Degradation of haloaromatic compounds

An ever increasing number of halogenated organic compounds has been produced by industry in the last few decades. These compounds are employed as biocides, for synthetic polymers, as solvents, and as synthetic intermediates. Production figures are often incomplete, and total production has frequently to be extrapolated from estimates for individual countries. Compounds of this type as a rule are highly persistent against biodegradation and belong, as "recalcitrant" chemicals, to the class of so-called xenobiotics. This term is used to characterise chemical substances which have no or limited structural analogy to natural compounds for which degradation pathways have evolved over billions of years. Xenobiotics frequently have some common features. e.g. high octanol/water partitioning coefficients and low water solubility which makes for a high accumulation ratio in the biosphere (bioaccumulation potential). Recalcitrant compounds therefore are found accumulated in mammals, especially in fat tissue, animal milk supplies and also in human milk. Highly sophisticated analytical techniques have been developed for the detection of organochlorines at the trace and ultratrace level

Impact Of Amino Acid Regimen on Milk Nutrient Yields by Sows Differing in Genetic Capacity for Lean Tissue Growth

The impact of dietary amino acid regimen on the milk nutrient yield of sows differing in genetic capacity for lean tissue growth was determined. Primiparous sows with a high (.77 to .85 lb/day) or low (.53 to .62 lb/day) genetic capacity for lean tissue growth from 40 to 240 pounds body weight were evaluated. During lactation, sows were offered daily 14.3 pounds of one of four fortified corn-soybean meal diets containing .58, .77, .96 and 1.15% lysine (L). Litters were standardized to 14 pigs within eight hours postpartum. Milk yield (via a deuterium oxide dilution technique) and composition were determined over four-day intervals from day 2 to 26 postpartum. Based on net feed consumption and the composition of mobilized body tissues (via a comparative slaughter technique), the daily supplies of lysine and metabolizable energy (ME) available for milk synthesis were calculated. The bodies of high lean growth (LG) sows possessed more proteinaceous tissues and protein and less fat tissue and lipid than low LG sows at the initiation of lactation. During lactation (days 2 to 28 postpartum), high LG sows (pooled across dietary regimens) consumed more feed, mobilized more body protein, and catabolized less body lipid than low LG sows, whereas milk yields were similar between genotypes. As total daily lysine supplies (from diet and mobilized tissues) increased, daily yields of milk, milk energy, and milk lysine increased, but the magnitude of the responses were less in the high LG sows. At low dietary lysine intakes, total lysine supply was limiting milk synthesis in both genotypes. As dietary lysine intake increased, total ME supply became more limiting than lysine, particularly in the high LG sows because of their inability to provide sufficient energy from mobilized body fat tissues. Based on these data, milk, milk energy, and lysine yields of high and low lean growth genotype sows are similar when similar total supplies of lysine and energy are available. When energy supplies do not limit milk synthesis, the efficiency of utilization of digestible lysine for milk lysine production is similar between genotypes. Specifically, .85 to .87 Mcal ME and 1.95 to 2.05 grams (g) of digestible lysine are needed per pound of milk produced in sows nursing large litters. If it is assumed that each nursing pig requires daily 1.8 pounds of milk, then lactating sows require about 1.5 to 1.6 Mcal ME and 4.3 to 4.5 g of digestible lysine (5.0 to 5.3 g lysine from a cornsoy diet) for each pig nursed. Because of the limited supplies of mobilizable fat tissues in high lean growth sows, the provision of adequate dietary energy intakes to the sows is more critical in order to allow their maximum lactational capacity to be expressed.</p

Virtual Klingler Dissection: Putting Fibers into Context

Fiber tracking is a standard tool to estimate the course of major white matter tracts from diffusion tensor magnetic resonance imaging (DT-MRI) data. In this work, we aim at supporting the visual analysis of classical streamlines from fiber tracking by integrating context from anatomical data, acquired by a $T_1$-weighted MRI measurement. To this end, we suggest a novel visualization metaphor, which is based on data-driven deformation of geometry and has been inspired by a technique for anatomical fiber preparation known as Klingler dissection. We demonstrate that our method conveys the relation between streamlines and surrounding anatomical features more effectively than standard techniques like slice images and direct volume rendering. The method works automatically, but its GPU-based implementation allows for additional, intuitive interaction

Identification and in vivoefficacy assessment of approved orally bioavailable human host protein-targeting drugs with broad anti-influenza a activity

10.3389/fimmu.2019.01097Frontiers in Immunology10JUN109

Endocannabinoids and related lipids in serum from patients with amyotrophic lateral sclerosis.

BACKGROUND: The goals of this study were to determine whether serum concentrations of endocannabinoids (eCB) and related lipids predict disease status in patients with amyotrophic lateral sclerosis (ALS) relative to healthy controls, and whether concentrations correlate with disease duration and severity. METHODS: Serum concentrations of the eCBs 2-arachidonoylglycerol (2-AG) and N-arachidonoylethanolamine (AEA), and related lipids palmitoylethanolamine (PEA), oleoylethanolamine (OEA), and 2-oleoylglycerol (2-OG), were measured in samples from 47 patients with ALS and 19 healthy adults. Hierarchical binary logistic and linear regression analyses assessed whether lipid concentrations predicted disease status (ALS or healthy control), duration, or severity. RESULTS: Binary logistic regression revealed that, after controlling for age and gender, 2-AG, 2-OG and AEA concentrations were unique predictors of the presence of ALS, demonstrating odds ratios of 0.86 (P = .039), 1.03 (P = .023), and 42.17 (P = .026), respectively. When all five lipids and covariates (age, sex, race, ethnicity, body mass index, presence of a feeding tube) were included, the resulting model had an overall classification accuracy of 92.9%. Hierarchical linear regression analyses indicated that in patients with ALS, AEA and OEA inversely correlated with disease duration (P = .030 and .031 respectively), while PEA demonstrated a positive relationship with disease duration (P = .013). None of the lipids examined predicted disease severity. CONCLUSIONS: These findings support previous studies indicating significant alterations in concentrations of circulating lipids in patients with ALS. They suggest that arachidonic and oleic acid containing small lipids may serve as biomarkers for identifying the presence and duration of this disease

Association of variants in gastric inhibitory polypeptide receptor gene with impaired glucose homeostasis in obese children and adolescents from Berlin.

OBJECTIVE: In the past 20 years, obesity has become a major health problem due to associated diseases like type 2 diabetes mellitus. The gastric inhibitory polypeptide receptor (GIPR) modulates body weight and glucose homeostasis and, therefore, represents an interesting candidate gene for obesity and the comorbidity impaired glucose homeostasis. Recently, a GIPR variation was found to be associated with impaired insulin response in humans. In this study, we screened the GIPR gene for mutations and examined the association between three single-nucleotide polymorphisms (SNPs; rs8111428, rs2302382, rs1800437) and childhood obesity, as well as impaired glucose homeostasis. METHODS: The coding region of the GIPR was screened for mutations by direct sequencing. We genotyped three known SNPs in 2280 healthy normal weight (1696) and obese (584) children and adolescents. Genotyping was performed using the SNaPshot protocol, the iplex, and matrix-assisted laser desorption ionization time-of-flight spectrometry technique. Obesity was defined by a body mass index SDS above 2; homeostatic model assessment was calculated. RESULTS: No evidence for an association was found between the SNPs and the obesity phenotype. Significant association was found between the minor allele C of the SNP rs1800437 and elevated homeostasis model of insulin resistance values (P=0.001). No further sequence variations in the GIPR were found to be associated with childhood obesity. CONCLUSION: Variations of the GIPR sequence are not associated with childhood obesity. This study points to a potential role for rs1800437 in glucose homeostasis. Further studies are necessary to confirm these results

Multifield-Graphs: An Approach to Visualizing Correlations in Multifield Scalar Data

We present an approach to visualizing correlations in 3D multifield scalar data. The core of our approach is the computation of correlation fields, which are scalar fields containing the local correlations of subsets of the multiple fields. While the visualization of the correlation fields can be done using standard 3D volume visualization techniques, their huge number makes selection and handling a challenge. We introduce the Multifield-Graph to give an overview of which multiple fields correlate and to show the strength of their correlation. This information guides the selection of informative correlation fields for visualization. We use our approach to visually analyze a number of real and synthetic multifield datasets

Visualization of White Matter Tracts with Wrapped Streamlines

Diffusion tensor imaging is a magnetic resonance imaging method which has gained increasing importance in neuroscience and especially in neurosurgery. It acquires diffusion properties represented by a symmetric 2nd order tensor for each voxel in the gathered dataset. From the medical point of view, the data is of special interest due to different diffusion characteristics of varying brain tissue allowing conclusions about the underlying structures such as white matter tracts. An obvious way to visualize this data is to focus on the anisotropic areas using the major eigenvector for tractography and rendering lines for visualization of the simulation results. Our approach extends this technique to avoid line representation since lines lead to very complex illustrations and furthermore are mistakable. Instead, we generate surfaces wrapping bundles of lines. Thereby, a more intuitive representation of different tracts is achieved