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利用贻贝每日活动预测砷在淡水中的生物利用度和生物蓄积。

Predicting bioavailability and bioaccumulation of arsenic by freshwater clam Corbicula fluminea using valve daily activity.

机构信息

Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan, 10617, Republic of China.

出版信息

Environ Monit Assess. 2010 Oct;169(1-4):647-59. doi: 10.1007/s10661-009-1204-2. Epub 2009 Oct 22.

Abstract

There are many bioindicators. However, it remains largely unknown which metal-bioindicator systems will give the reasonable detection ranges of bioavailable metals in the aquatic ecosystem. Various experimental data make the demonstration of biomonitoring processes challenging. Ingested inorganic arsenic is strongly associated with a wide spectrum of adverse health outcomes. Freshwater clam Corbicula fluminea, one of the most commonly used freshwater biomomitoring organisms, presents daily activity in valve movement and demonstrates biotic uptake potential to accumulate arsenic. Here, a systematical way was provided to dynamically link valve daily activity in C. fluminea and arsenic bioavailability and toxicokinetics to predict affinity at arsenic-binding site in gills and arsenic body burden. Using computational ecotoxicology methods, a valve daily rhythm model can be tuned mathematically to the responsive ranges of valve daily activity system in response to varied bioavailable arsenic concentration. The patterned response then can be used to predict the site-specific bioavailable arsenic concentration at the specific measuring time window. This approach can yield predictive data of results from toxicity studies of specific bioindicators that can assist in prediction of risk for aquatic animals and humans.

摘要

有许多生物标志物。然而,在很大程度上仍然不清楚哪些金属-生物标志物系统将提供水生生态系统中生物可利用金属的合理检测范围。各种实验数据使得生物监测过程的演示具有挑战性。摄入无机砷与广泛的健康不良后果密切相关。淡水蛤 Corbicula fluminea 是最常用的淡水生物监测生物之一,其瓣鳃每天都有活动,并表现出生物摄取潜力来积累砷。在这里,提供了一种系统的方法,可以将 C. fluminea 的瓣鳃每日活动与砷的生物利用度和毒代动力学动态联系起来,以预测鳃中砷结合位点的亲和力和砷的体内负荷。使用计算生态毒理学方法,可以对瓣鳃每日节律模型进行数学调整,以响应变化的生物可利用砷浓度,从而使瓣鳃每日活动系统的响应范围达到响应范围。然后可以使用这种模式响应来预测特定测量时间窗口内特定位置的生物可利用砷浓度。这种方法可以提供特定生物标志物毒性研究的预测性结果数据,有助于预测水生动物和人类的风险。

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