities to personalize the screening,prevention,diagnosis,management,and prognosis of T2DM through precision nutrition.
文摘Artificial intelligence, often referred to as AI, is a branch of computer science focused on developing systems that exhibit intelligent behavior. Broadly speaking, AI researchers aim to develop technologies that can think and act in a way that mimics human cognition and decision-making [1]. The foundations of AI can be traced back to early philosophical inquiries into the nature of intelligence and thinking. However, AI is generally considered to have emerged as a formal field of study in the 1940s and 1950s. Pioneering computer scientists at the time theorized that it might be possible to extend basic computer programming concepts using logic and reasoning to develop machines capable of “thinking” like humans. Over time, the definition and goals of AI have evolved. Some theorists argued for a narrower focus on developing computing systems able to efficiently solve problems, while others aimed for a closer replication of human intelligence. Today, AI encompasses a diverse set of techniques used to enable intelligent behavior in machines. Core disciplines that contribute to modern AI research include computer science, mathematics, statistics, linguistics, psychology and cognitive science, and neuroscience. Significant AI approaches used today involve statistical classification models, machine learning, and natural language processing. Classification methods are widely applicable to problems in various domains like healthcare, such as informing diagnostic or treatment decisions based on patterns in data. Dean and Goldreich, 1998, define ML as an approach through which a computer has to learn a model by itself from the data provided but no specification on the sort of model is provided to the computer. They can then predict values for things that are different from the values used in training the models. NLP looks at two interrelated concerns, the task of training computers to understand human languages and the fact that since natural languages are so complex, they lend themselves very well to serving a number of very useful goals when used by computers.
基金the financial support provided by the National Key Research and Development(R&D)Program of China(2018YFD0900400 to Gen He)Aoshan Talents Cultivation Program supported by Qingdao National Laboratory for Marine Science and Technology(2017ASTCP-OS12 to Gen He)+1 种基金Key R&D Program in Shandong Province(2020ZLYS03 to Kangsen Mai)China Agriculture Research System(CARS-47-G10 to Kangsen Mai).
文摘Food and nutrition are essential parts for the management of blood glucose of patients with diabetes and other metabolic diseases.The results of recent human clinical studies have shown that the blood glucose levels change differently in different people in response to the same standardized meals.This phenomenon shows the challenges to find a one-size-fits-all approach to combat diabetes.With the development of technologies,personalized nutrition/precision nutrition has gradually become more practical in order to treat individual diabetes.The aim of this review article is to summarize personalized nutrition’s progress and potential in treating the diabetes epidemic.We have searched PubMed to identify relevant articles and found that personalized nutrition on multiple factors associated with an individual has started to draw attention to scientifi c communities.Two seminal studies have shown that healthy adults show differential responses of postprandial blood glucose levels to the same standardized meals.Human clinical trials have started to integrate sensor technologies such as continuous glucose monitoring and personal data such as genomic sequences and microbiome to provide personalized nutrition advice,and shown promises in intervention and management of type 2 diabetes.It appears that the interplays of diets and genomes,gut microbiome,gut transit time,insulin sensitivity,cultural,social,and economic factors should all be considered to create a personalized treatment for an individual’s chronic metabolic disease.This probably can be achieved through the integration of personalized nutrition and personalized food intervention with the development of technologies and advances in food and nutrition sciences.More research should be anticipated soon.
