Center for High-Throughput Minimally-Invasive Radiation Biodosimetry

该计划代表了一种由非常高通量的实际需求所激励的内聚方法 生物剂量学在各种不同的大规模暴露情况下，预测个人剂量， 对未来伤害的敏感性。一个中心特征仍然是我们关注的3种不同的高通量 方法：全自动细胞遗传学（项目1），基因表达（项目2）和代谢组学（项目 3）。这些在通量、时间到结果、剂量重建、 暴露情景识别和个体放射敏感性预测，最终目标是量化其 在不同的大规模暴露场景中实现最佳综合使用。这些项目有四个共同主题： 1：“超越简单暴露”：走向复杂暴露的高通量生物剂量学：之后 IND将有各种各样的暴露场景，包括非常高的剂量率，中子暴露， 部分身体暴露（全部来自初始即时辐射），以及不同剂量率和低剂量率（从 外部辐射和内部辐射）。我们的目标是1）了解这些不同的暴露场景 调节我们已经开发的预测生物标志物的反应，2）最佳地使用这些 生物标志物来识别/表征个体可能暴露的这些不同暴露情景。 第2章：“超越剂量”：实现光子和中子的高可靠性个性化预测- 诱导的放射敏感性和晚期放射损伤：基因表达和代谢组学各有用途 用于预测晚期放射性肺病的个体化发作，以及用于预测哪些受照射的 动物会死于这种疾病。这项工作将扩展到中子诱导的晚期效应，同时也 评估衰老细胞对于晚期疾病发展和我们的肺部疾病特征的重要性。 3：“超越模型系统”：探索实验产生的光子的应用 体内人体暴露情况下的中子生物标志物：目标是评估体内人体暴露情况。 暴露，但生物剂量测定法的开发通常是用离体照射的人进行的， 血液或动物体内。对于光子和中子，将比较离体与体内产生的生物标志物。 比较，并且表征和比较来自不同物种的离体产生的生物标志物。 4：优化的生物标志物整合：三种不同的生物标志物系统反映了生物标志物的不同平衡。 在例如通量、结果时间、信号寿命、剂量重建、曝光等方面的能力 情景识别和个体放射敏感性预测。这里的目标是确定他们的最佳 在各种非常不同的可能的大规模暴露情景中的每一种中的综合使用。 三个科学核心（动物、辐照和剂量测定以及生物统计学）汇集了关键支持 技术，每个核心支持每个研究项目。由于其综合性， 研究表明，这将大大提高效率。

This Program represents a cohesive approach motivated by the practical needs of very high-throughput biodosimetry in a variety of different large-scale exposure scenarios, to predict both individual dose and also individual sensitivity to future injury. A central characteristic remains our focus on 3 different high-throughput approaches: fully automated cytogenetics (Project 1), gene expression (Project 2), and metabolomics (Project 3). These have different balances of capabilities in terms of throughput, time-to-result, dose reconstruction, exposure scenario identification and individual radiosensitivity prediction, and the final goal is to quantify their optimal integrated usage in different large-scale exposure scenarios. The Projects share four common themes: 1: “Beyond Simple Exposures”: Towards High-Throughput Biodosimetry for Complex Exposures: After an IND there will be a wide variety of exposure scenarios including very high dose rate, neutron exposure, partial-body exposure (all from the initial prompt radiation), and varying dose rate and low dose rate (from external fallout and internal exposure). The goals are to 1) understand how these different exposure scenarios modulate the response of the predictive biomarkers that we have developed, and 2) optimally use these biomarkers to identify / characterize these different exposure scenarios to which individuals may be exposed. 2: “Beyond Dose”: Towards High-Throughput Individualized Predictors of Photon and Neutron- Induced Radiosensitivity and Late Radiation Injury: Gene expression and metabolomics each have utility for predicting individualized onset of late radiation-induced lung disease, and for predicting which irradiated animals will die from the disease. This work will be extended to neutron-induced late effects, whilst also assessing the significance of senescent cells for late disease development and for our lung disease signatures. 3: “Beyond Model Systems”: Probing the Applications of Experimentally-Generated Photon and Neutron Biomarkers to In-Vivo Human Exposure Scenarios: The goal is to assess in-vivo human exposures, but biodosimetric assay development is typically performed either with ex-vivo irradiated human blood or in-vivo in animals. For both photons and neutrons, ex-vivo vs. in-vivo generated biomarkers will be compared, and ex-vivo generated biomarkers from different species will be characterized and compared. 4: Optimized Biomarker Integration: The three different biomarker systems reflect different balances of capabilities in terms of, for example, throughput, time-to-result, signal lifetime, dose reconstruction, exposure scenario identification and individual radiosensitivity prediction. The goal here is to identify their optimal integrated usage in each of a variety of very different possible large-scale exposure scenarios. Three scientific cores (Animal, Irradiation & Dosimetry, and Biostatistics) bring together key support technologies, with each Core supporting each of the Research Projects. Because of the integrated nature of the research, this results in major gains in efficiency.