Publication Date:
2022-05-25
Description:
Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Comparative Biochemistry and Physiology - Part A: Molecular & Integrative Physiology 155 (2010): 341-349, doi:10.1016/j.cbpa.2009.11.019.
Description:
Heavy metals, such as copper, zinc and cadmium, represent some of the most common and
serious pollutants in coastal estuaries. In the present study, we used a combination of linear and
artificial neural network (ANN) modelling to detect and explore interactions among low-dose
mixtures of these heavy metals and their impacts on fundamental physiological processes in
tissues of the Eastern oyster, Crassostrea virginica. Animals were exposed to Cd (0.001 – 0.400
μM), Zn (0.001 – 3.059 μM) or Cu (0.002 – 0.787 μM), either alone or in combination for 1 to
27 days. We measured indicators of acid-base balance (hemolymph pH and total CO2), gas
exchange (Po2), immunocompetence (total hemocyte counts, numbers of invasive bacteria),
antioxidant status (glutathione, GSH), oxidative damage (lipid peroxidation; LPx), and metal
accumulation in the gill and the hepatopancreas. Linear analysis showed that oxidative
membrane damage from tissue accumulation of environmental metals was correlated with
impaired acid-base balance in oysters. ANN analysis revealed interactions of metals with
hemolymph acid-base chemistry in predicting oxidative damage that were not evident from
linear analyses. These results highlight the usefulness of machine learning approaches, such as
ANNs, for improving our ability to recognize and understand the effects of sub-acute exposure to
contaminant mixtures.
Description:
This study was supported by NOAA’s Center of Excellence in Oceans and Human Health at HML and the National Science Foundation.
Keywords:
Heavy metals
;
Artificial neural networks
;
Crassostrea virginica
;
Lipid peroxidation
;
Glutathione
;
Acid-base balance
;
Hemolymph PO2
Repository Name:
Woods Hole Open Access Server
Type:
Preprint
Format:
application/pdf
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