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Multivariate Analysis of Radiation Responsive Proteins to Predict Radiation Exposure in Total-Body Irradiation and Partial-Body Irradiation Models

机译:辐射响应蛋白的多变量分析预测全辐射和部分辐射模型中的辐射暴露

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摘要

In the event of a radiological or nuclear attack, advanced clinical countermeasures are needed for screening and medical management of the exposed population. In such a scenario, minimally invasive biomarkers that can accurately quantify radiation exposure would be useful for triage management by first responders. In this murine study, we evaluated the efficacy of a novel combination of radiation responsive proteins, Flt3 ligand (FL), serum amyloid A (SAA), matrix metalloproteinase 9 (MMP9), fibrinogen beta (FGB) and pentraxin 3 (PTX3) to predict the received dose after whole- or partial-body irradiation. Ten-week-old female C57BL6 mice received a single whole-body or partial-body dose of 18 Gy from a Pantak X-ray source at a dose rate of 2.28 Gy/min. Plasma was collected by cardiac puncture at 24, 48, 72 h and 1 week postirradiation. Plasma protein levels were determined via commercially available ELISA assay. A multivariate discriminant analysis was utilized to generate best-fit dose prediction models for whole-body exposures using the selected biomarker panel and its potential application to partial-body exposures was examined. The combination of values from FL, SAA, MMP9, FGB and PTX3 between 24 h and 1 week postirradiation yielded novel dose-response relationships. For day 1 postirradiation, the best-fit model yielded a predictive accuracy of 81% utilizing FL alone. The use of additional proteins did not enhance the model accuracy whereas, at day 2 postirradiation, the addition of PTX3 and FGB to FL increased the accuracy to 100%. At day 3 the use of FL and PTX3 yielded a predictive accuracy of 93% and at day 7 use of FL and SAA had an accuracy of 90%. Dose prediction of partial-body exposures based on the TBI model had a higher predictive accuracy when the percentage of the body exposed to radiation increased. Our findings indicate that this novel combination of radiation responsive biomarker proteins are an efficient method for predicting radiation exposure and are more accurate when used in concert compared to using any single biomarker protein alone.
机译:如果发生放射或核袭击,则需要采取先进的临床对策以筛查和管理暴露人群。在这种情况下,可以准确量化辐射暴露量的微创生物标志物对于急救人员的分类管理很有用。在这项鼠类研究中,我们评估了放射响应蛋白,Flt3配体(FL),血清淀粉样蛋白A(SAA),基质金属蛋白酶9(MMP9),纤维蛋白原β(FGB)和戊糖原3(PTX3)的新型组合的疗效。预测全身或局部照射后的剂量。十周大的雌性C57BL6小鼠以2.28 Gy / min的剂量速率从Pantak X射线源接受了18 Gy的单一全身或局部剂量。在照射后24、48、72 h和1周通过心脏穿刺收集血浆。血浆蛋白水平通过可商购的ELISA测定法确定。使用选定的生物标志物组,使用多元判别分析为全身暴露量生成最佳拟合剂量预测模型,并检查其在部分身体暴露量中的潜在应用。照射后24小时至1周之间来自FL,SAA,MMP9,FGB和PTX3的值的组合产生了新颖的剂量反应关系。对于辐射后的第1天,仅使用FL的最佳拟合模型的预测准确性为81%。使用其他蛋白质并不能提高模型的准确性,而在照射后第2天,向FL中添加PTX3和FGB可以使准确性提高到100%。在第3天,使用FL和PTX3的预测准确性为93%,在第7天,使用FL和SAA的预测准确性为90%。当身体暴露于辐射的百分比增加时,基于TBI模型的部分身体暴露的剂量预测具有更高的预测准确性。我们的发现表明,这种辐射响应性生物标志物蛋白的新颖组合是一种预测辐射暴露的有效方法,与单独使用任何单个生物标志物蛋白一起使用时,其准确性更高。

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