2009 Regional Ambient Fish Tissue Monitoring Program Summary of Analyses

To supplement other environmental monitoring programs and to protect the health of people consuming fish from waters within this state, the state of Iowa conducts fish tissue monitoring. Since 1980, the Iowa Department of Natural Resources (IDNR), the United States Environmental Protection Agency Region VII (U.S. EPA), and the University of Iowa Hygienic Laboratory (UHL) have cooperatively conducted annual statewide collections and analyses of fish for toxic contaminants. Beginning in 1983, this monitoring effort became known as the Regional Ambient Fish Tissue Monitoring Program (RAFT). Currently, the RAFT program is the only statewide fish contaminant-monitoring program in Iowa. Historically, the data generated from the RAFT program have enabled IDNR to document temporal changes in contaminant levels and to identify Iowa lakes and rivers where high levels of contaminants in fish potentially threaten the health of fish-consuming Iowans (see IDNR 2006). The Iowa RAFT monitoring program incorporates four different types of monitoring sites: 1) status, 2) trend, 3) random and 4) follow-up. New for 2009 was the one-time inclusion of snapping turtle tissue as part of the Iowa RAFT sampling program.

2008 Regional Ambient Fish Tissue Monitoring Program Summary of Analyses

To supplement other environmental monitoring programs and to protect the health of people consuming fish from waters within this state, the state of Iowa conducts fish tissue monitoring. Since 1980, the Iowa Department of Natural Resources (IDNR), the United States Environmental Protection Agency Region VII (U.S. EPA), and the University of Iowa Hygienic Laboratory (UHL) have cooperatively conducted annual statewide collections and analyses of fish for toxic contaminants. Beginning in 1983, this monitoring effort became known as the Regional Ambient Fish Tissue Monitoring Program (RAFT). Currently, the RAFT program is the only statewide fish contaminant-monitoring program in Iowa. Historically, the data generated from the RAFT program have enabled IDNR to document temporal changes in contaminant levels and to identify Iowa lakes and rivers where high levels of contaminants in fish potentially threaten the health of fish-consuming Iowans (see IDNR 2006). The Iowa RAFT monitoring program incorporates four different types of monitoring sites: 1) status, 2) trend, 3) random and 4) follow-up.

2006/2007 Regional Ambient Fish Tissue Monitoring Program Summary of Analyses

To supplement other environmental monitoring programs and to protect the health of people consuming fish from waters within this state, the state of Iowa conducts fish tissue monitoring. Since 1980, the Iowa Department of Natural Resources (IDNR), the United States Environmental Protection Agency Region VII (U.S. EPA), and the University of Iowa Hygienic Laboratory (UHL) have cooperatively conducted annual statewide collections and analyses of fish for toxic contaminants. Beginning in 1983, this monitoring effort became known as the Regional Ambient Fish Tissue Monitoring Program (RAFT). Currently, the RAFT program is the only statewide fish contaminant-monitoring program in Iowa. Historically, the data generated from the RAFT program have enabled IDNR to document temporal changes in contaminant levels and to identify Iowa lakes and rivers where high levels of contaminants in fish potentially threaten the health of fish-consuming Iowans (see IDNR 2006a). The Iowa RAFT monitoring program incorporates four different types of monitoring sites: 1) status, 2) trend, 3) random and 4) follow-up.

2005 Regional Ambient Fish Tissue Monitoring Program Summary of Analyses

To supplement other environmental monitoring programs and to protect the health of people consuming fish from waters within this state, the state of Iowa conducts fish tissue monitoring. Since 1980, the Iowa Department of Natural Resources (IDNR), the United States Environmental Protection Agency Region VII (U.S. EPA), and the University of Iowa Hygienic Laboratory (UHL) have cooperatively conducted annual statewide collections and analyses of fish for toxic contaminants. Beginning in 1983, this monitoring effort became known as the Regional Ambient Fish Tissue Monitoring Program (the RAFT program). Currently, the RAFT program is the only statewide fish contaminant-monitoring program in Iowa. Historically, the data generated from the RAFT program have enabled IDNR to document temporal changes in contaminant levels and to identify Iowa lakes and rivers where high levels of contaminants in fish potentially threaten the health of fish-consuming Iowans. The Iowa RAFT monitoring program incorporates three different types of monitoring sites: 1) status, 2) trend, and 3) follow-up.

2004 Regional Ambient Fish Tissue Monitoring Program Summary of Analyses

To supplement other environmental monitoring programs and to protect the health of people consuming fish from waters within this state, the state of Iowa conducts fish tissue monitoring. Since 1980, the Iowa Department of Natural Resources (IDNR), the United States Environmental Protection Agency Region VII (U.S. EPA), and the University of Iowa Hygienic Laboratory (UHL) have cooperatively conducted annual statewide collections and analyses of fish for toxic contaminants. Beginning in 1983, this monitoring effort became the Regional Ambient Fish Tissue Monitoring Program (the RAFT program). Currently, the RAFT program is the only statewide fish contaminant-monitoring program in Iowa. Historically, the data generated from the RAFT program have enabled IDNR to document temporal changes in contaminant levels and to identify Iowa lakes and rivers where high levels of contaminants in fish potentially threaten the health of fish-consuming Iowans. The Iowa RAFT monitoring program incorporates three different but equally important types of monitoring sites: 1) status, 2) trend, and 3) follow-up.

2003 Regional Ambient Fish Tissue Monitoring Program; Summary of Analyses

To supplement other environmental monitoring programs and to protect the health of people consuming fish from waters within this state, the state of Iowa conducts fish tissue monitoring. Since 1980, the Iowa Department of Natural Resources (IDNR), the United States Environmental Protection Agency Region VII (U.S. EPA), and the University of Iowa Hygienic Laboratory (UHL) have cooperatively conducted annual statewide collections and analyses of fish for toxic contaminants. Beginning in 1983, this monitoring effort became the Regional Ambient Fish Tissue Monitoring Program (the RAFT program). Currently, the RAFT program is the only statewide fish contaminant-monitoring program in Iowa. Historically, the data generated from the RAFT program have enabled IDNR to document temporal changes in contaminant levels and to identify Iowa lakes and rivers where high levels of contaminants in fish potentially threaten the health of Iowans consuming fish. The Iowa RAFT monitoring program incorporates three different but equally important types of monitoring sites: 1) status, 2) trend, and 3) follow-up.

2002 Regional Ambient Fish Tissue Monitoring Program Summary of Analyses

To supplement other environmental monitoring programs and to protect the health of people consuming fish from waters within this state, the state of Iowa conducts fish tissue monitoring. Since 1980, the Iowa Department of Natural Resources (IDNR), the United States Environmental Protection Agency Region VII (U.S. EPA), and the University of Iowa Hygienic Laboratory (UHL) have cooperatively conducted annual statewide collections and analyses of fish for toxic contaminants. Beginning in 1983, this monitoring effort became the Regional Ambient Fish Tissue Monitoring Program (the RAFT program). Currently, the RAFT program is the only statewide fish contaminant-monitoring program in Iowa. Historically, the data generated from the RAFT program have enabled IDNR to document temporal changes in contaminant levels and to identify Iowa lakes and rivers where high levels of contaminants in fish potentially threaten the health of fish consuming Iowans. The Iowa RAFT monitoring program incorporates three different but equally important types of monitoring sites: 1) status, 2) trend, and 3) follow-up.

2001 Regional Ambient Fish Tissue Monitoring Program; Summary of Analyses

To supplement other environmental monitoring programs and to protect the health of people consuming fish from waters within this state, the state of Iowa conducts fish tissue monitoring. Since 1980, the Iowa Department of Natural Resources (IDNR), the United States Environmental Protection Agency Region VII (U.S. EPA), and the University of Iowa Hygienic Laboratory (UHL) have cooperatively conducted annual statewide collections and analyses of fish for toxic contaminants. Beginning in 1983, this monitoring effort became the Regional Ambient Fish Tissue Monitoring Program (the RAFT program). Currently, the RAFT program is the only statewide fish contaminant-monitoring program in Iowa. Historically, the data generated from the RAFT program have enabled IDNR to document temporal changes in contaminant levels and to identify Iowa lakes and rivers where high levels of contaminants in fish potentially threaten the health of fish consuming Iowans.

Blockade of the renin-angiotensin system and renal tissue oxygenation as measured with BOLD-MRI in patients with type 2 diabetes.

AIM: To assess whether blockade of the renin-angiotensin system (RAS), a recognized strategy to prevent the progression of diabetic nephropathy, affects renal tissue oxygenation in type 2 diabetes mellitus (T2DM) patients. METHODS: Prospective randomized 2-way cross over study; T2DM patients with (micro)albuminuria and/or hypertension underwent blood oxygenation level-dependent magnetic resonance imaging (BOLD-MRI) at baseline, after one month of enalapril (20mgqd), and after one month of candesartan (16mgqd). Each BOLD-MRI was performed before and after the administration of furosemide. The mean R2* (=1/T2*) values in the medulla and cortex were calculated, a low R2* indicating high tissue oxygenation. RESULTS: Twelve patients (mean age: 60±11 years, eGFR: 62±22ml/min/1.73m(2)) completed the study. Neither chronic enalapril nor candesartan intake modified renal cortical or medullary R2* levels. Furosemide significantly decreased cortical and medullary R2* levels suggesting a transient increase in renal oxygenation. Medullary R2* levels correlated positively with urinary sodium excretion and systemic blood pressure, suggesting lower renal oxygenation at higher dietary sodium intake and blood pressure; cortical R2* levels correlated positively with glycemia and HbA1c. CONCLUSION: RAS blockade does not seem to increase renal tissue oxygenation in T2DM hypertensive patients. The response to furosemide and the association with 24h urinary sodium excretion emphasize the crucial role of renal sodium handling as one of the main determinants of renal tissue oxygenation.

3D culture of postnatal retinal stem cells using self assembling polymers

PURPOSE We have previously shown that retinal stem cells (RSCs) can be isolated from the radial glia population of the newborn mouse retina (Angénieux et al., 2006). These RSCs have a great capacity to renew and to generate a large number of neurons including cells differentiated towards the photoreceptor lineage (Mehri-Soussi et al., 2006). However, recent published results from our lab revealed that such cells have a poor integration and survival rate after grafting. The uncontrolled environment of a retina seems to prevent good integration and survival after grafting in vivo. To bypass this problem, we are evaluating the possibility of generating in vitro a hemi-retinal tissue before transplantation. METHODS RSC were expanded and cells passaged <10 were seeded in a solution containing poly-ethylene-glycol (PEG) polymer based hydrogels crosslinked with peptides that are chosen to be substrates for matrix metalloproteinases. Various doses of cross linkers peptides allowing connections between PEG polymers were tested. Different growth factors were studied to stimulate cell proliferation and differentiation. RESULTS Cells survived only in the presence of EGF and FGF-2 and generated colonies with a sphere shape. No cells migrated within the gel. To improve the migration and the repartition of the cells in the gels, the integrin ligand RGDSP was added into the gel. In the presence of FGF-2 and EGF, newly formed cell clusters appeared by cell proliferation within several days, but again no outspreading of cells was observed. No difference was even seen when the stiffness of the hydrogels or the concentration of the integrin ligand RGDSP were changed. However, our preliminary results show that RSCs still form spheres when laminin is entrapped in the gel, but they started to spread out having a neuronal morphology after around 2 weeks. The neuronal population was assessed by the presence of the neuronal marker b-tubulin-III. This differentiation was achieved after successive steps of stimulations including FGF-2 and EGF, and then only FGF-2. Glial cells were also present. Further characterizations are under process. CONCLUSIONS RSC can be grown in 3D. Preliminary results show that neuronal cell phenotype acquisition can be instructed by exogenous stimulations and factors linked to the gel. Further developments are necessary to form a homogenous tissue containing retinal cells.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

The JNK inhibitor XG-102 protects from ischemic damage with delayed intravenous administration also in the presence of recombinant tissue plasminogen activator.

BACKGROUND: XG-102 (formerly D-JNKI1), a TAT-coupled dextrogyre peptide which selectively inhibits the c-Jun N-terminal kinase, is a powerful neuroprotectant in mouse models of middle cerebral artery occlusion (MCAo) with delayed intracerebroventricular injection. We aimed to determine whether this neuroprotection could also be achieved by intravenous injection of XG-102, which is a more feasible approach for future use in stroke patients. We also tested the compatibility of the compound with recombinant tissue plasminogen activator (rtPA), commonly used for intravenous thrombolysis and known to enhance excitotoxicity. METHODS: Male ICR-CD1 mice were subjected to a 30-min-suture MCAo. XG-102 was injected intravenously in a single dose, 6 h after ischemia. Hippocampal slice cultures were subjected to oxygen (5%) and glucose (1 mM) deprivation for 30 min. rtPA was added after ischemia and before XG-102 administration, both in vitro and in vivo. RESULTS: The lowest intravenous dose achieving neuroprotection was 0.0003 mg/kg, which reduced the infarct volume after 48 h from 62 +/- 19 mm(3) (n = 18) for the vehicle-treated group to 18 +/- 9 mm(3) (n = 5, p &lt; 0.01). The behavioral outcome was also significantly improved at two doses. Addition of rtPA after ischemia enhanced the ischemic damage both in vitro and in vivo, but XG-102 was still able to induce a significant neuroprotection. CONCLUSIONS: A single intravenous administration of XG-102 several hours after ischemia induces a powerful neuroprotection. XG-102 protects from ischemic damage in the presence of rtPA. The feasibility of systemic administration of this promising compound and its compatibility with rtPA are important steps for its development as a drug candidate in ischemic stroke.

Study of the impact of tissue density heterogeneities on 3-dimensional abdominal dosimetry: comparison between dose kernel convolution and direct monte carlo methods.

Dose kernel convolution (DK) methods have been proposed to speed up absorbed dose calculations in molecular radionuclide therapy. Our aim was to evaluate the impact of tissue density heterogeneities (TDH) on dosimetry when using a DK method and to propose a simple density-correction method. METHODS: This study has been conducted on 3 clinical cases: case 1, non-Hodgkin lymphoma treated with (131)I-tositumomab; case 2, a neuroendocrine tumor treatment simulated with (177)Lu-peptides; and case 3, hepatocellular carcinoma treated with (90)Y-microspheres. Absorbed dose calculations were performed using a direct Monte Carlo approach accounting for TDH (3D-RD), and a DK approach (VoxelDose, or VD). For each individual voxel, the VD absorbed dose, D(VD), calculated assuming uniform density, was corrected for density, giving D(VDd). The average 3D-RD absorbed dose values, D(3DRD), were compared with D(VD) and D(VDd), using the relative difference Δ(VD/3DRD). At the voxel level, density-binned Δ(VD/3DRD) and Δ(VDd/3DRD) were plotted against ρ and fitted with a linear regression. RESULTS: The D(VD) calculations showed a good agreement with D(3DRD). Δ(VD/3DRD) was less than 3.5%, except for the tumor of case 1 (5.9%) and the renal cortex of case 2 (5.6%). At the voxel level, the Δ(VD/3DRD) range was 0%-14% for cases 1 and 2, and -3% to 7% for case 3. All 3 cases showed a linear relationship between voxel bin-averaged Δ(VD/3DRD) and density, ρ: case 1 (Δ = -0.56ρ + 0.62, R(2) = 0.93), case 2 (Δ = -0.91ρ + 0.96, R(2) = 0.99), and case 3 (Δ = -0.69ρ + 0.72, R(2) = 0.91). The density correction improved the agreement of the DK method with the Monte Carlo approach (Δ(VDd/3DRD) < 1.1%), but with a lesser extent for the tumor of case 1 (3.1%). At the voxel level, the Δ(VDd/3DRD) range decreased for the 3 clinical cases (case 1, -1% to 4%; case 2, -0.5% to 1.5%, and -1.5% to 2%). No more linear regression existed for cases 2 and 3, contrary to case 1 (Δ = 0.41ρ - 0.38, R(2) = 0.88) although the slope in case 1 was less pronounced. CONCLUSION: This study shows a small influence of TDH in the abdominal region for 3 representative clinical cases. A simple density-correction method was proposed and improved the comparison in the absorbed dose calculations when using our voxel S value implementation.