Collaborative Research: Decoding and encoding mechanistic relations between structure and function in crack resistance of articular cartilage and cartilage inspired biomaterials.
合作研究:解码和编码关节软骨和软骨启发生物材料的抗裂结构和功能之间的机械关系。
基本信息
- 批准号:1808026
- 负责人:
- 金额:$ 25万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-07-15 至 2022-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Non-Technical SummaryArticular cartilage is a soft tissue which provides a smooth cushion and distributes mechanical load in joints. As a material, articular cartilage is remarkable. It is only a few millimeters thick, can routinely bear up to ten times one's body weight over 100-200 million loading cycles, and still avoids fracturing. The simultaneous strength, fracture resistance (toughness), and longevity of native articular cartilage remains unmatched in synthetic materials. Such properties are desperately needed for tissue engineering, tissue repair, and even soft robotics applications. The molecular mechanism underlying this exceptional toughness, however, is not well understood. This project will obtain an understanding of the underlying principles and mechanisms that lead to the toughness of articular cartilage, and provide criteria, as we do for cracks in airplane wings, for predicting the probability that initially untreated tears in cartilage will fracture further. The PIs will test the hypothesis that cartilage has such terrific properties due to the fact that it is comprised of two interweaving polymer networks, one which provides mechanical rigidity and one that provides dissipation. Moreover, this double network changes in composition with location in the tissue. These ideas will be tested using numerical simulation and comparison with experimental measurements of the tissue mechanical properties. Using this integrated approach, the PIs will elucidate mechanical structure-function relations underlying fracture toughness of articular cartilage (AC) which will lead to better predictions of cartilage mechanics and failure, and guide the design of new bioinspired materials. The project will provide insights into tissue failure, tissue repair therapies, and design principles for soft robotics. PIs will educate and train a new generation of scientists who understand physics, engineering, and biology, organize workshops aimed at teaching communication skills to graduate students, and promote diversity in STEM workforce. Technical SummaryArticular Cartilage (AC) is a soft tissue that covers the ends of bones to distribute mechanical load in joints. AC contains relatively few cells and its network-like extracellular matrix primarily determines its mechanical response. Its strength, toughness, and crack resistance are extremely high compared to synthetic materials, but the molecular mechanism underlying this exceptional toughness is not well understood. Given the heterogeneous, depth dependent, and multi-component structure and composition of AC, existing continuum descriptions are too coarse-grained to fully describe its fracture mechanics. The PIs will address this challenge by approaching cartilage fracture with a new structure function framework that combines rigidity percolation theory and microscale double-network hydrogel models, together with new confocal elastography experiments that can inform and interface with the model development. Using this integrated approach consisting of multi-scale mathematical modeling and state-of-the art experiments, they will test the hypothesis that the toughness of AC arises because (i) the reinforcing network state is in proximity to a mechanical phase transition allowing tunable mechanical response, and (ii) the tissue is a multi-component heterogeneous composite enabling novel response to stress and blunting of cracks. The project will obtain an understanding of the dependence of cracks on structure and composition of cartilage and similar soft tissues, as well as on loading conditions, and provide insights into tissue failure, and tissue repair therapies. More broadly, this new framework will enable novel and concrete predictions on how these structure, composition, and constitutive mechanical properties can be tuned to resist, and blunt cracks in biomimetic and engineered materials. PIs will educate and train a new generation of scientists who understand physics, engineering, and biology, and promote diversity in STEM workforce. Cohen and Bonassar will develop soft-skills curriculum units for graduate students and postdocs based on a recent science communication workshop held at Cornell by the Alan Alda Center for Communicating Science. Das will mentor minority and 1st generation students via RIT's McNair Program.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
非技术概述关节软骨是一种软组织,可提供光滑的缓冲并在关节中分配机械负荷。作为一种材料,关节软骨是引人注目的。它只有几毫米厚,可以在1亿到2亿次的载荷循环中承受10倍于体重的载荷,并且仍然避免断裂。天然关节软骨的同时强度、抗断裂性(韧性)和寿命在合成材料中仍然是无与伦比的。组织工程、组织修复甚至软机器人应用都迫切需要这些特性。然而,这种特殊韧性的分子机制还没有很好地理解。该项目将获得对导致关节软骨韧性的基本原理和机制的理解,并提供标准,就像我们对飞机机翼裂缝所做的那样,用于预测最初未经处理的软骨撕裂进一步断裂的可能性。PI将测试软骨具有如此出色特性的假设,因为它由两个交织的聚合物网络组成,一个提供机械刚度,一个提供耗散。此外,这种双重网络的组成随着组织中的位置而变化。这些想法将使用数值模拟和组织力学性能的实验测量的比较进行测试。使用这种综合方法,PI将阐明关节软骨(AC)断裂韧性的机械结构-功能关系,这将导致更好地预测软骨力学和失效,并指导新的仿生材料的设计。该项目将提供对组织失效,组织修复疗法和软机器人设计原理的见解。PI将教育和培训新一代科学家,他们了解物理学,工程学和生物学,组织旨在向研究生教授沟通技巧的研讨会,并促进STEM劳动力的多样性。技术摘要关节软骨(AC)是一种覆盖骨骼末端的软组织,用于分配关节中的机械载荷。AC含有相对较少的细胞,其网络样细胞外基质主要决定其机械响应。与合成材料相比,其强度、韧性和抗裂性极高,但这种特殊韧性背后的分子机制尚不清楚。考虑到AC的异质性、深度依赖性和多组分结构和组成,现有的连续介质描述过于粗粒度,无法完全描述其断裂力学。PI将通过采用新的结构功能框架来处理软骨骨折来应对这一挑战,该框架结合了刚性渗流理论和微尺度双网络水凝胶模型,以及新的共聚焦弹性成像实验,可以为模型开发提供信息和接口。使用这种由多尺度数学建模和最先进的实验组成的综合方法,他们将测试AC韧性的假设,因为(i)增强网络状态接近机械相变,允许可调的机械响应,以及(ii)组织是一种多组分异质复合材料,能够对应力和裂纹钝化产生新的响应。该项目将了解裂纹对软骨和类似软组织的结构和组成以及载荷条件的依赖性,并提供对组织失效和组织修复治疗的见解。更广泛地说,这个新的框架将使新的和具体的预测,这些结构,组成和本构力学性能可以调整,以抵抗,并在仿生和工程材料钝裂纹。PI将教育和培训新一代科学家,他们了解物理,工程和生物学,并促进STEM劳动力的多样性。科恩和博纳萨尔将根据艾伦·阿尔达传播科学中心最近在康奈尔大学举办的科学传播研讨会,为研究生和博士后开发软技能课程单元。Das将通过RIT的McNair计划指导少数民族和第一代学生。该奖项反映了NSF的法定使命,并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。
项目成果
期刊论文数量(6)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Reentrant rigidity percolation in structurally correlated filamentous networks
结构相关丝状网络中的可重入刚性渗透
- DOI:10.1103/physrevresearch.4.043152
- 发表时间:2022
- 期刊:
- 影响因子:4.2
- 作者:Michel, Jonathan;von Kessel, Gabriel;Jackson, Thomas Wyse;Bonassar, Lawrence J.;Cohen, Itai;Das, Moumita
- 通讯作者:Das, Moumita
Rigidity and fracture of biopolymer double networks
生物聚合物双网络的刚性和断裂
- DOI:10.1039/d1sm00802a
- 发表时间:2022
- 期刊:
- 影响因子:3.4
- 作者:Lwin, Pancy;Sindermann, Andrew;Sutter, Leo;Wyse Jackson, Thomas;Bonassar, Lawrence;Cohen, Itai;Das, Moumita
- 通讯作者:Das, Moumita
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Moumita Das其他文献
A kernel-enriched order-dependent nonparametric spatio-temporal process
核丰富的阶依赖非参数时空过程
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:2.3
- 作者:
Moumita Das;S. Bhattacharya - 通讯作者:
S. Bhattacharya
Compressive stress triggers fibroblasts spreading over cancer cells to generate carcinoma in situ organization
压缩应力触发成纤维细胞在癌细胞上扩散以产生原位癌组织
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:5.9
- 作者:
Fabien Bertillot;Laetitia Andrique;Carlos Ureña Martin;Olivier Zajac;L. de Plater;Michael M Norton;Aurélien Richard;K. Alessandri;Basile G. Gurchenkov;Florian Fage;A. Asnacios;Christophe Lamaze;Moumita Das;J. Maître;Pierre Nassoy;Danijela Matic Vignjevic - 通讯作者:
Danijela Matic Vignjevic
Probing quantum correlations in non-degenerate hyper-Raman process
- DOI:
10.1140/epjp/s13360-025-06161-y - 发表时间:
2025-03-18 - 期刊:
- 影响因子:2.900
- 作者:
Moumita Das;Biswajit Sen;Ankur Sensharma;Kishore Thapliyal;Anirban Pathak - 通讯作者:
Anirban Pathak
Enhancing Speculative Execution With Selective Approximate Computing
通过选择性近似计算增强推测执行
- DOI:
10.1145/3307651 - 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Bernard Nongpoh;Rajarshi Ray;Moumita Das;A. Banerjee - 通讯作者:
A. Banerjee
Contextual Prediction Errors Reorganize Episodic Memories in Time
上下文预测错误及时重组情景记忆
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Fahd Yazin;Moumita Das;A. Banerjee;Dipanjan Roy - 通讯作者:
Dipanjan Roy
Moumita Das的其他文献
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{{ truncateString('Moumita Das', 18)}}的其他基金
Collaborative Research: Biomechanical mechanisms conferring wound resilience in single-celled organisms
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2317443 - 财政年份:2023
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Standard Grant
Collaborative Research: NSF Workshop on Models for Uncovering Rules and Unexpected Phenomena in Biological Systems (MODULUS)
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2232740 - 财政年份:2022
- 资助金额:
$ 25万 - 项目类别:
Standard Grant
Collaborative Research: MODULUS:Decoding the Rules of Phase Separation in Bacterial Chromatin
合作研究:MODULUS:解码细菌染色质相分离规则
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2031179 - 财政年份:2021
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$ 25万 - 项目类别:
Standard Grant
Collaborative Research: DMREF: Living biotic-abiotic materials with temporally programmable actuation
合作研究:DMREF:具有临时可编程驱动的生物-非生物活性材料
- 批准号:
2118449 - 财政年份:2021
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Standard Grant
Collaborative Research: Bottom-up Construction of a Synthetic Neuron and Programmable Neuronal Network
合作研究:合成神经元和可编程神经元网络的自下而上构建
- 批准号:
1935277 - 财政年份:2019
- 资助金额:
$ 25万 - 项目类别:
Standard Grant
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