Optimisation of Plasma Coatings for Bone-Replacement Scaffolds Using Mesenchymal Stem Cells.
使用间充质干细胞优化骨替代支架的等离子体涂层。
基本信息
- 批准号:1644851
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:英国
- 项目类别:Studentship
- 财政年份:2015
- 资助国家:英国
- 起止时间:2015 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Musculoskeletal disease is a leading cause of morbidity across the world, associated with pain, immobility, deformities and in some cases, death. Disease prevalence increases with age. In the coming years, the incidence of disorders affecting the skeleton will rise, causing huge healthcare and socioeconomic burden. Current treatments are typically restricted to pain management followed by end-stage total joint replacement. Cell-based therapies are an appealing biological option in orthopaedics, as they may provide long-lasting restoration of skeletal tissue function by exploiting the intrinsic capacity of mesenchymal stem cells (MSCs) to differentiate into bone and cartilage, often in association with a biomimetic support material to enable 3D reconstruction.Although many materials have been investigated to enhance bone repair, none have seen as much clinical use as the calcium phosphates, the most prominent being hydroxyapatite (HA). This material has been reported as both osteoconductive (support osteoprogenitors and new bone deposition) and potentially osteoinductive (stimulate differentiation of osteoprogenitors towards bone-forming osteoblasts). This cellular response to HA scaffolds or HA-coated implants has been demonstrated in vitro and in vivo using MSCs and terminally differentiated osteoblasts. MSCs are a multipotent progenitor cell population found in many tissues throughout the body including bone marrow; they can be isolated and induced to differentiate into many different cell types, including osteoblasts.The inherent variability in HA scaffold/coating production leads to large variation in the final material characteristics. This is particularly important as cell responses to these material surfaces have been demonstrated to rely on multiple factors. These include surface topography, (micro)structure and composition, which are in some part determined by initial production process variables (such as time, temperature, feed rate). Whilst recent developments in computational topography and solid free-form fabrication make it possible to generate components with control over gross architecture, allowing patient-specific design, the determination of the optimal conditions for cellular responses (e.g. attachment, proliferation, differentiation) still relies on inefficient, time-consuming and expensive assays commonly using a 'One Factor At a Time' (OFAT) approach. This process does not account for the significant between-factor interactions within the chosen process, nor the influence of these factor variables on the cellular response.The purpose of this study is to implement statistical Design of Experiments (DOE) techniques using multivariate analysis to assess multiple input parameter effects on osteogenic responses of MSCs to HA in parallel experimental runs; therefore avoiding confounding results due to between-factor interactions of traditional OFAT approaches. In this instance the experimental methodology will be implemented around the HA plasma spraying of orthopaedic implant devices, a complex production process known to enhance cellular responses and bone growth, but have a large degree of variation in relation to input parameters that will influence clinical effect.Specifically, we propose a 4-factor DOE screening of HA plasma-coating process input parameters in conjunction with assays of osteogenic capacity. This will allow rapid screening of multiple HA material output parameters and their effects at a cellular level. Leading HA formulations will be taken forward for further analysis of osteogenic induction and mechanism of action. This proposal will rely equally on cross-institutional expertise in materials science (Leeds, DePuy), process engineering, DOE screening (DePuy), MSC biology, cell differentiation and cell-biomaterial interaction (York), making it a truly interdisciplinary approach to expedite optimised biomimetic scaffold development for clinical applications.
肌肉骨骼疾病是世界各地发病的主要原因,与疼痛、不动、畸形以及在某些情况下导致死亡有关。患病率随年龄增长而增加。在未来几年,影响骨骼的疾病的发病率将上升,造成巨大的医疗保健和社会经济负担。目前的治疗通常限于疼痛管理,然后是终末期全关节置换术。基于细胞的治疗是骨科中一种有吸引力的生物学选择,因为它们可以通过利用间充质干细胞(MSC)分化为骨和软骨的内在能力来提供骨骼组织功能的持久恢复,通常与仿生支持材料相结合以实现3D重建。虽然已经研究了许多材料来增强骨修复,没有一种具有磷酸钙那样多的临床应用,最突出的是羟基磷灰石(HA)。据报道,该材料具有骨传导性(支持骨祖细胞和新骨沉积)和潜在的骨诱导性(刺激骨祖细胞向骨形成成骨细胞分化)。这种对HA支架或HA涂层植入物的细胞反应已经在体外和体内使用MSC和终末分化成骨细胞证明。骨髓间充质干细胞是一种多能祖细胞群,存在于包括骨髓在内的全身许多组织中;它们可以被分离并诱导分化为许多不同的细胞类型,包括成骨细胞。HA支架/涂层生产的固有可变性导致最终材料特性的巨大变化。这是特别重要的,因为细胞对这些材料表面的反应已被证明依赖于多种因素。这些包括表面形貌、(微)结构和组成,其在某种程度上由初始生产工艺变量(例如时间、温度、进料速率)决定。虽然最近在计算拓扑学和固体自由形式制造方面的发展使得可以生成对总体结构具有控制的组件,从而允许患者特异性设计,但是细胞反应(例如附着、增殖、分化)的最佳条件的确定仍然依赖于通常使用“一次一个因素”(OFAT)方法的低效、耗时和昂贵的测定。这个过程并不占显着的因素间的相互作用,在所选择的过程中,也没有这些因素变量对细胞respons. The的影响,本研究的目的是实施统计设计的实验(DOE)技术,使用多变量分析,以评估多个输入参数的影响骨髓间充质干细胞成骨反应HA在平行的实验运行;因此避免了由于传统OFAT方法的因素间相互作用而导致的混淆结果。在这种情况下,实验方法将围绕HA等离子喷涂骨科植入物设备,一个复杂的生产过程中,已知的增强细胞反应和骨生长,但有很大程度的变化,输入参数,将影响临床effects.Specifically,我们提出了一个4因素DOE筛选HA等离子涂层工艺输入参数结合成骨能力的测定。这将允许快速筛选多个HA材料输出参数及其在细胞水平上的影响。主要的HA制剂将被用于进一步分析成骨诱导和作用机制。该提案将同样依赖于材料科学(利兹,DePuy),工艺工程,DOE筛选(DePuy),MSC生物学,细胞分化和细胞-生物材料相互作用(约克)的跨机构专业知识,使其成为真正的跨学科方法,以加快优化仿生支架的临床应用开发。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
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专利数量(0)
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其他文献
吉治仁志 他: "トランスジェニックマウスによるTIMP-1の線維化促進機序"最新医学. 55. 1781-1787 (2000)
Hitoshi Yoshiji 等:“转基因小鼠中 TIMP-1 的促纤维化机制”现代医学 55. 1781-1787 (2000)。
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
LiDAR Implementations for Autonomous Vehicle Applications
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
吉治仁志 他: "イラスト医学&サイエンスシリーズ血管の分子医学"羊土社(渋谷正史編). 125 (2000)
Hitoshi Yoshiji 等人:“血管医学与科学系列分子医学图解”Yodosha(涉谷正志编辑)125(2000)。
- DOI:
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Effect of manidipine hydrochloride,a calcium antagonist,on isoproterenol-induced left ventricular hypertrophy: "Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,K.,Teragaki,M.,Iwao,H.and Yoshikawa,J." Jpn Circ J. 62(1). 47-52 (1998)
钙拮抗剂盐酸马尼地平对异丙肾上腺素引起的左心室肥厚的影响:“Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,
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- 影响因子:0
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