Cancer risk at low doses of ionizing radiation: artificial neural networks inference from atomic bomb survivors.

Cancer risk at low doses of ionizing radiation: artificial neural networks inference from atomic bomb survivors.
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低剂量的电离辐射下的癌症风险:原子弹幸存者的人工神经网络推断。

DOI:
10.1093/jrr/rrt133
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发表时间:
2014-05
影响因子:
2
通讯作者:
Takeda S
Takeda S
中科院分区:
医学4区
文献类型:
--
作者:
Sasaki MS;Tachibana A;Takeda S

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低剂量电离辐射下的癌症风险仍然界定不清,因为广岛和长崎原子弹爆炸幸存者所受剂量低于0.2西沃特的剂量在数量上的联系含糊不清,这是由于有关总辐射剂量的统计能力和现有资料的限制。为了解决这些困难,研究人员开发了一种基于人工神经网络“集与火”算法的新型非参数统计方法,并在辐射效应研究基金会建立的癌症数据库中进行了测试。分析揭示了低剂量下无法用名义照射剂量解释的独特特征,包括:(i)存在一个随照射时器官、性别和年龄而变化的阈值,以及(ii)长崎低剂量下癌症风险小幅但显著的突发性增加,这可能反映了体内暴露于239Pu。这个阈值不同于零效应的规范定义,因为它表现为负超额相对风险,或抑制背景癌症发病率。在低剂量辐射照射下,这种独特的组织反应与辐射-环境相互作用的分子基础有关,这有利于最近出现的DNA双链断裂修复途径选择及其通过组蛋白标记的表观遗传记忆的实验证据。
Cancer risk at low doses of ionizing radiation remains poorly defined because of ambiguity in the quantitative link to doses below 0.2 Sv in atomic bomb survivors in Hiroshima and Nagasaki arising from limitations in the statistical power and information available on overall radiation dose. To deal with these difficulties, a novel nonparametric statistics based on the ‘integrate-and-fire’ algorithm of artificial neural networks was developed and tested in cancer databases established by the Radiation Effects Research Foundation. The analysis revealed unique features at low doses that could not be accounted for by nominal exposure dose, including (i) the presence of a threshold that varied with organ, gender and age at exposure, and (ii) a small but significant bumping increase in cancer risk at low doses in Nagasaki that probably reflects internal exposure to 239Pu. The threshold was distinct from the canonical definition of zero effect in that it was manifested as negative excess relative risk, or suppression of background cancer rates. Such a unique tissue response at low doses of radiation exposure has been implicated in the context of the molecular basis of radiation–environment interplay in favor of recently emerging experimental evidence on DNA double-strand break repair pathway choice and its epigenetic memory by histone marking.
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