Effect of PCB Bioavailability Changes in Sediments on Bioaccumulation in Fish

In situ sediment amendment with sorbents such as activated carbon (AC) can effectively reduce the bioavailability of hydrophobic organic chemicals such as polychlorinated biphenyls (PCBs). However, there is limited experimental or modeling assessment of how bioavailability changes in sediments impact bioaccumulation in fish – the primary risk driver for exposure to humans and top predators in the aquatic ecosystem. In the present study we performed laboratory aquarium experiments and modeling to explore how PCB sorption in sediments impacted exposure pathways and bioaccumulation in fish. Results showed that freely dissolved PCBs in porewater and overlying water measured by passive sampling were reduced by more than 95% upon amendment with 4.5% fine granular AC. The amendment also reduced the PCB uptake in fish by 87% after 90 days of exposure. Measured freely dissolved concentrations were incorporated in equilibrium and kinetic models for predicting uptake by fish. Predicted uptake using the kinetic model was generally within a factor of 2 for total PCBs measured in fish. The kinetic model output was most sensitive to overlying water PCBs, lipid fraction, and dissolved oxygen concentration (regulating gill ventilation). Our results indicate that by incorporating changes in freely dissolved PCB concentrations in bioaccumulation models it is possible to predict effectiveness of sediment remediation in reducing PCB uptake in fish

Consistency of the individual host response to <i>E. coli</i> 83972 inoculation.

<p>A. The host response in urine samples from the first (blue) and second inoculations (grey) were compared (Geometric means + SEs) in six patients that had received repeated inoculations. B. Kinetics of the host response during the first and second ABU episode in one high and one low responder.</p

Promoter polymorphisms and the host response to ABU.

<p>A. Three of five <i>TLR4</i> genotypes associated with primary ABU were detected (blue hexagons) in five of the eleven patients. These patients had significantly lower neutrophil numbers (p<0.002) and IL-6 (p<0.0001), MCP-1 (p<0.01), IP-10 (p<0.0001), and sIL-2Rα (p<0.0001) concentrations than the patients with non-ABU associated <i>TLR4</i> genotypes XIX, IV, XX and IX (red squares). Each column represents one patient and each hexagon or square one monthly urine sample. B. The heterozygous <i>IRF3</i> promoter genotype associated with ABU (A/G-C/T, blue hexagon) was detected in four of the eleven patients, who had significantly lower neutrophil numbers (p = 0.01) and IL-6 (p<0.001) and MCP-1 (p = 0.0001) concentrations than patients with the homozygous, pyelonephritis-associated genotype (A/A-C/C, red square). Each column represents one patient and each hexagon or square one monthly urine sample.</p

Host response to <i>E. coli</i> 83972 bacteriuria.

<p><i>E. coli</i> 83972 ABU triggered an increase in PMN numbers and IL-8 concentrations (p<0.0001) but IL-6 levels were unchanged (n.s., Mann-Whitney test). Group-wise comparison of monthly urine samples collected during <i>E. coli</i> 83927 ABU or after PBS inoculations. Coded patient IDs are noted on the x-axis. A. Means + SEs of neutrophil numbers, IL-8 and IL-6 concentrations during <i>E. coli</i> 83972 bacteriuria (pink) or sterile conditions (blue). B. Intra-individual comparison of samples obtained during <i>E. coli</i> 83972 bacteriuria (pink) and sterile intervals (blue). C. Box-plot of intra-individual host response variation during <i>E. coli</i> 83972 ABU.</p

Patients and samples.

<p>Samples from patients participating in a clinical trial of induced <i>E. coli</i> 83972 ABU were analyzed. All collected urine samples were subjected to PMN, IL-6 and IL-8 quantification, and blood samples from eleven patients were collected for genotyping of promoter polymorphisms in TLR4 and IRF3. Blood and urine samples from these eleven patients were also selected for an extended urine protein analysis.</p

Patient Characteristics.

<p>The table displays data from trials performed between 1993 and June, 2005. All patients had incomplete bladder emptying (residual urine ≥100 ml) and UTI susceptibility with a history ≥3 UTI/ year with urinary cultures showing uropathogenic growth, two years prior to the study.</p><p>1) M =  Male, F =  Female.</p><p>2) Clean Intermittent Catheterization. All patients had been instructed to use CIC regularly. Of the 8 patients who did not use CIC during the study 2 patients refused because of practical reasons and the remaining 6 patients had residual urine <300 ml, and had not experienced any improvement from previously performed regular CIC.</p

Supplement 1. Detailed description of how the methods are applied to data, including SAS and R code and data from two experiments.

<h2>File List</h2><blockquote> <table> <tbody><tr> <td><a href="Jena_dataset.pdf">Jena_dataset.pdf</a></td> <td> </td> <td>Worked example of model fitting for the Jena_dataset.pdf </td> </tr> <tr> <td><a href="Jena_dataset.sas">Jena_dataset.sas</a></td> <td> </td> <td>SAS code for analysis of Jena_dataset.sas </td> </tr> <tr> <td><a href="Jena_dataset.r">Jena_dataset.r</a></td> <td> </td> <td>R code for analysis of Jena_dataset.r </td> </tr> <tr> <td><a href="Jena_data.csv">Jena_data.csv</a></td> <td> </td> <td>Jena data </td> </tr> <tr> <td><a href="Ireland_site_biodepth.csv">Ireland_site_biodepth.csv</a></td> <td> </td> <td>Data for Ireland_site_Biodepth.csv </td> </tr> </tbody></table> </blockquote><h2>Description</h2><blockquote> <p>The supplements are designed to assist the reader to implement the methods using the statistical packages SAS and R. The first supplement (Worked example of model fitting for theJena_dataset.pdf) provides a detailed description of the application and interpretation of a range of models using the Jena dataset. The second and third supplements (SAS code for analysis of Jena_dataset.sas) and (R code for analysis of Jena_dataset.r) provide SAS and R code to implement the method using the Jena dataset. The data for the two sites is provided in Jena_data.csv and Ireland_site_biodepth.csv.</p> <p>Hash values for supplements Jena_data.csv and Ireland_site_biodepth.csv calculated by HASHCALC:</p> <p>MD5 hash value for Jena_data.csv</p> <p>6b86c280a15bbd4aae08b5b4c91363ee</p> <p>MD5 hash value for Ireland_site_biodepth.csv</p> <p>9b60c32ceca9259e47d7ee42b9ae5f16</p> </blockquote

Appendix B. Detail of the construction of the matrices of phylogenetic distances used for the species in the two experiments.

Detail of the construction of the matrices of phylogenetic distances used for the species in the two experiments

Appendix C. Calculation of the standard deviation of the variable CD across all communities at a given level of richness.

Calculation of the standard deviation of the variable CD across all communities at a given level of richness

Appendix A. Yield per plot vs. number of species for the Biodepth Ireland experiment.

Yield per plot vs. number of species for the Biodepth Ireland experiment