Rapid Low-Cost Paper-based Biodosimetry that reveals individual organ injuries

摘要： 核事故和/或恐怖主义的威胁日益增加，迫切需要 确认和量化暴露于辐射的大量人群中吸收的辐射剂量的能力 未知数量的意外辐射有效的分诊方法有可能挽救 成千上万的生命。为了最好地利用现有资源，逐步分流建议首先 使用区分未暴露和暴露的即时（POC）测试， 人群，然后使用高通量定量 分析方法，以估计其吸收的辐射剂量。理想的POC测试将预测 骨髓等主要器官的急性和延迟辐射损伤。估计 生物剂量学测量宿主对电离辐射的生物反应。的 特定基因的表达根据辐射剂量而改变。这里我们用这个表达 这些辐射反应基因的水平作为暴露于辐射的生物标志物。在此之前， 我们使用基因组方法结合体内NHP模型来识别许多辐射， 响应基因，并开发高通量实验室测试，以检测和量化吸收 在暴露后7天内接受辐射剂量。对这些数据的新分析揭示了一个子集 区分暴露个体和非暴露个体的生物标志物。此外， 辐射暴露的标志是淋巴细胞总数的迅速衰减。这个新 一组生物标志物可以定量预测淋巴细胞计数在7 暴露后24天，暴露后24小时。我们也有技术将我们的 将基因表达检测转化为低成本的纸基POC检测，与筛选和 人口众多。通过结合我们的能力和目前可用的生物标志物，我们打算 开发一种低成本的POC测试; 1）识别暴露于意外辐射的个人; 2） 根据吸收的辐射剂量对个人进行定性分类; 3）预测风险 通过计算第1天的未来第7天淋巴细胞计数来评估严重骨髓损伤。我们 我们将分三个步骤执行我们的项目研究计划。首先，我们将选择最佳子集， 生物标志物通过分析基因表达数据集和整理文献。二是 使我们的基于纸的、低成本的POC测试适应这些标志物的关键表达水平。 最后，我们将使用独立的未知样本验证我们的测试和生物标志物。

Abstract: Increasing threats of nuclear accidents and/or terrorism have triggered an urgent need for the ability to confirm and quantify absorbed radiation doses in a large population exposed to an unknown amount of unintended radiation. An effective triage method has the potential to save thousands of lives. To best utilize the available resources, stepwise triage recommends first using a point-of-care (POC) test that distinguishes between the non-exposed and the exposed population, followed by an assessment of those exposed using high throughput quantitative analysis methods to estimate their absorbed doses of radiation. The ideal POC test will predict acute and delayed radiation injuries to major organs, like bone marrow. To estimate the absorbed dose, biodosimetry measures host biological responses to ionizing radiation. The expression of specific genes alters based on the dose of radiation. Here we use the expression levels of these radiation-responsive genes as biomarkers of exposure to radiation. Previously, we used genomic approaches coupled with an in vivo NHP model to identify many radiation responsive genes and develop a high throughput laboratory test to detect and quantify absorbed dose of radiation within 7 days of post exposure. A new analysis of these data reveals a subset of biomarkers that distinguish exposed from non-exposed individuals. Moreover, one of the hallmarks of radiation exposure is a rapid decay in the total number of lymphocytes. This new panel of biomarkers can quantitatively predict a significant drop in the lymphocyte count at 7 days post exposure, only 24 hours post exposure. We also have technology for converting our gene expression assays into a low-cost paper-based POC test, compatible with screening a large population. By combining our capabilities and currently available biomarkers, we intend to develop a low-cost POC test that; 1) identifies individuals exposed to unintended radiation; 2) qualitatively classifies individuals based on their absorbed dose of radiation; 3) predicts the risk of serious bone marrow injury by calculating their future day 7 lymphocyte counts on day 1. We will execute our project study plan in three steps. First, we will select the best subset of biomarkers by analyzing gene expression data sets and curating literature. Second, we will adapt our paper-based, low-cost, POC test to the critical expression levels of these markers. Finally, we will validate our test and biomarkers using independent unknown samples.