Utilising novel technologies to predict muscle loss and muscle quality

利用新技术预测肌肉损失和肌肉质量

• 批准号: 2399458
• 金额: --
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2399458
• 关键词: Utilising; novel; technologies; predict; muscle

A key hallmark of the natural biology of ageing is a progressive loss of skeletal muscle mass, strength and aerobic capacity, termed 'sarcopenia'. The association between muscle loss (mass and quality) and increased incidence of falls, fractures, metabolic disease and other health complications indicates that the burden of our ageing society on health-care systems will increase dramatically over the upcoming decades. Whilst a degree of sarcopenia appears to be inevitable as we age, its rate of onset is highly modifiable based on environmental factors such as physical activity, nutrition, and inflammation (Wall et al, Ageing Res Rev. 2013;12). Indeed, physical inactivity/unloading has been proposed as a primary factor contributing to the functional decline in older individuals, particularly of the postural muscles of the lower limbs (thigh and calf), resulting in negative effects on gait, walking motor control, and walking economy. Importantly, lower walking economy after disuse can further contribute to the reduced daily activity in the older population (Floreani et al, PLoS One. 2018;13) resulting in a lower quality of life.Mechanistic in vivo human studies investigating muscle loss with physical unloading have generally adopted limb immobilisation or prolonged bed rest models. Such studies have led to clear characterisations of muscle disuse atrophy of the lower limbs of older individuals, particularly the gastrocnemius (De Boer et al. Eur J Appl Physiol. 2008;104), and identified a reduction in skeletal muscle protein synthesis in response to nutrition ("anabolic resistance") as a primary mechanism. However, such studies have failed to identify fully effective countermeasures. For example, calf raise and leg press exercises 2-3 times per week had a minimal effect on the 50% decline in plantar flexion function, architecture (Reeves et al, J Gravit Physiol. 2002;9) and tendon stiffness (Reeves et al. J Appl Physiol. 2005;98), during 90 days bed rest. Moreover, while such models of physical unloading provide a controlled model for isolating disuse per se in humans, it ignores other key drivers of muscle atrophy inherent to ageing, such as inflammation and inadequate nutrition. This PhD will focus on the mechanisms, progression, and prevention of sarcopenia by addressing the following objectives:1. Understand the causes of muscle atrophy using a unique 'ocean rowing' model system that integrates undernutrition, physical inactivity, and inflammation.2. Improve interventions to mitigate muscle loss into old age, such as nutrition and exercise programmes.3. Support rehabilitation by implementing these interventions through the development of predictive technologies using wearable devices and apps.4. Ensure interventions are effective at improving healthcare by being intuitive, low cost and minimally intrusive.The proposed research aligns with the UKRI Healthy Ageing Challenge and more specifically with the grand challenges of the EPSRC Developing Future Therapies; Frontiers of Physical Intervention, and Rehabilitation.

自然衰老生物学的一个关键特征是骨骼肌质量、力量和有氧能力的逐渐丧失，称为“肌肉减少症”。肌肉损失（数量和质量）与跌倒、骨折、代谢疾病和其他健康并发症发生率增加之间的关联表明，在未来几十年里，我们老龄化社会对卫生保健系统的负担将急剧增加。虽然随着年龄的增长，一定程度的肌肉减少症似乎是不可避免的，但其发病率是高度可改变的，这取决于环境因素，如身体活动、营养和炎症（Wall等人，Ageing Res Rev. 2013;12）。事实上，缺乏运动/卸载已被认为是导致老年人功能下降的主要因素，特别是下肢（大腿和小腿）的姿势肌肉，从而对步态、步行运动控制和步行经济性产生负面影响。重要的是，废弃后较低的步行经济性会进一步导致老年人日常活动减少（Floreani等人，PLoS One. 2018;13），导致生活质量下降。机械体内人体研究研究肌肉损失与物理卸载通常采用肢体固定或长时间卧床休息模型。这些研究已经明确了老年人下肢肌肉失用性萎缩的特征，特别是腓肠肌（De Boer等）。应用物理学报；2008；104)，并确定了骨骼肌蛋白质合成的减少是对营养的反应（“合成代谢抵抗”）的主要机制。然而，这些研究未能确定充分有效的对策。例如，每周2-3次小腿抬高和腿部按压练习对足底屈曲功能、结构（Reeves et al. J gravity Physiol. 2002;9）和肌腱刚度（Reeves et al. J . 2002;9）下降50%的影响很小。journal of chengdu electromechanical college; 2005；98)，卧床休息90天。此外，虽然这种物理卸载模型为隔离人类本身的废用提供了一个受控模型，但它忽略了衰老固有的肌肉萎缩的其他关键驱动因素，如炎症和营养不足。本博士将重点研究肌肉减少症的机制、进展和预防，目标如下：使用独特的“海洋划船”模型系统了解肌肉萎缩的原因，该模型系统集成了营养不良，缺乏运动和炎症。2 .改善干预措施，如营养和锻炼计划，以减轻老年肌肉损失。通过使用可穿戴设备和应用程序开发预测技术，实施这些干预措施，以支持康复。确保干预措施通过直观、低成本和最小侵入性来有效改善医疗保健。拟议的研究与UKRI健康老龄化挑战，更具体地说，与EPSRC开发未来疗法的重大挑战保持一致；物理干预和康复的前沿。