Center for Nanobiology and Predictive Toxicology

纳米生物学和预测毒理学中心

• 批准号: 8464703
• 负责人: Andre Elias Nel
• 金额: $ 105.49万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-24 至 2015-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8464703
• 关键词: Biological Availability; Biology; Biometry; Cells; Cellular Structures; Cellular biology; Computer Simulation; Cytolysis; Data; Dose; Engineering; Fibrosis; Future; Generations; Goals; Health; Image; In Vitro; Inflammation; Inhalation Exposure; Injury; Lead; Libraries; Link; Lung; Lytic; Machine Learning; Mathematics; Membrane; Metals; Methods; Modeling; Molecular; Multivariate Analysis; Mus; Organ; Outcome; Oxidative Stress; Pathway interactions; Performance; Play; Pneumonia; Property; Rattus; Research Project Grants; Risk; Rodent; Role; Science; Signal Pathway; Signal Transduction; Silicon Dioxide; Structure; Tissues; Toxic effect; Toxicology; base; cellular imaging; chemical property; combinatorial; computer science; cytotoxicity; hazard; high throughput screening; in vivo; mathematical model; metal oxide; multidisciplinary; nano; nanobiology; nanomaterials; nanoparticle; physical property; predictive modeling; screening; statistics; Biological Availability; Biology; Biometry; Cells; Cellular Structures; Cellular biology; Computer Simulation; Cytolysis; Data; Dose; Engineering; Fibrosis; Future; Generations; Goals; Health; Image; In Vitro; Inflammation; Inhalation Exposure; Injury; Lead; Libraries; Link; Lung; Lytic; Machine Learning; Mathematics; Membrane; Metals; Methods; Modeling; Molecular; Multivariate Analysis; Mus; Organ; Outcome; Oxidative Stress; Pathway interactions; Performance; Play; Pneumonia; Property; Rattus; Research Project Grants; Risk; Rodent; Role; Science; Signal Pathway; Signal Transduction; Silicon Dioxide; Structure; Tissues; Toxic effect; Toxicology; base; cellular imaging; chemical property; combinatorial; computer science; cytotoxicity; hazard; high throughput screening; in vivo; mathematical model; metal oxide; multidisciplinary; nano; nanobiology; nanomaterials; nanoparticle; physical property; predictive modeling; screening; statistics

DESCRIPTION (provided by applicant): The Center for Nanobiology and Predictive Toxicology has assembled a multidisciplinary team with expertise in nanomaterial science, toxicology, cell biology, high throughput screening, biostatistics, mathematics and computer science with the overall goal of gaining fundamental understanding of how the physical and Chemical properties of carefully selected ENM libraries relate to interactions with cells and cellular structures, including how these bio-physicochemical interactions at the nano-bio interface may lead to pulmonary toxicity. This goal will be executed through the acquisition, synthesis and characterization of compositional and combinatorial ENM libraries that focus on the major physicochemical properties of nominated metal, metal oxide and silica nanoparticles {Scientific Core), hypothesized to play a role in pulmonary toxicity through the generation of oxidative stress, inflammation, signal pathway activation and membrane lysis. These efforts will be assisted by in silico modeling that use heatmaps, mathematical models and machine learning to perform hazard ranking and risk prediction. The major objectives of the Center are: (i) To establish an overarching predictive toxicological paradigm, which is defined as the assessment of in vivo toxic potential of ENM based on in vitro and in silico methods (integrated center effort); (ii) To establish rapid throughput cellular screening and conduct imaging to identify compositional and combinatorial ENM properties that lead to bioavailability and engagement of the injury pathways discussed above (Project 1); (iii) To establish through the performance of instillation and inhalation exposures in the rodent lung how the structure-property relationships linking ENM to in vitro injury mechanisms may be predictive of pulmonary inflammation, fibrosis and cytotoxicity in a dose-dependent fashion (Project 2); (iv) To develop in silico toxicity models that utilize multivariate analysis of the rapid throughput screening and cellular imaging data to show the relationships that can be used to develop "nano-QSARs" for probabilistic risk ranking (Project 3).

描述（由申请人提供）：纳米生物学和预测毒理学中心已经组装了一个具有纳米材料科学，毒理学，细胞生物学，高吞吐量筛查，生物统计学，数学和计算机科学的多学科团队，并与对精心选择的细胞相互作用的整体了解，并将其与化学群体相互作用的整体理解与构建方式相互作用，以使这些型号的整体了解与这些细胞相互作用，并纳米生物生物界面处的生物化学相互作用可能导致肺毒性。该目标将通过对构图和组合ENM库的获取，合成和表征来执行，该库的重点是指定金属，金属氧化物和硅胶粒子的主要物理化学特性（Scientific Core），假设通过氧化应激，氧化压力，信号pation，Signal，Membrance Active和Membrance Active and of肺毒性起作用，从而在肺部毒性中起作用。这些努力将通过使用热图，数学模型和机器学习来执行危险排名和风险预测的计算机建模来协助这些努力。该中心的主要目标是：（i）建立一个总体预测毒理范式，该范式定义为基于体外和计算机方法（综合中心努力）的ENM体内毒性潜力的评估； （ii）建立快速的吞吐量细胞筛选并进行成像，以识别导致上述损伤途径的生物利用度和参与度的组成和组合特性（项目1）； （iii）通过在啮齿动物肺中进行灌注和吸入暴露的性能来建立结构 - 培养基关系如何将ENM与体外损伤机制联系起来可能预测肺部炎症，纤维化和细胞毒性以剂量依赖的方式（项目2）； （iv）在使用快速吞吐量筛选和细胞成像数据的多元分析的硅毒性模型中发展，以显示可用于开发概率风险排名的“纳米QSAR”的关系（项目3）。