BIOMECHANICS OF STEM CELLS
干细胞的生物力学
基本信息
- 批准号:8171902
- 负责人:
- 金额:$ 0.11万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2010
- 资助国家:美国
- 起止时间:2010-08-01 至 2013-07-31
- 项目状态:已结题
- 来源:
- 关键词:Aspirate substanceBiomechanicsBone MarrowCD34 geneCardiacCell LineCellsComputer Retrieval of Information on Scientific Projects DatabaseComputer softwareFundingGoalsGrantInstitutionLicensingMeasuresMechanicsModelingPopulationProcessPropertyRecording of previous eventsResearchResearch PersonnelResourcesRunningSimulateSolidSourceStem cellsStromal CellsSuctionSupercomputingTimeUnited States National Institutes of HealthWorkexperiencenerve stem cellnovel strategiespressureresearch studyresponsesimulation
项目摘要
This subproject is one of many research subprojects utilizing the
resources provided by a Center grant funded by NIH/NCRR. The subproject and
investigator (PI) may have received primary funding from another NIH source,
and thus could be represented in other CRISP entries. The institution listed is
for the Center, which is not necessarily the institution for the investigator.
The aim of this project is to investigate the mechanical properties of stem cells. We shall use a novel approach that combines experiments with FEM simulations to identify mechanical properties of stem cells such as the Young's modulus and ultimate strength. The experiments will involve micropipette aspiration (MPA) of stem cells under an applied suction pressure. Subsequently, the aspiration process will be simulated using the commercial FEM software ABAQUS. We shall try various candidate viscoelastic material models for the stem cells, such as the Maxwell model, Generalized Maxwell model, Kelvin-Voigt model or Standard Linear Solid (SLS) model. The goal is to find the model that best approximates the material response of stem cells (as measured experimentally via MPA), together with a set of optimum values for the model parameters. We shall achieve this by tuning the model used in the FEM simulations until the simulated aspiration history (aspirated volume projection as a function of time) matches that experimentally observed. To compute population means of the model parameters, aspiration experiments will be performed on a number of stem cells corresponding to three cell lines: CD34+ cells (generally used for cardiac therapy), neural stem cells (NSCs) and bone marrow stromal cells (mBMSCs). For each experiment, a large number of FEM simulations need to be performed to fine tune the model and its parameters. Hence the need for supercomputing resources for the successful execution of this project. We propose to use ABAQUS on PSC's Pople for this project, as we have prior experience with ABAQUS and using Pople for CFD and FSI simulations. We shall provide our own ABAQUS license. Furthermore, the parallel execution of ABAQUS can use both threads and MPI tasks, and we shall determine which mode works best on Pople. Thus, we would like to request a startup grant on Pople with 30,000 SUs for this project. This will most likely be insufficient for completing the project and so we intend to apply for a research allocation later. We would also like to request ASTA support for this project, for help in figuring out the most efficient way to run our ABAQUS simulations on Pople.
该副本是利用众多研究子项目之一
由NIH/NCRR资助的中心赠款提供的资源。子弹和
调查员(PI)可能已经从其他NIH来源获得了主要资金,
因此可以在其他清晰的条目中代表。列出的机构是
对于中心,这不一定是调查员的机构。
该项目的目的是研究干细胞的机械性能。我们将使用一种新颖的方法将实验与FEM模拟相结合,以鉴定干细胞的机械性能,例如杨氏模量和最终强度。该实验将涉及在应用吸力压力下干细胞的微目抽吸(MPA)。随后,将使用商业FEM软件Abaqus模拟吸气过程。我们将尝试用于干细胞的各种候选粘弹性材料模型,例如麦克斯韦模型,广义麦克斯韦模型,开尔文 - 沃伊格特模型或标准线性固体(SLS)模型。目的是找到最能近似干细胞材料响应的模型(如通过MPA实验测量),以及一组模型参数的最佳值。我们将通过调整FEM模拟中使用的模型来实现这一目标,直到模拟抽吸历史(吸气体积投影作为时间的函数)匹配实验观察到的匹配。为了计算模型参数的种群平均值,将对对应于三个细胞系的许多干细胞进行抽吸实验:CD34+细胞(通常用于心脏治疗),神经干细胞(NSC)和骨髓基质细胞(MBMSC)。对于每个实验,需要进行大量的FEM模拟,以微调模型及其参数。因此,需要超级计算资源以成功执行该项目。我们建议将Abaqus在PSC的Pople上使用该项目,因为我们先前在Abaqus方面经验并将Pople用于CFD和FSI模拟。我们将提供自己的Abaqus许可证。此外,ABAQUS的并行执行可以同时使用线程和MPI任务,我们将确定哪种模式在Pople上最有效。因此,我们想在此项目上向30,000个SUS上的Pople上启动赠款。这很可能不足以完成该项目,因此我们打算以后申请研究分配。我们还想要求对该项目的ASTA支持,以帮助弄清在Pople上运行Abaqus模拟的最有效方法。
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)
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