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      A Novel Approach Based on Metabolomics Coupled With Intestinal Flora Analysis and Network Pharmacology to Explain the Mechanisms of Action of Bekhogainsam Decoction in the Improvement of Symptoms of Streptozotocin-Induced Diabetic Nephropathy in Mice

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          Abstract

          Bekhogainsam decoction (BHID), a representative prescription for the treatment of diabetes mellitus (DM) and diabetic complications in both traditional Korean and Chinese medicine, was examined for its ability to ameliorate diabetic nephropathy (DN), and its mechanism of action was evaluated by metabolomics, gut microbiota, and network pharmacology. In this study, male specific pathogen-free C57BL/6 mice were intraperitoneally injected with streptozotocin (STZ, 100 mg/kg) once per day for 3 days consecutively, and were then orally administered BHID at 100 and 500 mg/kg, and metformin at 250 mg/kg once per day for 4 weeks. Our results showed that the administration of BHID to mice with STZ-induced DN prevented physiological and serological changes, structural damage, and kidney dysfunction. Based on a metabolomics test with serum, the profoundly altered metabolites in the BHID treatment group were identified. Thirty-six BHID-related proteins and four signaling pathways, including valine, leucine, and isoleucine biosynthesis, nicotinate and nicotinamide metabolism, tryptophan metabolism, and alanine, aspartate, and glutamate metabolism pathways, were explored. Principal coordinates analysis (PCoA) of the gut microbiota revealed that BHID treatment significantly affected the flora composition. In addition, the network pharmacology analysis revealed that BHID acted through phosphatidylinositol-3-kinase/protein kinase B (PI3K/Akt) and MAPK-related protein targets. Our findings on the anti-DN effects of BHID and its mechanism of action, from the perspective of systems biology, have provided scientific evidence to support the clinical treatment of patients with diabetes, and implied that BHID has the potential to prevent the progression of DN.

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          Exercise and Type 2 Diabetes

          Although physical activity (PA) is a key element in the prevention and management of type 2 diabetes, many with this chronic disease do not become or remain regularly active. High-quality studies establishing the importance of exercise and fitness in diabetes were lacking until recently, but it is now well established that participation in regular PA improves blood glucose control and can prevent or delay type 2 diabetes, along with positively impacting lipids, blood pressure, cardiovascular events, mortality, and quality of life. Structured interventions combining PA and modest weight loss have been shown to lower risk of type 2 diabetes by up to 58% in high-risk populations. Most benefits of PA on diabetes management are realized through acute and chronic improvements in insulin action, accomplished with both aerobic and resistance training. The benefits of physical training are discussed, along with recommendations for varying activities, PA-associated blood glucose management, diabetes prevention, gestational diabetes mellitus, and safe and effective practices for PA with diabetes-related complications. Diabetes has become a widespread epidemic, primarily due to increasing prevalence and incidence of type 2 diabetes. According to the Centers for Disease Control and Prevention, in 2007 almost 24 million Americans had diabetes, with one-quarter of those, or six million, undiagnosed (1). Currently, it is estimated that almost 60 million U.S. residents also have prediabetes—a condition in which blood glucose levels are above normal—thus greatly increasing their risk of type 2 diabetes (1). Lifetime risk estimates suggest that one in three Americans born in 2000 or later will develop diabetes, but in high-risk ethnic populations, closer to 50% may develop it (2). Diabetes is a significant cause of premature mortality and morbidity related to cardiovascular disease, blindness, kidney and nerve disease, and amputation (1). Although regular PA may prevent or delay diabetes and its complications (3 –10), the majority of people with type 2 diabetes are not active (11). In this article, the broader term “physical activity” (defined as bodily movement produced by the contraction of skeletal muscle that substantially increases energy expenditure) is used interchangeably with “exercise,” which is defined as a subset of PA done with the intention of developing physical fitness (i.e., cardiovascular, strength, and flexibility training). The intent is to recognize that many types of physical movement may have a positive impact on physical fitness, morbidity, and mortality in individuals with type 2 diabetes. Conclusion Exercise plays a major role in the prevention and control of insulin resistance, prediabetes, gestational diabetes mellitus, type 2 diabetes, and diabetes-related health complications. Both aerobic training and resistance training improve insulin action, at least acutely, and can assist with management of blood glucose levels, lipids, blood pressure, cardiovascular risk, mortality, and quality of life, but exercise must be undertaken regularly to have continued benefits and likely include regular training of varying types. Most people with type 2 diabetes can perform exercise safely, as long as certain precautions are taken. The inclusion of an exercise program or other means of increasing overall PA is critical for optimal health in individuals with type 2 diabetes. Both the American College of Sports Medicine (ACSM) and the American Diabetes Association (ADA) reviewed the relevant, published research and developed the recommendations that are defined in Table 1 and listed in Table 2. The entire position statement can be accessed online at http://care.diabetesjournals.org. Table 1 Evidence categories for ACSM and evidence-grading system for clinical practice recommendations for ADA I. ACSM evidence categories Evidence category Source of evidence Definition A Randomized, controlled trials (overwhelming data) Provides a consistent pattern of findings with substantial studies B Randomized, controlled trials (limited data) Few randomized trials exist, which are small in size, and results are inconsistent C Nonrandomized trials, observational studies Outcomes are from uncontrolled, nonrandomized, and/or observational studies D Panel consensus judgment Panel's expert opinion when the evidence is insufficient to place it in categories A through C II. ADA evidence-grading system for clinical practice recommendations Level of evidence Description A Clear evidence from well-conducted, generalizable, randomized, controlled trials that are adequately powered, including the following: Evidence from a well-conducted multicenter trial Evidence from a meta-analysis that incorporated quality ratings in the analysis Compelling nonexperimental evidence, i.e., the “all-or-none” rule developed by the Centre for Evidence-Based Medicine at Oxford Supportive evidence from well-conducted, randomized, controlled trials that are adequately powered, including the following: Evidence from a well-conducted trial at one or more institutions Evidence from a meta-analysis that incorporated quality ratings in the analysis B Supportive evidence from well-conducted cohort studies, including the following: Evidence from a well-conducted prospective cohort study or registry Evidence from a well-conducted meta-analysis of cohort studies Supportive evidence from a well-conducted case-control study C Supportive evidence from poorly controlled or uncontrolled studies, including the following: Evidence from randomized clinical trials with one or more major or three or more minor methodological flaws that could invalidate the results Evidence from observational studies with high potential for bias (such as case series with comparison to historical controls) Evidence from case series or case reports Conflicting evidence with the weight of evidence supporting the recommendation E Expert consensus or clinical experience Table 2 Summary of ACSM evidence and ADA clinical practice recommendation statements ACSM evidence and ADA clinical practice recommendation statements ACSM evidence category (A, highest; D, lowest)/ ADA level of evidence (A, highest; E, lowest) Acute effects of exercise • PA causes increased glucose uptake into active muscles balanced by hepatic glucose production, with a greater reliance on carbohydrate to fuel muscular activity as intensity increases. A/* • Insulin-stimulated blood glucose uptake into skeletal muscle predominates at rest and is impaired in type 2 diabetes, while muscular contractions stimulate blood glucose transport via a separate, additive mechanism not impaired by insulin resistance or type 2 diabetes. A/* • Although moderate aerobic exercise improves blood glucose and insulin action acutely, the risk of exercise-induced hypoglycemia is minimal without use of exogenous insulin or insulin secretagogues. Transient hyperglycemia can follow intense PA. C/* • The acute effects of resistance exercise in type 2 diabetes have not been reported, but result in lower fasting blood glucose levels for at least 24 h postexercise in individuals with impaired fasting glucose. C/* • A combination of aerobic and resistance exercise training may be more effective in improving blood glucose control than either alone; however, more studies are needed to determine whether total caloric expenditure, exercise duration, or exercise mode is responsible. B/* • Milder forms of exercise (e.g., tai chi, yoga) have shown mixed results. C/* • PA can result in acute improvements in systemic insulin action lasting from 2 to 72 h. A/* Chronic effects of exercise training • Both aerobic and resistance training improve insulin action, blood glucose control, and fat oxidation and storage in muscle. B/* • Resistance exercise enhances skeletal muscle mass. A/* • Blood lipid responses to training are mixed but may result in a small reduction in LDL cholesterol with no change in HDL cholesterol or triglycerides. Combined weight loss and PA may be more effective than aerobic exercise training alone on lipids. C/* • Aerobic training may slightly reduce systolic blood pressure, but reductions in diastolic blood pressure are less common, in individuals with type 2 diabetes. C/* • Observational studies suggest that greater PA and fitness are associated with a lower risk of all-cause and cardiovascular mortality. C/* • Recommended levels of PA may help produce weight loss. However, up to 60 min/day may be required when relying on exercise alone for weight loss. C/* • Individuals with type 2 diabetes engaged in supervised training exhibit greater compliance and blood glucose control than those undertaking exercise training without supervision. B/* • Increased PA and physical fitness can reduce symptoms of depression and improve health-related quality of life in those with type 2 diabetes. B/* PA and prevention of type 2 diabetes • At least 2.5 h/week of moderate to vigorous PA should be undertaken as part of lifestyle changes to prevent type 2 diabetes onset in high-risk adults. A/A PA in prevention and control of gestational diabetes mellitus • Epidemiological studies suggest that higher levels of PA may reduce risk of developing gestational diabetes mellitus during pregnancy. C/* • Randomized controlled trials suggest that moderate exercise may lower maternal blood glucose levels in gestational diabetes mellitus. B/* Preexercise evaluation • Before undertaking exercise more intense than brisk walking, sedentary persons with type 2 diabetes will likely benefit from an evaluation by a physician. Electrocardiogram exercise stress testing for asymptomatic individuals at low risk of coronary artery disease is not recommended but may be indicated for higher risk. C/C Recommended PA participation for persons with type 2 diabetes • Persons with type 2 diabetes should undertake at least 150 min/week of moderate to vigorous aerobic exercise spread out over at least 3 days during the week, with no more than 2 consecutive days between bouts of aerobic activity. B/B • In addition to aerobic training, persons with type 2 diabetes should undertake moderate to vigorous resistance training at least 2–3 days/week. B/B • Supervised and combined aerobic and resistance training may confer additional health benefits, although milder forms of PA (such as yoga) have shown mixed results. Persons with type 2 diabetes are encouraged to increase their total daily unstructured PA. Flexibility training may be included but should not be undertaken in place of other recommended types of PA. B/C Exercise with nonoptimal blood glucose control • Individuals with type 2 diabetes may engage in PA, using caution when exercising with blood glucose levels exceeding 300 mg/dl (16.7 mmol/l) without ketosis, provided they are feeling well and are adequately hydrated. C/E • Persons with type 2 diabetes not using insulin or insulin secretagogues are unlikely to experience hypoglycemia related to PA. Users of insulin and insulin secretagogues are advised to supplement with carbohydrate as needed to prevent hypoglycemia during and after exercise. C/C Medication effects on exercise responses • Medication dosage adjustments to prevent exercise-associated hypoglycemia may be required by individuals using insulin or certain insulin secretagogues. Most other medications prescribed for concomitant health problems do not affect exercise, with the exception of β-blockers, some diuretics, and statins. C/C Exercise with long-term complications of diabetes • Known cardiovascular disease is not an absolute contraindication to exercise. Individuals with angina classified as moderate or high risk should likely begin exercise in a supervised cardiac rehabilitation program. PA is advised for anyone with peripheral artery disease. C/C • Individuals with peripheral neuropathy and without acute ulceration may participate in moderate weight-bearing exercise. Comprehensive foot care including daily inspection of feet and use of proper footwear is recommended for prevention and early detection of sores or ulcers. Moderate walking likely does not increase risk of foot ulcers or re-ulceration with peripheral neuropathy. B/B • Individuals with cardiac autonomic neuropathy should be screened and receive physician approval and possibly an exercise stress test prior to exercise initiation. Exercise intensity is best prescribed using the heart rate reserve method with direct measurement of maximal heart rate. C/C • Individuals with uncontrolled proliferative retinopathy should avoid activities that greatly increase intraocular pressure and hemorrhage risk. D/E • Exercise training increases physical function and quality of life in individuals with kidney disease and may even be undertaken during dialysis sessions. The presence of microabuminuria per se does not necessitate exercise restrictions. C/C Adoption and maintenance of exercise by persons with diabetes • Efforts to promote PA should focus on developing self-efficacy and fostering social support from family, friends, and health care providers. Encouraging mild or moderate PA may be most beneficial to adoption and maintenance of regular PA participation. Lifestyle interventions may have some efficacy in promoting PA behavior. B/B *No recommendation given.
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            Metabolomics enables precision medicine: “A White Paper, Community Perspective”

            Introduction: Background to metabolomics Metabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or “-omics” level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person’s metabolic state provides a close representation of that individual’s overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates. Objectives of White Paper—expected treatment outcomes and metabolomics enabling tool for precision medicine We anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and stratification of patients based on metabolic pathways impacted; (4) reveal biomarkers for drug response phenotypes, providing an effective means to predict variation in a subject’s response to treatment (pharmacometabolomics); (5) define a metabotype for each specific genotype, offering a functional read-out for genetic variants: (6) provide a means to monitor response and recurrence of diseases, such as cancers: (7) describe the molecular landscape in human performance applications and extreme environments. Importantly, sophisticated metabolomic analytical platforms and informatics tools have recently been developed that make it possible to measure thousands of metabolites in blood, other body fluids, and tissues. Such tools also enable more robust analysis of response to treatment. New insights have been gained about mechanisms of diseases, including neuropsychiatric disorders, cardiovascular disease, cancers, diabetes and a range of pathologies. A series of ground breaking studies supported by National Institute of Health (NIH) through the Pharmacometabolomics Research Network and its partnership with the Pharmacogenomics Research Network illustrate how a patient’s metabotype at baseline, prior to treatment, during treatment, and post-treatment, can inform about treatment outcomes and variations in responsiveness to drugs (e.g., statins, antidepressants, antihypertensives and antiplatelet therapies). These studies along with several others also exemplify how metabolomics data can complement and inform genetic data in defining ethnic, sex, and gender basis for variation in responses to treatment, which illustrates how pharmacometabolomics and pharmacogenomics are complementary and powerful tools for precision medicine. Conclusions: Key scientific concepts and recommendations for precision medicine Our metabolomics community believes that inclusion of metabolomics data in precision medicine initiatives is timely and will provide an extremely valuable layer of data that compliments and informs other data obtained by these important initiatives. Our Metabolomics Society, through its “Precision Medicine and Pharmacometabolomics Task Group”, with input from our metabolomics community at large, has developed this White Paper where we discuss the value and approaches for including metabolomics data in large precision medicine initiatives. This White Paper offers recommendations for the selection of state of-the-art metabolomics platforms and approaches that offer the widest biochemical coverage, considers critical sample collection and preservation, as well as standardization of measurements, among other important topics. We anticipate that our metabolomics community will have representation in large precision medicine initiatives to provide input with regard to sample acquisition/preservation, selection of optimal omics technologies, and key issues regarding data collection, interpretation, and dissemination. We strongly recommend the collection and biobanking of samples for precision medicine initiatives that will take into consideration needs for large-scale metabolic phenotyping studies.
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              How Can Synergism of Traditional Medicines Benefit from Network Pharmacology?

              Many prescriptions of traditional medicines (TMs), whose efficacy has been tested in clinical practice, have great therapeutic value and represent an excellent resource for drug discovery. Research into single compounds of TMs, such as artemisinin from Artemisia annua L., has achieved great success; however, it has become evident that a TM prescription (which frequently contains various herbs or other components) has a synergistic effect in effecting a cure or reducing toxicity. Network pharmacology targets biological networks and analyzes the links among drugs, targets, and diseases in those networks. Comprehensive, systematic research into network pharmacology is consistent with the perspective of holisticity, which is a main characteristic of many TMs. By means of network pharmacology, research has demonstrated that many a TM show a synergistic effect by acting at different levels on multiple targets and pathways. This approach effectively bridges the gap between modern medicine and TM, and it greatly facilitates studies into the synergistic actions of TMs. There are different kinds of synergistic effects with TMs, such as synergy among herbs, effective parts, and pure compounds; however, for various reasons, new drug discovery should at present focus on synergy among pure compounds.
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                Author and article information

                Contributors
                Journal
                Front Pharmacol
                Front Pharmacol
                Front. Pharmacol.
                Frontiers in Pharmacology
                Frontiers Media S.A.
                1663-9812
                21 May 2020
                2020
                : 11
                : 633
                Affiliations
                [1] 1Department of Herbology, College of Korean Medicine, Dongguk University , Gyeongju, South Korea
                [2] 2Experimental Teaching Center, College of Chinese Materia Medica and Food Engineering, Shanxi University of Chinese Medicine , Jinzhong, China
                [3] 3Korean Medicine R&D Center, Dongguk University , Gyeongju, South Korea
                Author notes

                Edited by: Wei Zhou, The Affiliated Hospital of Shenzhen University, China

                Reviewed by: Sol Cristians, National Autonomous University of Mexico, Mexico; Hong Zheng, Wenzhou Medical University, China

                *Correspondence: Hyo Won Jung, tenzing2@ 123456hanmail.net ; Yong-Ki Park, yongki@ 123456dongguk.ac.kr

                This article was submitted to Ethnopharmacology, a section of the journal Frontiers in Pharmacology

                Article
                10.3389/fphar.2020.00633
                7253635
                32508632
                acc2b97a-8b93-4975-b70a-258f98331146
                Copyright © 2020 Meng, Ma, Kang, Kang, Jung and Park

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 28 October 2019
                : 21 April 2020
                Page count
                Figures: 11, Tables: 3, Equations: 0, References: 54, Pages: 19, Words: 10325
                Funding
                Funded by: National Research Foundation of Korea 10.13039/501100003725
                Award ID: 2016R1D1A2B01012117 & 2016R1D1A1B04935601
                Categories
                Pharmacology
                Original Research

                Pharmacology & Pharmaceutical medicine
                bekhogainsam decoction,diabetic nephropathy,metabolomics,gut microbiota,network pharmacology

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