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Dietary Polysaccharides in the Amelioration of Gut Microbiome Dysbiosis and Metabolic Diseases. 膳食多糖在改善肠道菌群失调和代谢疾病中的作用。
Pub Date : 2017-01-01 Epub Date: 2017-12-18 DOI: 10.15226/2374-8354/4/2/00140
Shokouh Ahmadi, Rabina Mainali, Ravinder Nagpal, Mahmoud Sheikh-Zeinoddin, Sabihe Soleimanian-Zad, Shaohua Wang, Gagan Deep, Santosh Kumar Mishra, Hariom Yadav

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.

在上个世纪,包括肥胖、糖尿病、心血管疾病、高血压和癌症在内的代谢性疾病的流行已演变成一种全球流行病。由于缺乏有效的预防和治疗策略,这些疾病的发病率不断上升。这就需要开发新的策略,以帮助预防、治疗和/或更好地管理这些疾病。虽然这些代谢疾病的复杂病理生理是发展预防和/或治疗策略的主要障碍之一,但有一些因素是或可以推测比其他因素更有效的目标。近年来,肠道微生物群已成为代谢性疾病的主要影响因素之一,开发肠道微生物群的正调节因子被认为是一个重要的研究方向。来自植物和食物来源的天然不可消化多糖被认为是肠道微生物群的有效调节剂,可以喂养肠道中的某些有益微生物。这使得人们越来越关注从不同植物和食物来源中分离出新的生物活性多糖,并将其作为调节肠道微生物组成的功能成分来改善宿主的健康,包括代谢。因此,多糖作为益生元成分,被推测在控制代谢疾病如肥胖和糖尿病方面具有积极作用。在这篇综述文章中,我们总结了一些最常见的影响代谢健康的植物和食物中的多糖,并讨论了这些多糖为什么以及如何有助于预防或改善代谢疾病,如肥胖、2型糖尿病、高血压和血脂异常。
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引用次数: 43
Cell Therapy and Critical Limb Ischemia: Evidence and Window of Opportunity in Obesity. 细胞治疗和严重肢体缺血:肥胖症的证据和机会之窗。
Pub Date : 2016-01-01 Epub Date: 2016-09-15 DOI: 10.15226/2374-8354/3/1/00121
Sally L Elshaer, Renee E Lorys, A B El-Remessy
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].
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引用次数: 4
Predicted vs. Actual Resting Energy Expenditure and Activity Coefficients: Post-Gastric Bypass, Lean and Obese Women. 预测与实际静息能量消耗和活动系数:胃旁路术后,瘦和肥胖女性。
Pub Date : 2014-01-01 DOI: 10.15226/2374-8354/1/2/00109
F. Ramírez-Marrero, K. Edens, M. Joyner, T. Curry
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.
总能量消耗(TEE)和能量需求通常通过预测静息能量消耗(REE)乘以体力活动(PA)系数的方程来估计,体力活动(PA)系数同时考虑了PA能量消耗和食物的产热效应。基于PA自我报告的PA系数是尚未评估的潜在误差来源。因此,在本研究中,我们比较了:1)Harris-Benedict (HB), Mifflin-St。Jeor (MSJ)和粮食及农业组织/世界卫生组织/联合国大学(FAO/WHO/UNU)用间接量热法测量稀土元素(REE-m)的稀土方程;2) PA系数由PA自我报告与客观评估确定;3)胃旁路术后(GB = 13)、瘦(LE = 7)和肥胖(OB = 12)女性的TEE估计。在参与者仰卧休息30分钟后,在禁食过夜后的早晨测量REE。通过问卷评估自我报告的PA,并使用佩戴5-7天的加速度计客观测量PA。通过食物频率问卷评估营养摄入量。人体测量包括DEXA和腹部CT扫描。符合条件的受试者在研究前≥12个月接受手术,体重减轻≥10kg。所有的参与者年龄都在18-45岁之间,能够进行流动活动,并且没有参加运动训练项目。采用单因素方差分析(One-way ANOVA)检测REE和TEE的差异。REE预测方程的准确性由REE-m值在10%以内的案例和一致性分析确定。REE预测结果与REE-m没有差异,但与HB和MSJ的一致性更好,特别是在GB和LE组。使用HB和MSJ方程,自我报告确定的PA系数与客观评估的PA系数的差异导致TEE高估(约200-300千卡/天)。粮农组织/世卫组织/联合国大学无论采用何种PA评估方法,都高估了所有组的TEE(大约300-900千卡/天)。这些结果表明:1)HB和MSJ方程是GB和LE中REE的良好预测因子,但在OB女性中则不是;2)用于估计TEE的PA系数必须通过客观的PA评估来确定;3)使用PA系数与FAO/WHO/UNU方程进行TEE估计时必须谨慎使用。
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引用次数: 8
Predicted vs. Actual Resting Energy Expenditure and Activity Coefficients: Post-Gastric Bypass, Lean and Obese Women. 预测与实际静息能量消耗和活动系数:胃旁路术后,瘦和肥胖女性。
Farah A Ramirez-Marrero, Kim L Edens, Michael J Joyner, Timothy B Curry

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.

总能量消耗(TEE)和能量需求通常通过预测静息能量消耗(REE)乘以体力活动(PA)系数的方程来估计,体力活动(PA)系数同时考虑了PA能量消耗和食物的产热效应。基于PA自我报告的PA系数是尚未评估的潜在误差来源。因此,在本研究中,我们比较了:1)Harris-Benedict (HB), Mifflin-St。Jeor (MSJ)和粮食及农业组织/世界卫生组织/联合国大学(FAO/WHO/UNU)用间接量热法测量稀土元素(REE-m)的稀土方程;2) PA系数由PA自我报告与客观评估确定;3)胃旁路术后(GB = 13)、瘦(LE = 7)和肥胖(OB = 12)女性的TEE估计。在参与者仰卧休息30分钟后,在禁食过夜后的早晨测量REE。通过问卷评估自我报告的PA,并使用佩戴5-7天的加速度计客观测量PA。通过食物频率问卷评估营养摄入量。人体测量包括DEXA和腹部CT扫描。符合条件的受试者在研究前≥12个月接受手术,体重减轻≥10kg。所有的参与者年龄都在18-45岁之间,能够进行流动活动,并且没有参加运动训练项目。采用单因素方差分析(One-way ANOVA)检测REE和TEE的差异。REE预测方程的准确性由REE-m值在10%以内的案例和一致性分析确定。REE预测结果与REE-m没有差异,但与HB和MSJ的一致性更好,特别是在GB和LE组。使用HB和MSJ方程,自我报告确定的PA系数与客观评估的PA系数的差异导致TEE高估(约200-300千卡/天)。粮农组织/世卫组织/联合国大学无论采用何种PA评估方法,都高估了所有组的TEE(大约300-900千卡/天)。这些结果表明:1)HB和MSJ方程是GB和LE中REE的良好预测因子,但在OB女性中则不是;2)用于估计TEE的PA系数必须通过客观的PA评估来确定;3)使用PA系数与FAO/WHO/UNU方程进行TEE估计时必须谨慎使用。
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引用次数: 0
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