Villából kórházat? A József Attiláról elnevezett kórház története

<p>Preoperative difficulty, expected and actual postoperative improvement on the Catquest-9SF items by functional characteristics (N = 174)^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0169844#t004fn001" target="_blank">*</a>}.</p

MASNOVO, AMATO

To address the poorly understood mixture effects of chemicals in the marine mammal dugong, we coupled equilibrium-based passive sampling in blubber to a range of in vitro bioassays for screening mixtures of bioaccumulative chemicals. The modes of action included early effect indicators along important toxicity pathways, such as induction of xenobiotic metabolism, and some integrative indicators downstream of the molecular initiating event, such as adaptive stress responses. Activation of aryl hydrocarbon receptor (AhR) and Nrf2-mediated oxidative stress response were found to be the most prominent effects, while the p53-mediated DNA damage response and NF-κB-mediated response to inflammation were not significantly affected. Although polychlorinated dibenzo-<i>p</i>-dioxins (PCDDs) quantified in the samples accounted for the majority of AhR-mediated activity, PCDDs explained less than 5% of the total oxidative stress response, despite their known ability to activate this pathway. Altered oxidative stress response was observed with both individual chemicals and blubber extracts subject to metabolic activation by rat liver S9 fraction. Metabolic activation resulted in both enhanced and reduced toxicity, suggesting the relevance and utility of incorporating metabolic enzymes into in vitro bioassays. Our approach provides a first insight into the burden of toxicologically relevant bioaccumulative chemical mixtures in dugongs and can be applied to lipid tissue of other wildlife species

Evolution of Hepatic Glucose Metabolism: Liver-Specific Glucokinase Deficiency Explained by Parallel Loss of the Gene for Glucokinase Regulatory Protein (GCKR)

<div><p>Background</p><p>Glucokinase (GCK) plays an important role in the regulation of carbohydrate metabolism. In the liver, phosphorylation of glucose to glucose-6-phosphate by GCK is the first step for both glycolysis and glycogen synthesis. However, some vertebrate species are deficient in GCK activity in the liver, despite containing <i>GCK</i> genes that appear to be compatible with function in their genomes. Glucokinase regulatory protein (GCKR) is the most important post-transcriptional regulator of GCK in the liver; it participates in the modulation of GCK activity and location depending upon changes in glucose levels. In experimental models, loss of GCKR has been shown to associate with reduced hepatic GCK protein levels and activity.</p> <p>Methodology/Principal Findings</p><p><i>GCKR</i> genes and <i>GCKR</i>-like sequences were identified in the genomes of all vertebrate species with available genome sequences. The coding sequences of <i>GCKR</i> and <i>GCKR</i>-like genes were identified and aligned; base changes likely to disrupt coding potential or splicing were also identified.</p> <p>Conclusions/Significance</p><p><i>GCKR</i> genes could not be found in the genomes of 9 vertebrate species, including all birds. In addition, in multiple mammalian genomes, whereas <i>GCKR</i>-like gene sequences could be identified, these genes could not predict a functional protein. Vertebrate species that were previously reported to be deficient in hepatic GCK activity were found to have deleted (birds and lizard) or mutated (mammals) <i>GCKR</i> genes. Our results suggest that mutation of the <i>GCKR</i> gene leads to hepatic GCK deficiency due to the loss of the stabilizing effect of GCKR.</p> </div

Exons bearing inactivating mutation in mammalian <i>GCKR</i> genes.

<p>Exons bearing inactivating mutation in mammalian <i>GCKR</i> genes.</p

Bioenergy Potential from Food Waste in California

Food waste makes up approximately 15% of municipal solid waste generated in the United States, and 95% of food waste is ultimately landfilled. Its bioavailable carbon and nutrient content makes it a major contributor to landfill methane emissions, but also presents an important opportunity for energy recovery. This paper presents the first detailed analysis of monthly food waste generation in California at a county level, and its potential contribution to the state’s energy production. Scenarios that rely on excess capacity at existing anaerobic digester (AD) and solid biomass combustion facilities, and alternatives that allow for new facility construction, are developed and modeled. Potential monthly electricity generation from the conversion of gross food waste using a combination of AD and combustion varies from 420 to 700 MW, averaging 530 MW. At least 66% of gross high moisture solids and 23% of gross low moisture solids can be treated using existing county infrastructure, and this fraction increases to 99% of high moisture solids and 55% of low moisture solids if waste can be shipped anywhere within the state. Biogas flaring practices at AD facilities can reduce potential energy production by 10 to 40%

Genomic neighborhoods around vertebrate <i>GCKR</i> genes.

<p>Relative order and orientation of genes near the <i>GCKR</i> genes in human, chicken, Chinese softshell turtle, coelacanth, zebrafish and takifugu genomes. Gene names, as annotated in the human genome, are shown above the arrows, with the arrowhead indicating direction of transcription. Gene sizes and distance between genes are not to scale. Human is representative of the gene organization in mammals, while chicken is representative of birds. <i>GCKR</i> gene was not found in bird genomes. In fish, two distinct gene organizations were found – one found in zebrafish, and a second found in other fish genomes and represented by takifugu. The Chinese softshell turtle GCKR gene was distributed over two genomic contigs, with the slashes (/) indicating the ends of contigs.</p

Vertebrate <i>GCKR</i> genes.

*<p>Predicted genes have a single frame shift mutation that may be a sequencing error.</p

Evolution of <i>GCKR</i> genes and hepatic GCK activity in vertebrates.

<p>Summary of information on the structure of <i>GCKR</i> genes and hepatic GCK activity are placed on a phylogeny of vertebrates with available genome sequences (with the common names of the species shown on the right). Higher-level taxonomic groups of species are indicated to the right, with their composition indicated by the vertical bars. The phylogenetic relationship is from Ensembl (<a href="http://www.ensembl.org" target="_blank">www.ensembl.org</a>). <i>Xenopus laevis</i> is added to the tree as it has an intact <i>GCKR</i> cDNA. Genes are labeled as intact (I), likely intact (I?) or mutated (M), with the types of mutation indicated: fs = frame shift, sm = splice mutation, Δ = deletion, and Δ? = likely deletion (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0060896#pone-0060896-t002" target="_blank">Tables 2</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0060896#pone-0060896-t003" target="_blank">3</a>). The phylogenetic placement of gene inactivation events (Ψ, with type of inactivation indicated) was determined by parsimony. Possible inactivations, or events with unresolved locations (i.e., on the bird lineage), are indicated by the ? symbol. Hepatic GCK activity is from references 27-31, with Y = activity found, N = no or very low activity, and nd = not determined.</p

Relative rate tests.

1<p>– Number of unique amino acid substitutions on the lineages to species A and B when the Tasmanian devil sequence was used as the outgroup.</p>2<p>– Chi square value for the expectation that an equal number of substitutions occurred on each lineage.</p

Applicability of Passive Sampling to Bioanalytical Screening of Bioaccumulative Chemicals in Marine Wildlife

Quantification of bioaccumulative contaminants in biota is time and cost-intensive and the required extensive cleanup steps make it selective toward targeted chemical groups. Therefore tissue extracts prepared for chemical analysis are not amenable to assess the combined effects of unresolved complex mixtures. Passive equilibrium sampling with polydimethylsiloxane (PDMS) has the potential for unbiased sampling of mixtures, and the PDMS extracts can be directly dosed into cell-based bioassays. The passive sampling approach was tested by exposing PDMS to lipid-rich tissue (dugong blubber; 85% lipid) spiked with a known mixture of hydrophobic contaminants (five congeners of tetra- to octachloro-dibenzo-<i>p</i>-dioxins). The equilibrium was attained within 24 h. Lipid-PDMS partition coefficients (<i>K</i>_lip‑PDMS) ranged from 20 to 38, were independent of hydrophobicity, and within the range of those previously measured for organochlorine compounds. To test if passive sampling can be combined with bioanalysis without the need for chemical cleanup, spiked blubber-PDMS extracts were dosed into the CAFLUX bioassay, which specifically targets dioxin-like chemicals. Small quantities of lipids coextracted by the PDMS were found to affect the kinetics in the regularly applied 24-h bioassay; however, this effect was eliminated by a longer exposure period (72 h). The validated method was applied to 11 unspiked dugong blubber samples with known (native) dioxin concentrations. These results provide the first proof of concept for linking passive sampling of lipid-rich tissue with cell-based bioassays, and could be further extended to other lipid rich species and a wider range of bioanalytical end points