A fundamental goal in nano-toxicology is that of identifying particle physical and chemical properties, which are likely to explain biological hazard. The first line of screening for potentially adverse outcomes often consists of exposure escalation experiments, involving the exposure of micro-organisms or cell lines to a library of nanomaterials. We discuss a modeling strategy, that relates the outcome of an exposure escalation experiment to nanoparticle properties. Our approach makes use of a hierarchical decision process, where we jointly identify particles that initiate adverse biological outcomes and explain the probability of this event in terms of the particle physicochemical descriptors. The proposed inferential framework results in summaries that are easily interpretable as simple probability statements. We present the application of the proposed method to a data set on 24 metal oxides nanoparticles, characterized in relation to their electrical, crystal and dissolution properties.

中文翻译：

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将纳米粒子特性与暴露升级实验中的生物学结果联系起来

纳米毒理学的一个基本目标是确定可能解释生物危害的粒子物理和化学特性。潜在不利结果的第一线筛查通常包括暴露升级实验，包括将微生物或细胞系暴露于纳米材料库。我们讨论了一种建模策略，该策略将暴露升级实验的结果与纳米粒子特性相关联。我们的方法利用分层决策过程，在其中我们共同识别引发不利生物结果的粒子，并根据粒子物理化学描述符解释该事件的概率。提议的推理框架产生的摘要很容易解释为简单的概率陈述。