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Physical activity brings significant health benefits to middle-aged adults, although the research to date has been focused on late adulthood. This study aims to examine how ageing affects the self-reported and accelerometer-derived measures of physical activity levels in middle-aged adults. We employed the data recorded in the UK Biobank and analysed the physical activity levels of 2,998 participants (1381 men and 1617 women), based on self-completion questionnaire and accelerometry measurement of physical activity. We also assessed the musculoskeletal health of the participants using the dual-energy X-ray absorptiometry (DXA) measurements provided by the UK Biobank. Participants were categorised into three groups according to their age: group I younger middle-aged (40 to 49 years), group II older middle-aged (50 to 59 years), and group III oldest middle-aged (60 to 69 years). Self-reported physical activity level increased with age and was the highest in group III, followed by group II and I (P?<?0.05). On the contrary, physical activity measured by accelerometry decreased significantly with age from group I to III (P?<?0.05), and the same pertained to the measurements of musculoskeletal health (P?<?0.05). It was also shown that middle-aged adults mostly engaged in low and moderate intensity activities. The opposing trends of the self-reported and measured physical activity levels may suggest that middle-aged adults over-report their activity level as they age. They should be aware of the difference between their perceived and actual physical activity levels, and objective measures would be useful to prevent the decline in musculoskeletal health.

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目的 应用可视化方法分析代谢组学在中医药领域的现状及趋势。方法 检索中国知网数据库(CNKI)和Web of Science 核心合集数据库2021年3月15日之前收录的中医药领域代谢组学研究的相关文献,应用CiteSpace软件对纳入的文献进行关键词、作者、研究机构等内容进行可视化分析。结果 共纳入中文文献247篇,英文文献350篇。文献数量在波动中迅速上升。中、英文文献作者合作网络显示,张爱华是中医药领域代谢组学研究发文量最多的作者,并形成了核心研究团队。发文机构显示,中国医学科学院是该领域的重要研究机构,机构间合作紧密。中、英文文献关键词分析显示,研究内容主要集中在核磁共振、代谢标记物、冠心病、质谱技术、代谢通路等相关领域。结论 中医药领域代谢组学研究的热点主要为中医药治疗代谢性疾病的机制研究。研究趋势为卵泡代谢组学研究及中药有效成分的研究。  相似文献   
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Noninvasive imaging of cardiac fibrosis is important for early diagnosis and intervention in chronic heart diseases. Here, we investigated whether noninvasive, contrast agent-free MRI T2-mapping can quantify myocardial fibrosis in preclinical models of aging and pressure overload. Myocardial fibrosis and remodeling were analyzed in two animal models: (i) aging (15-month-old male CF-1 mice vs. young 6- to 8-week-old mice), and (ii) pressure overload (PO; by transverse aortic constriction in 4- to 5-month-old male C57BL/6 mice vs. sham-operated for 14 days). In vivo T2-mapping was performed by acquiring data during the isovolumic and early diastolic phases, with a modified respiratory and ECG-triggered multiecho TurboRARE sequence on a 7-T MRI. Cine MRI provided cardiac morphology and function. A quantitative segmentation method was developed to analyze the in vivo T2-maps of hearts at midventricle, apex, and basal regions. The cardiac fibrosis area was analyzed ex vivo by picro sirius red (PSR) staining. Both aged and pressure-overloaded hearts developed significant myocardial contractile dysfunction, cardiac hypertrophy, and interstitial fibrosis. The aged mice had two phenotypes, fibrotic and mild-fibrotic. Notably, the aged fibrotic subgroup and the PO mice showed a marked decrease in T2 relaxation times (25.3 ± 0.6 in aged vs. 29.9 ± 0.7 ms in young mice, p = 0.002; and 24.3 ± 1.7 in PO vs. 28.7 ± 0.7 ms in shams, p = 0.05). However, no significant difference in T2 was detected between the aged mild-fibrotic subgroup and the young mice. Accordingly, an inverse correlation between myocardial fibrosis percentage (FP) and T2 relaxation time was derived (R2 = 0.98): T2 (ms) = 30.45 – 1.05 × FP. Thus, these results demonstrate a statistical agreement between T2-map–quantified fibrosis and PSR staining in two different clinically relevant animal models. In conclusion, T2-mapping MRI is a promising noninvasive contrast agent-free quantitative technique to characterize myocardial fibrosis.  相似文献   
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人工智能(Artificial Intelligence,AI)的蓬勃兴起为现代社会带来了前所未有的机遇,中医药是中华民族传承千年的文化瑰宝。随着人工智能技术不断在中医药领域的科技创新中崭露头角,二者的融合不断加深,人工智能在中医药领域的发展前景、争议挑战也引发了诸多思考。本文将从人工智能在中医药领域的应用入手,对人工智能辅助中医诊断、智能决策与数据挖掘、健康管理及中草药现代化研究等方面,就近年来国内外研究进展进行总结与分析,以期为AI视域下实现中医药现代化、智能化赋能。  相似文献   
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