Characterization of subsurface media from locations up- and down-gradient of a uranium-contaminated aquifer.

The processing of sediment to accurately characterize the spatially-resolved depth profiles of geophysical and geochemical properties along with signatures of microbial density and activity remains a challenge especially in complex contaminated areas. This study processed cores from two sediment boreholes from background and contaminated core sediments and surrounding groundwater. Fresh core sediments were compared by depth to capture the changes in sediment structure, sediment minerals, biomass, and pore water geochemistry in terms of major and trace elements including pollutants, cations, anions, and organic acids. Soil porewater samples were matched to groundwater level, flow rate, and preferential flows and compared to homogenized groundwater-only samples from neighboring monitoring wells. Groundwater analysis of nearby wells only revealed high sulfate and nitrate concentrations while the same analysis using sediment pore water samples with depth was able to suggest areas high in sulfate- and nitrate-reducing bacteria based on their decreased concentration and production of reduced by-products that could not be seen in the groundwater samples. Positive correlations among porewater content, total organic carbon, trace metals and clay minerals revealed a more complicated relationship among contaminant, sediment texture, groundwater table, and biomass. The fluctuating capillary interface had high concentrations of Fe and Mn-oxides combined with trace elements including U, Th, Sr, Ba, Cu, and Co. This suggests the mobility of potentially hazardous elements, sediment structure, and biogeochemical factors are all linked together to impact microbial communities, emphasizing that solid interfaces play an important role in determining the abundance of bacteria in the sediments

Timing of Toenail Collection and Concentrations of Metals in Pancreatic Cancer. Evidence Against Disease Progression Bias

Trace elements such as cadmium, arsenic, zinc or selenium increase or decrease risk of a wide range of human diseases. Their levels in toenails may provide a measure of mid-term intake of trace elements for studies in humans. However, in biologically and clinically aggressive diseases as pancreatic cancer, the progression of the disease could modify such concentrations and produce reverse causation bias. The aim was to analyze the influence of specific time intervals between several clinical events and the collection of toenails upon concentrations of trace elements in patients with pancreatic cancer. Subjects were 118 incident cases of pancreatic adenocarcinoma prospectively recruited in eastern Spain. Toenails were collected at cancer diagnosis, and soon thereafter interviews were conducted. Information on cancer signs and symptoms was obtained from medical records and patient interviews. Levels of 12 trace elements were determined in toenail samples by inductively coupled plasma mass spectrometry. General linear models adjusting for potential confounders were applied to analyze relations between log concentrations of trace elements and the time intervals, including the interval from first symptom of cancer to toenail collection (iST). Toenail concentrations of the 12 trace elements were weakly or not influenced by the progression of the disease or the diagnostic procedures. Concentrations of aluminum were slightly higher in subjects with a longer iST (age, sex and stage adjusted geometric means: 11.44 vs. 7.75 µg/g for iST > 120 days vs. ≤ 40 days). There was a weak inverse relation of iST with concentrations of zinc and selenium (maximum differences of about 20 and 0.08 µg/g, respectively). Conclusions: concentrations of the trace elements were weakly or not influenced by the development of the disease before toenail collection. Only concentrations of aluminum increased slightly with increasing iST, whereas levels of zinc and selenium decreased weakly. Even in an aggressive disease as pancreatic cancer, toenail concentrations of trace elements may provide a valid measure of mid-term intake of trace elements, unaffected by clinical events and disease progression

Identification of Membrane Proteins in the Hyperthermophilic Archaeon Pyrococcus Furiosus Using Proteomics and Prediction Programs

Cell-free extracts from the hyperthermophilic archaeon Pyrococcus furiosus were separated into membrane and cytoplasmic fractions and each was analyzed by 2D-gel electrophoresis. A total of 66 proteins were identified, 32 in the membrane fraction and 34 in the cytoplasmic fraction. Six prediction programs were used to predict the subcellular locations of these proteins. Three were based on signal-peptides (SignalP, TargetP, and SOSUISignal) and three on transmembrane-spanning α-helices (TSEG, SOSUI, and PRED-TMR2). A consensus of the six programs predicted that 23 of the 32 proteins (72%) from the membrane fraction should be in the membrane and that all of the proteins from the cytoplasmic fraction should be in the cytoplasm. Two membrane-associated proteins predicted to be cytoplasmic by the programs are also predicted to consist primarily of transmembrane-spanning β-sheets using porin protein models, suggesting that they are, in fact, membrane components. An ATPase subunit homolog found in the membrane fraction, although predicted to be cytoplasmic, is most likely complexed with other ATPase subunits in the membrane fraction. An additional three proteins predicted to be cytoplasmic but found in the membrane fraction, may be cytoplasmic contaminants. These include a chaperone homolog that may have attached to denatured membrane proteins during cell fractionation. Omitting these three proteins would boost the membrane-protein predictability of the models to near 80%. A consensus prediction using all six programs for all 2242 ORFs in the P. furiosus genome estimates that 24% of the ORF products are found in the membrane. However, this is likely to be a minimum value due to the programs’ inability to recognize certain membrane-related proteins, such as subunits associated with membrane complexes and porin-type proteins

Multiple interactions between the alpha2C- and beta1-adrenergic receptors influence heart failure survival

<p>Abstract</p> <p>Background</p> <p>Persistent stimulation of cardiac β₁-adrenergic receptors by endogenous norepinephrine promotes heart failure progression. Polymorphisms of this gene are known to alter receptor function or expression, as are polymorphisms of the α_2C-adrenergic receptor, which regulates norepinephrine release from cardiac presynaptic nerves. The purpose of this study was to investigate possible synergistic effects of polymorphisms of these two intronless genes (<it>ADRB1 </it>and <it>ADRA2C</it>, respectively) on the risk of death/transplant in heart failure patients.</p> <p>Methods</p> <p>Sixteen sequence variations in <it>ADRA2C </it>and 17 sequence variations in <it>ADRB1 </it>were genotyped in a longitudinal study of 655 white heart failure patients. Eleven sequence variations in each gene were polymorphic in the heart failure cohort. Cox proportional hazards modeling was used to identify polymorphisms and potential intra- or intergenic interactions that influenced risk of death or cardiac transplant. A leave-one-out cross-validation method was utilized for internal validation.</p> <p>Results</p> <p>Three polymorphisms in <it>ADRA2C </it>and five polymorphisms in <it>ADRB1 </it>were involved in eight cross-validated epistatic interactions identifying several two-locus genotype classes with significant relative risks ranging from 3.02 to 9.23. There was no evidence of intragenic epistasis. Combining high risk genotype classes across epistatic pairs to take into account linkage disequilibrium, the relative risk of death or transplant was 3.35 (1.82, 6.18) relative to all other genotype classes.</p> <p>Conclusion</p> <p>Multiple polymorphisms act synergistically between the <it>ADRA2C </it>and <it>ADRB1 </it>genes to increase risk of death or cardiac transplant in heart failure patients.</p

Mathematical Model of Plasmid-Mediated Resistance to Ceftiofur in Commensal Enteric Escherichia coli of Cattle

Antimicrobial use in food animals may contribute to antimicrobial resistance in bacteria of animals and humans. Commensal bacteria of animal intestine may serve as a reservoir of resistance-genes. To understand the dynamics of plasmid-mediated resistance to cephalosporin ceftiofur in enteric commensals of cattle, we developed a deterministic mathematical model of the dynamics of ceftiofur-sensitive and resistant commensal enteric Escherichia coli (E. coli) in the absence of and during parenteral therapy with ceftiofur. The most common treatment scenarios including those using a sustained-release drug formulation were simulated; the model outputs were in agreement with the available experimental data. The model indicated that a low but stable fraction of resistant enteric E. coli could persist in the absence of immediate ceftiofur pressure, being sustained by horizontal and vertical transfers of plasmids carrying resistance-genes, and ingestion of resistant E. coli. During parenteral therapy with ceftiofur, resistant enteric E. coli expanded in absolute number and relative frequency. This expansion was most influenced by parameters of antimicrobial action of ceftiofur against E. coli. After treatment (>5 weeks from start of therapy) the fraction of ceftiofur-resistant cells among enteric E. coli, similar to that in the absence of treatment, was most influenced by the parameters of ecology of enteric E. coli, such as the frequency of transfer of plasmids carrying resistance-genes, the rate of replacement of enteric E. coli by ingested E. coli, and the frequency of ceftiofur resistance in the latter

Planck 2013 results. XX. Cosmology from Sunyaev-Zeldovich cluster counts

We present constraints on cosmological parameters using number counts as a function of redshift for a sub-sample of 189 galaxy clusters from the Planck SZ (PSZ) catalogue. The PSZ is selected through the signature of the Sunyaev--Zeldovich (SZ) effect, and the sub-sample used here has a signal-to-noise threshold of seven, with each object confirmed as a cluster and all but one with a redshift estimate. We discuss the completeness of the sample and our construction of a likelihood analysis. Using a relation between mass $M$ and SZ signal $Y$ calibrated to X-ray measurements, we derive constraints on the power spectrum amplitude $\sigma_8$ and matter density parameter $\Omega_{\mathrm{m}}$ in a flat $\Lambda$CDM model. We test the robustness of our estimates and find that possible biases in the $Y$--$M$ relation and the halo mass function are larger than the statistical uncertainties from the cluster sample. Assuming the X-ray determined mass to be biased low relative to the true mass by between zero and 30%, motivated by comparison of the observed mass scaling relations to those from a set of numerical simulations, we find that $\sigma_8=0.75\pm 0.03$, $\Omega_{\mathrm{m}}=0.29\pm 0.02$, and $\sigma_8(\Omega_{\mathrm{m}}/0.27)^{0.3} = 0.764 \pm 0.025$. The value of $\sigma_8$ is degenerate with the mass bias; if the latter is fixed to a value of 20% we find $\sigma_8(\Omega_{\mathrm{m}}/0.27)^{0.3}=0.78\pm 0.01$ and a tighter one-dimensional range $\sigma_8=0.77\pm 0.02$. We find that the larger values of $\sigma_8$ and $\Omega_{\mathrm{m}}$ preferred by Planck's measurements of the primary CMB anisotropies can be accommodated by a mass bias of about 40%. Alternatively, consistency with the primary CMB constraints can be achieved by inclusion of processes that suppress power on small scales relative to the $\Lambda$CDM model, such as a component of massive neutrinos (abridged).Comment: 20 pages, accepted for publication by A&