Trophic Magnification of Parabens and Their Metabolites in a Subtropical Marine Food Web

Despite the widespread use of parabens in a range of consumer products, little is known about bioaccumulation of these chemicals in aquatic environments. In this study, six parabens and four of their common metabolites were measured in abiotic (water, sediment) and biotic (fish including sharks, invertebrates, plants) samples collected from a subtropical marine food web in coastal Florida. Methyl paraben (MeP) was found in all abiotic (100%) and a majority of biotic (87%) samples. 4-Hydroxy benzoic acid (4-HB) was the most abundant metabolite, found in 97% of biotic and all abiotic samples analyzed. The food chain accumulation of MeP and 4-HB was investigated for this food web. The trophic magnification factor (TMF) of MeP was estimated to be 1.83, which suggests considerable bioaccumulation and biomagnification of this compound in the marine food web. In contrast, a low TMF value was found for 4-HB (0.30), indicating that this compound is metabolized and excreted along the food web. This is the first study to document the widespread occurrence of parabens and their metabolites in fish, invertebrates, seagrasses, marine macroalgae, mangroves, seawater, and ocean sediments and to elucidate biomagnification potential of MeP in a marine food web

Comparison of predictive performance in different prediction models.

<p>Comparison of predictive performance in different prediction models.</p

Performance of the prediction model for LNM in endometrial endometrioid cancer.

<p>Performance of the prediction model for LNM in endometrial endometrioid cancer.</p

Description of three reported prediction models for lymph node metastasis (LNM) in endometrial cancer.

<p>Description of three reported prediction models for lymph node metastasis (LNM) in endometrial cancer.</p

Basic characteristics of selected 370 patients and the 866 patients with endometrioid histology from original 1098 patients.

<p>Basic characteristics of selected 370 patients and the 866 patients with endometrioid histology from original 1098 patients.</p

Results of univariate and multivariate logistic regression analyses in the prediction cohort.

<p>Results of univariate and multivariate logistic regression analyses in the prediction cohort.</p

Flowchart of selection of patients in prediction cohort.

<p>Flowchart of selection of patients in prediction cohort.</p