TY - JOUR
T1 - Modelling metallothionein induction in the liver of Sparus aurata exposed to metal-contaminated sediments
AU - Costa, Pedro M.
AU - Diniz, Mário Emanuel Campos de Sousa
AU - Moura, Isabel Maria Andrade Martins Galhardas de
AU - Costa, Maria Helena Ferrão Ribeiro da
PY - 2008/1/1
Y1 - 2008/1/1
N2 - Metallothionein (MT) in the liver of gilthead seabreams (Sparus aurata L., 1758) exposed to Sado estuary (Portugal) sediments was quantified to assess the MT induction potential as a biomarker of sediment-based contamination by copper (Cu), cadmium (U), lead (Pb) and arsenic (As). Sediments were collected from two control sites and four sites with different levels of contamination. Sediment Cu, Cd, Pb, As, total organic matter (TOM) and fine fraction (FF) levels were determined. Generalized linear models (GLM) allowed integration of sediment parameters with liver Cu, Cd, Pb, As and MT concentrations. Although sediment metal levels were lower than expected, we relate NIT with liver Cd and also with interactions between liver and sediment Cu and between liver Cu and TOM. We suggest integrating biomarkers and environmental parameters using statistical models such as GLM as a more sensitive and reliable technique for sediment risk assessment than traditional isolated biomarker approaches. (C) 2007 Elsevier Inc. All rights reserved.
AB - Metallothionein (MT) in the liver of gilthead seabreams (Sparus aurata L., 1758) exposed to Sado estuary (Portugal) sediments was quantified to assess the MT induction potential as a biomarker of sediment-based contamination by copper (Cu), cadmium (U), lead (Pb) and arsenic (As). Sediments were collected from two control sites and four sites with different levels of contamination. Sediment Cu, Cd, Pb, As, total organic matter (TOM) and fine fraction (FF) levels were determined. Generalized linear models (GLM) allowed integration of sediment parameters with liver Cu, Cd, Pb, As and MT concentrations. Although sediment metal levels were lower than expected, we relate NIT with liver Cd and also with interactions between liver and sediment Cu and between liver Cu and TOM. We suggest integrating biomarkers and environmental parameters using statistical models such as GLM as a more sensitive and reliable technique for sediment risk assessment than traditional isolated biomarker approaches. (C) 2007 Elsevier Inc. All rights reserved.
U2 - 10.1016/j.ecoenv.2007.05.012
DO - 10.1016/j.ecoenv.2007.05.012
M3 - Article
C2 - 17617458
SN - 0147-6513
VL - 71
SP - 117
EP - 124
JO - Ecotoxicology and Environmental Safety
JF - Ecotoxicology and Environmental Safety
IS - 1
ER -