First detection of CYP1A1 and CYP2B induction in Mediterranean cetacean skin biopsies and cultured fibroblasts by Western blot analysis

Fossi, María Cristina; Casini, Silvia; Bucalossi, D.; Marsili, Letizia

doi:10.1016/j.marenvres.2008.02.006

Cited by 34 publications

(26 citation statements)

References 10 publications

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“…In the present study, we have focused our attention on striped dolphins ( Stenella coeruleoalba ), which are the most abundant dolphins in the Mediterranean Sea (Aguilar; Gomez de Segura et al,; Fortuna et al,, Panigada et al,); they are pelagic odontocetes at the top of the marine food chain and are therefore potentially subject to biomagnification of persistent contaminants. In the International Union for Conservation of Nature (IUCN) Red List, striped dolphins are classified as least concern for extinction (IUCN,).…”

Section: Introductionmentioning

confidence: 99%

An “ex vivo” model to evaluate toxicological responses to mixtures of contaminants in cetaceans: Integumentum biopsy slices

Fossi

Casini

Maltese

et al. 2013

Environmental Toxicology

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The need for powerful new tools to detect the effects of chemical pollution, in particular of persistent organic pollutants (POPs) and polycyclic aromatic hydrocarbons (PAHs) on Mediterranean cetaceans led us to develop and apply a suite of sensitive biomarkers for integument biopsies of stranded and free-ranging animals. This multi-response ex vivo method has the aim to detect toxicological effects of contaminant mixtures. In the present study, we applied an ex vivo assay using skin biopsy and liver slices, combining molecular biomarkers [Western blot of Cytochrome P450 1A1 (CYP1A1) and Cytochrome P450 2B (CYP2B)] and gene expression biomarkers (Quantitative real-time PCR of CYP1A1, heat shock protein 70, estrogen receptor alpha and E2F transcription factor) in response to chemical exposure [organochlorines compounds (OCs), polybrominated diphenyl ethers (PBDEs), and PAHs] for stranded Mediterranean Stenella coeruleoalba. The main goal of this experiment was to identify the biomarker and/or a suite of biomarkers that could best detect the presence of a specific class of pollutants (OCs, PBDEs, and PAHs) or a mixture of them. This multi-response biomarker methodology revealed an high sensitivity and selectivity of responses (such as CYP1A and ER α mRNA variations after OCs and PAHs exposure) and could represent a valid future approach for the study of inter- and intra-species sensitivities to various classes of environmental contaminants.

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Section: Introductionmentioning

confidence: 99%

An “ex vivo” model to evaluate toxicological responses to mixtures of contaminants in cetaceans: Integumentum biopsy slices

Fossi

Casini

Maltese

et al. 2013

Environmental Toxicology

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“…Fossi et al 2006Fossi et al , 2008Marsili et al 2008;Spinsanti et al 2008) and on the evaluation of immunotoxicity and metabolic activity for pollutant breakdown or biotransformation (e.g. Boon et al 1998;De Guise et al 1998;Kim et al 1998;White et al 2000;Nakata et al 2002;Levin et al 2004Levin et al , 2007Mori et al 2006;Wilson et al 2007;Camara Pellissò et al 2008).…”

Section: In Vitro Researchmentioning

confidence: 99%

Toxicology of Marine Mammals: New Developments and Opportunities

Weijs

Zaccaroni

2015

Arch Environ Contam Toxicol

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It is widely recognized that marine mammals are exposed to a wide variety of pollutants, with a weight of evidence indicating impacts on their health. Since hundreds of new chemicals enter the global market every year, the methods, approaches and technologies used to characterize pollution levels or impacts are also in a constant state of flux. However, legal and ethical constraints often limit the type and extent of toxicological research being carried out in marine mammals. Nevertheless, new and emerging in vivo, in vitro as well as in silico research opportunities abound in the field of marine mammal toxicology. In the application of findings to population-, species-, or habitatrelated risk assessments, the identification of causal relationships which inform source apportionment is important. This, in turn, is informed by a comprehensive understanding of contaminant classes, profiles and fate over space and time. Such considerations figure prominently in the design and interpretation of marine mammal (eco)-toxicology research. This mini-review attempts to follow the evolution behind marine mammal toxicology until now, highlight some of the research that has been done and suggest opportunities for future research. This Special Issue will showcase new developments in marine mammal toxicology, approaches for exposure-effect research in risk assessment as well as future opportunities.

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“…The mats occupy extensive area of seafloor below 100 m depth in the Inlet, varying in coverage with the annual cycle of anoxia [27]. Munida are abundant and especially well adapted to the low and fluctuating oxygen concentrations found at these depths in Saanich Inlet [28]. …”

Section: Introductionmentioning

confidence: 99%

Automated Image Analysis for the Detection of Benthic Crustaceans and Bacterial Mat Coverage Using the VENUS Undersea Cabled Network

Aguzzi

Costa²,

Robert

et al. 2011

Sensors

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The development and deployment of sensors for undersea cabled observatories is presently biased toward the measurement of habitat variables, while sensor technologies for biological community characterization through species identification and individual counting are less common. The VENUS cabled multisensory network (Vancouver Island, Canada) deploys seafloor camera systems at several sites. Our objective in this study was to implement new automated image analysis protocols for the recognition and counting of benthic decapods (i.e., the galatheid squat lobster, Munida quadrispina), as well as for the evaluation of changes in bacterial mat coverage (i.e., Beggiatoa spp.), using a camera deployed in Saanich Inlet (103 m depth). For the counting of Munida we remotely acquired 100 digital photos at hourly intervals from 2 to 6 December 2009. In the case of bacterial mat coverage estimation, images were taken from 2 to 8 December 2009 at the same time frequency. The automated image analysis protocols for both study cases were created in MatLab 7.1. Automation for Munida counting incorporated the combination of both filtering and background correction (Median- and Top-Hat Filters) with Euclidean Distances (ED) on Red-Green-Blue (RGB) channels. The Scale-Invariant Feature Transform (SIFT) features and Fourier Descriptors (FD) of tracked objects were then extracted. Animal classifications were carried out with the tools of morphometric multivariate statistic (i.e., Partial Least Square Discriminant Analysis; PLSDA) on Mean RGB (RGBv) value for each object and Fourier Descriptors (RGBv+FD) matrices plus SIFT and ED. The SIFT approach returned the better results. Higher percentages of images were correctly classified and lower misclassification errors (an animal is present but not detected) occurred. In contrast, RGBv+FD and ED resulted in a high incidence of records being generated for non-present animals. Bacterial mat coverage was estimated in terms of Percent Coverage and Fractal Dimension. A constant Region of Interest (ROI) was defined and background extraction by a Gaussian Blurring Filter was performed. Image subtraction within ROI was followed by the sum of the RGB channels matrices. Percent Coverage was calculated on the resulting image. Fractal Dimension was estimated using the box-counting method. The images were then resized to a dimension in pixels equal to a power of 2, allowing subdivision into sub-multiple quadrants. In comparisons of manual and automated Percent Coverage and Fractal Dimension estimates, the former showed an overestimation tendency for both parameters. The primary limitations on the automatic analysis of benthic images were habitat variations in sediment texture and water column turbidity. The application of filters for background corrections is a required preliminary step for the efficient recognition of animals and bacterial mat patches.

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First detection of CYP1A1 and CYP2B induction in Mediterranean cetacean skin biopsies and cultured fibroblasts by Western blot analysis

Cited by 34 publications

References 10 publications

An “ex vivo” model to evaluate toxicological responses to mixtures of contaminants in cetaceans: Integumentum biopsy slices

An “ex vivo” model to evaluate toxicological responses to mixtures of contaminants in cetaceans: Integumentum biopsy slices

Toxicology of Marine Mammals: New Developments and Opportunities

Automated Image Analysis for the Detection of Benthic Crustaceans and Bacterial Mat Coverage Using the VENUS Undersea Cabled Network

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