Although Concentrated Animal Feeding Operations (CAFOs) have been identified as potentially important sources for the release of estrogens into the environment, information is lacking on the concentrations of estrogens in whole lagoon effluents (including suspended solids) which are used for land application. Lagoons associated with swine, poultry, and cattle operations were sampled at three locations each for direct analysis for estrogens by GC/ MS/MS and estrogen conjugates by LC/MS/MS. Estrogen conjugates were also analyzed indirectly by first subjecting the same samples to enzyme hydrolysis. Solids from centrifuged samples were extracted for free estrogens to estimate total estrogen load. Total free estrogen levels (estrone, 17alpha-estradiol, 17beta-estradiol, estriol) were generally higher in swine primary (1000-21000 ng/L), followed by poultry primary (1800-4000 ng/L), dairy secondary (370-550 ng/L), and beef secondary (22-24 ng/L) whole lagoon samples. Swine and poultry lagoons contained levels of 17(alpha-estradiol comparable to those of 17beta-estradiol. Confirmed estrogen conjugates included estrone-3-sulfate (2-91 ng/L), 17beta-estradiol-3-sulfate (8-44 ng/L), 17alpha-estradiol-3-sulfate (141-182 ng/L), and 17beta-estradiol-17-sulfate (72-84 ng/L) in some lagoons. Enzymatic hydrolysis indicated the presence of additional unidentified estrogen conjugates not detected bythe LC/MS/MS method. In most cases estrogen conjugates accounted for at least a third of the total estrogen equivalents. Collectively, these methods can be used to better determine estrogen loads from CAFO operations, and this research shows that estrogen conjugates contribute significantly to the overall estrogen load, even in different types of CAFO lagoons.

No abstract

After the fireworks displays, perchlorate concentrations decreased toward the background level within 20 to 80 days, with the rate of attenuation correlating to surface water temperature. Adsorption tests indicate that sediments underlying the water column have limited (<100 nmol/g) capacity to remove perchlorate via chemical adsorption. Microcosms showed comparatively rapid intrinsic perchlorate degradation in the absence of nitrate consistent with the observed disappearance of perchlorate from the study site. This suggests that at sites with appropriate biogeochemical conditions, natural attenuation may be an important factor affecting the fate of perchlorate following fireworks displays.

Custom software entitled Plant Metabolite Annotation Toolbox (PlantMAT) has been developed to address the number one grand challenge in metabolomics, which is the large-scale and confident identification of metabolites. PlantMAT uses informed phytochemical knowledge for the prediction of plant natural products such as saponins and glycosylated flavonoids through combinatorial enumeration of aglycone, glycosyl, and acyl subunits. Many of the predicted structures have yet to be characterized and are absent from traditional chemical databases, but have a higher probability of being present in planta. PlantMAT allows users to operate an automated and streamlined workflow for metabolite annotation from a user-friendly interface within Microsoft Excel, a familiar, easily accessed program for chemists and biologists. The usefulness of PlantMAT is exemplified using ultrahigh-performance liquid chromatography-electrospray ionization quadrupole time-of-flight tandem mass spectrometry (UHPLC-ESI-QTOF-MS/MS) metabolite profiling data of saponins and glycosylated flavonoids from the model legume Medicago truncatula. The results demonstrate PlantMAT substantially increases the chemical/metabolic space of traditional chemical databases. Ten of the PlantMAT-predicted identifications were validated and confirmed through the isolation of the compounds using ultrahigh-performance liquid chromatography-mass spectrometry-solid-phase extraction (UHPLC-MS-SPE) followed by de novo structural elucidation using 1D/2D nuclear magnetic resonance (NMR). It is further demonstrated that PlantMAT enables the dereplication of previously identified metabolites and is also a powerful tool for the discovery of structurally novel metabolites.