Obesity & control therapies : open access最新文献

{"title":"Dietary Polysaccharides in the Amelioration of Gut Microbiome Dysbiosis and Metabolic Diseases.","authors":"Shokouh Ahmadi,&nbsp;Rabina Mainali,&nbsp;Ravinder Nagpal,&nbsp;Mahmoud Sheikh-Zeinoddin,&nbsp;Sabihe Soleimanian-Zad,&nbsp;Shaohua Wang,&nbsp;Gagan Deep,&nbsp;Santosh Kumar Mishra,&nbsp;Hariom Yadav","doi":"10.15226/2374-8354/4/2/00140","DOIUrl":"https://doi.org/10.15226/2374-8354/4/2/00140","url":null,"abstract":"<p><p>The prevalence of metabolic diseases including obesity, diabetes, cardiovascular diseases, hypertension and cancer has evolved into a global epidemic over the last century. The rate of these disorders is continuously rising due to the lack of effective preventative and therapeutic strategies. This warrants for the development of novel strategies that could help in the prevention, treatment and/ or better management of such disorders. Although the complex pathophysiology of these metabolic diseases is one of the major hurdles in the development of preventive and/or therapeutic strategies, there are some factors that are or can speculated to be more effective to target than others. Recently, gut microbiome has emerged as one of the major contributing factors in metabolic diseases, and developing positive modulators of gut microbiota is being considered to be of significant interest. Natural non-digestible polysaccharides from plants and food sources are considered potent modulators of gut microbiome that can feed certain beneficial microbes in the gut. This has led to an increased interest in the isolation of novel bioactive polysaccharides from different plants and food sources and their application as functional components to modulate the gut microbiome composition to improve host's health including metabolism. Therefore, polysaccharides, as prebiotics components, are being speculated to confer positive effects in managing metabolic diseases like obesity and diabetes. In this review article, we summarize some of the most common polysaccharides from plants and food that impact metabolic health and discuss why and how these could be helpful in preventing or ameliorating metabolic diseases such as obesity, type 2 diabetes, hypertension and dyslipidemia.</p>","PeriodicalId":90940,"journal":{"name":"Obesity & control therapies : open access","volume":"4 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6249025/pdf/nihms-991536.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36715724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cell Therapy and Critical Limb Ischemia: Evidence and Window of Opportunity in Obesity.","authors":"Sally L Elshaer,&nbsp;Renee E Lorys,&nbsp;A B El-Remessy","doi":"10.15226/2374-8354/3/1/00121","DOIUrl":"https://doi.org/10.15226/2374-8354/3/1/00121","url":null,"abstract":"Endothelial Cells (ECs) from pre-existing capillaries, followed by their proliferation, migration, and capillary formation [10]. By contrast, arteriogenesis describes the remodeling of existing collateral channels, so that they can deliver more blood flow to the limb [11]. Finally, adult vasculogenesis involves the recruitment of Endothelial Progenitor Cells (EPCs), which migrate from the bone marrow to the area of ischemia and differentiate to form new blood vessels [12].","PeriodicalId":90940,"journal":{"name":"Obesity & control therapies : open access","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5624549/pdf/nihms884746.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35573804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicted vs. Actual Resting Energy Expenditure and Activity Coefficients: Post-Gastric Bypass, Lean and Obese Women.","authors":"F. Ramírez-Marrero, K. Edens, M. Joyner, T. Curry","doi":"10.15226/2374-8354/1/2/00109","DOIUrl":"https://doi.org/10.15226/2374-8354/1/2/00109","url":null,"abstract":"Total Energy Expenditure (TEE) and energy requirements are commonly estimated from equations predicting Resting Energy Expenditure (REE) multiplied by a Physical Activity (PA) coefficient that accounts for both PA energy expenditure and the thermogenic effect of food. PA coefficients based on PA self-reports are a potential source of error that has not been evaluated. Therefore, in this study we compared: 1) the Harris-Benedict (HB), Mifflin-St. Jeor (MSJ), and the Food and Agriculture Organization/World Health Organization/United Nations University (FAO/WHO/UNU) REE equations with REE measured (REE-m) with indirect calorimetry; 2) PA coefficients determined with PA self-reports vs. objectively assessed PA; and 3) TEE estimates in post-Gastric Bypass (GB = 13), lean (LE = 7), and obese (OB = 12) women. REE was measured in the morning after an overnight fast with participants resting supine for 30 min. Self-reported PA was evaluated with a questionnaire and objectively measured with accelerometers worn for 5-7 days. Nutritional intake was evaluated with a food frequency questionnaire. Anthropometry included DEXA, and abdominal CT scans. Eligible GB had surgery ≥ 12 months before the study, and had ≥ 10 kg of body weight loss. All participants were 18-45 years of age, able to engage in ambulatory activities, and not taking part in exercise training programs. One-way ANOVA was used to detect differences in REE and TEE. Accuracy of REE prediction equations were determined by cases within 10% of REE-m, and agreement analyses. REE predictions were not different than REE-m, but agreements were better with HB and MSJ, particularly in the GB and LE groups. Discrepancies in the PA coefficients determined with self-report vs. objectively assessed PA resulted in TEE overestimates (approximately 200-300 Kcal/day) using HB and MSJ equations. FAO/WHO/UNU overestimated TEE in all groups regardless of the PA assessment method (approximately 300-900 kcal/day). These results suggest that: 1) HB and MSJ equations are good predictors of REE among GB and LE, but not among OB women, 2) PA coefficients used to estimate TEE must be determined with objective PA assessment, and 3) TEE estimates using PA coefficients with the FAO/WHO/UNU equation must be used with caution.","PeriodicalId":90940,"journal":{"name":"Obesity & control therapies : open access","volume":"516 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77457936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicted vs. Actual Resting Energy Expenditure and Activity Coefficients: Post-Gastric Bypass, Lean and Obese Women.","authors":"Farah A Ramirez-Marrero,&nbsp;Kim L Edens,&nbsp;Michael J Joyner,&nbsp;Timothy B Curry","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Total Energy Expenditure (TEE) and energy requirements are commonly estimated from equations predicting Resting Energy Expenditure (REE) multiplied by a Physical Activity (PA) coefficient that accounts for both PA energy expenditure and the thermogenic effect of food. PA coefficients based on PA self-reports are a potential source of error that has not been evaluated. Therefore, in this study we compared: 1) the Harris-Benedict (HB), Mifflin-St. Jeor (MSJ), and the Food and Agriculture Organization/World Health Organization/United Nations University (FAO/WHO/UNU) REE equations with REE measured (REE-m) with indirect calorimetry; 2) PA coefficients determined with PA self-reports vs. objectively assessed PA; and 3) TEE estimates in post-Gastric Bypass (GB = 13), lean (LE = 7), and obese (OB = 12) women. REE was measured in the morning after an overnight fast with participants resting supine for 30 min. Self-reported PA was evaluated with a questionnaire and objectively measured with accelerometers worn for 5-7 days. Nutritional intake was evaluated with a food frequency questionnaire. Anthropometry included DEXA, and abdominal CT scans. Eligible GB had surgery ≥ 12 months before the study, and had ≥ 10 kg of body weight loss. All participants were 18-45 years of age, able to engage in ambulatory activities, and not taking part in exercise training programs. One-way ANOVA was used to detect differences in REE and TEE. Accuracy of REE prediction equations were determined by cases within 10% of REE-m, and agreement analyses. REE predictions were not different than REE-m, but agreements were better with HB and MSJ, particularly in the GB and LE groups. Discrepancies in the PA coefficients determined with self-report vs. objectively assessed PA resulted in TEE overestimates (approximately 200-300 Kcal/day) using HB and MSJ equations. FAO/WHO/UNU overestimated TEE in all groups regardless of the PA assessment method (approximately 300-900 kcal/day). These results suggest that: 1) HB and MSJ equations are good predictors of REE among GB and LE, but not among OB women, 2) PA coefficients used to estimate TEE must be determined with objective PA assessment, and 3) TEE estimates using PA coefficients with the FAO/WHO/UNU equation must be used with caution.</p>","PeriodicalId":90940,"journal":{"name":"Obesity & control therapies : open access","volume":"1 2","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4383286/pdf/nihms663261.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33193037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}