AGING AND SKELETAL MUSCLE--NEW BODY COMPOSITION MODELS
衰老与骨骼肌——新的身体成分模型
基本信息
- 批准号:2054906
- 负责人:
- 金额:$ 24.76万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:1995
- 资助国家:美国
- 起止时间:1995-04-17 至 1999-03-31
- 项目状态:已结题
- 来源:
- 关键词:African American adolescence (12-20) adult human (21+) aging biopsy body composition caucasian American creatinine gas chromatography mass spectrometry gender difference genetic markers genetics human subject magnetic resonance imaging mathematical model method development model design /development muscle function nuclear magnetic resonance spectroscopy racial /ethnic difference striated muscles urinalysis
项目摘要
Skeletal muscle is one of the largest components at the tissue-system
level of body composition and is involved in many biological processes.
Weakness and frailty in the elderly, osteoporosis, and the cachexia of
acquired immunodeficiency syndrome are only a few of the conditions in
which muscle plays an important role. Despite the relevance of skeletal
muscle to so many acute and chronic conditions, the methods used to
estimate muscle in vivo remain limited and understudied.
Accumulating evidence strongly suggests that most presently available
methods of measuring muscle mass are inaccurate in general or
systematically in error when applied to selected groups. The sources of
error/bias may include: 1. a failure to account for changes in muscle
composition that occur with aging (e.g., decreasing muscle contents of
potassium and creatine-phosphate, relative expansion of extracellular
fluid, changing fiber-type proportions, and intramuscular adipose tissue
deposition); and 2. inadequate adjustment of models/methods for ethnicity
(e.g., white-black differences in fiber-type proportions and muscle
distribution). A major advance in the study of skeletal muscle in vivo
was the introduction of whole-body computerized tomography (CT) and more
recently magnetic resonance (MR) imaging. Pilot studies from our
laboratory based on CT and other methods demonstrate inaccuracies and
large systematic errors in most of the widely used methods for measuring
muscle mass in vivo (e.g., neutron activation and CT muscle estimates (X
plus/minus SD), 27.5 plus/minus 8.4 kg & 34.4 plus/minus 6.2 kg) differed
by an average of 20.0% in healthy men; and anthropometric arm muscle area
measurements in elderly women failed to detect significant (p<0.05)
reductions in muscle mass.
The overall aim of the proposed research program is twofold: to study,
using state-of-the-art methods (e.g., MR imaging and spectroscopy,
analyses of muscle biopsies, 13C-creatinine kinetics, & genetic markers of
racial admixture) the biology (composition, distribution, and function) of
skeletal muscle across age, gender, and ethnic groups, and to apply this
information to the development of methods that will allow a broad range of
investigators to estimate and appropriately interpret whole-body skeletal
muscle mass in settings that range from epidemiologic field stations to
the research laboratory. The hypotheses will be tested and specific aims
carried out in 240 healthy white and black men and women over the age of
18 yrs.
This research will fill an important gap in body composition methodology
and provide extensive new information on the ethnic-specific changes that
occur in muscle with aging.
骨骼肌是组织系统中最大的组成部分之一
身体成分水平,并参与许多生物过程。
老年人体弱、骨质疏松、恶病质
获得性免疫缺陷综合症只是其中的一小部分
哪块肌肉起着重要作用。 尽管与骨骼相关
肌肉对如此多的急性和慢性疾病的影响,所使用的方法
估计体内的肌肉仍然有限且尚未得到充分研究。
越来越多的证据强烈表明,目前大多数可用的
测量肌肉质量的方法总体上不准确或
当应用于选定的群体时会出现系统性错误。 的来源
错误/偏差可能包括: 1. 未能考虑肌肉的变化
随着衰老而发生的成分(例如,肌肉含量减少
钾和磷酸肌酸,细胞外的相对扩张
液体、改变纤维类型比例和肌内脂肪组织
沉积); 2. 对种族模型/方法的调整不充分
(例如,纤维类型比例和肌肉的白黑差异
分配)。 骨骼肌体内研究的重大进展
全身计算机断层扫描 (CT) 等的引入
最近的磁共振(MR)成像。 我们的试点研究
基于 CT 和其他方法的实验室证明不准确
大多数广泛使用的测量方法存在较大的系统误差
体内肌肉质量(例如,中子激活和 CT 肌肉估计(X
正/负SD),27.5正/负8.4公斤和34.4正/负6.2公斤)不同
健康男性平均减少 20.0%;和人体测量手臂肌肉面积
老年女性的测量未能发现显着性(p<0.05)
肌肉质量减少。
拟议研究计划的总体目标有两个:研究、
使用最先进的方法(例如 MR 成像和光谱学,
肌肉活检、13C-肌酐动力学和遗传标记的分析
种族混合)的生物学(组成、分布和功能)
跨年龄、性别和种族的骨骼肌,并将其应用到
信息的发展将允许广泛的方法
研究人员估计并适当解释全身骨骼
从流行病学现场站到
研究实验室。 将测试假设并确定具体目标
对 240 名年龄超过 10 岁的健康白人和黑人男性和女性进行了研究
18 岁
这项研究将填补身体成分方法学的一个重要空白
并提供有关种族特定变化的广泛新信息
随着衰老发生在肌肉中。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Steven B Heymsfield其他文献
Erratum to: Physiological models of body composition and human obesity
- DOI:
10.1186/1743-7075-6-7 - 发表时间:
2009-02-16 - 期刊:
- 影响因子:4.100
- 作者:
David G Levitt;Steven B Heymsfield;Richard N Pierson;Sue A Shapses;John G Kral - 通讯作者:
John G Kral
Are Lean Body Mass and Fat-Free Mass the Same or Different Body Components? A Critical Perspective
- DOI:
10.1016/j.advnut.2024.100335 - 发表时间:
2024-12-01 - 期刊:
- 影响因子:
- 作者:
Steven B Heymsfield;Jasmine Brown;Sophia Ramirez;Carla M Prado;Grant M Tinsley;Maria Cristina Gonzalez - 通讯作者:
Maria Cristina Gonzalez
Muscle matters: the effects of medically induced weight loss on skeletal muscle
肌肉很重要:医学诱导减重对骨骼肌的影响
- DOI:
10.1016/s2213-8587(24)00272-9 - 发表时间:
2024-11-01 - 期刊:
- 影响因子:41.800
- 作者:
Carla M Prado;Stuart M Phillips;M Cristina Gonzalez;Steven B Heymsfield - 通讯作者:
Steven B Heymsfield
Beyond Traditional Body Composition Metrics: Load-Capacity Indices Emerge as Predictors of Cardiometabolic Outcomes—A Systematic Review and Meta-Analysis
超越传统身体成分指标:负荷能力指数成为心脏代谢结果的预测因子——一项系统综述和荟萃分析
- DOI:
10.1016/j.advnut.2024.100364 - 发表时间:
2025-02-01 - 期刊:
- 影响因子:9.200
- 作者:
Zhongyang Guan;Marianna Minnetti;Steven B Heymsfield;Eleonora Poggiogalle;Carla M Prado;Marc Sim;Blossom CM Stephan;Jonathan CK Wells;Lorenzo M Donini;Mario Siervo - 通讯作者:
Mario Siervo
Steven B Heymsfield的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Steven B Heymsfield', 18)}}的其他基金
MRI Visceral Adipose Tissue Partitioning:Advanced Models
MRI 内脏脂肪组织分区:高级模型
- 批准号:
6720003 - 财政年份:2003
- 资助金额:
$ 24.76万 - 项目类别:
MRI Visceral Adipose Tissue Partitioning:Advanced Models
MRI 内脏脂肪组织分区:高级模型
- 批准号:
6837066 - 财政年份:2003
- 资助金额:
$ 24.76万 - 项目类别:
AGING AND SKELETAL MUSCLE--NEW BODY COMPOSITION MODELS
衰老与骨骼肌——新的身体成分模型
- 批准号:
2054907 - 财政年份:1995
- 资助金额:
$ 24.76万 - 项目类别:
BODY COMPOSITION: METHODS, MODEL & CLINICAL APPLICATION
身体成分:方法、模型
- 批准号:
6517186 - 财政年份:1990
- 资助金额:
$ 24.76万 - 项目类别:
BODY COMPOSITION: METHODS, MODEL & CLINICAL APPLICATION
身体成分:方法、模型
- 批准号:
6576911 - 财政年份:1990
- 资助金额:
$ 24.76万 - 项目类别:
BODY COMPOSITION: METHODS, MODEL & CLINICAL APPLICATION
身体成分:方法、模型
- 批准号:
6796491 - 财政年份:1990
- 资助金额:
$ 24.76万 - 项目类别:
BODY COMPOSITION: METHODS, MODEL & CLINICAL APPLICATION
身体成分:方法、模型
- 批准号:
6700191 - 财政年份:1990
- 资助金额:
$ 24.76万 - 项目类别:
MEDICAL APPLICATIONS--HIGH PRECISION IN BODY COMPOSITION
医疗应用——高精度身体成分
- 批准号:
6176568 - 财政年份:1990
- 资助金额:
$ 24.76万 - 项目类别:
BODY COMPOSITION: METHODS, MODEL & CLINICAL APPLICATION
身体成分:方法、模型
- 批准号:
6796483 - 财政年份:1990
- 资助金额:
$ 24.76万 - 项目类别:














{{item.name}}会员




