Mapping the Genetic Variation of Regional Brain Volumes as Explained by All Common SNPs from the ADNI Study

Typically twin studies are used to investigate the aggregate effects of genetic and environmental influences on brain phenotypic measures. Although some phenotypic measures are highly heritable in twin studies, SNPs (single nucleotide polymorphisms) identified by genome-wide association studies (GWAS) account for only a small fraction of the heritability of these measures. We mapped the genetic variation (the proportion of phenotypic variance explained by variation among SNPs) of volumes of pre-defined regions across the whole brain, as explained by 512,905 SNPs genotyped on 747 adult participants from the Alzheimer''s Disease Neuroimaging Initiative (ADNI). We found that 85% of the variance of intracranial volume (ICV) (p = 0.04) was explained by considering all SNPs simultaneously, and after adjusting for ICV, total grey matter (GM) and white matter (WM) volumes had genetic variation estimates near zero (p = 0.5). We found varying estimates of genetic variation across 93 non-overlapping regions, with asymmetry in estimates between the left and right cerebral hemispheres. Several regions reported in previous studies to be related to Alzheimer''s disease progression were estimated to have a large proportion of volumetric variance explained by the SNPs.     

Optimization of parameters for improvement of phenol degradation by Rhodococcus UKMP-5M using response surface methodology

Phenol is a toxic compound and is one of the major pollutants contained in the waste water from petroleum and its downstream industries. Response surface methodology (RSM) was used to optimize medium composition and culture condition for enhancement of growth of Rhodococcus UKMP-5M and phenol degradation rate in shake flask cultures. Phenol and (NH₄)₂SO₄ concentrations as well as temperature were the most significant factors that influenced growth and phenol degradation. Central composite design (CCD) was used for optimization of these parameters with growth, and degradation rates were used as the responses. Cultivation with 0.5 g/L phenol and 0.3 g/L (NH₄)₂SO₄ and incubation at 36 °C greatly enhanced growth of Rhodococcus UKMP-5M, where the final cell concentration increased from 0.117 g/L to 0.376 g/L. On the other hand, the degradation rate was greatly increased in cultivation with 0.7 g/L phenol and 0.4 g/L (NH₄)₂SO₄ and incubation at 37 °C. In this cultivation, the time taken to degrade 1 g/L phenol in the culture was reduced from 48 h to 27 h. The model for both responses was found significant and the predicted values were found to be in a good agreement with experimental values and subsequently validated. Increases in phenol degradation rate during Rhodococcus UKMP-5M cultivation corresponded well with increasing phenol hydroxylase activity.     

Plasma Reflectarrays

This paper investigates the design of four different configurations of plasma reflectarrays. The results provide insight into different radiation characteristics of plasma reflectarrays. The proposed unit cell consists of a cubic glass box filled with argon gas energized with applied AC voltage. The reflectarray reflection coefficient phase variation is achieved by varying the plasma frequency of the energized gas. Four plasma reflectarrays for satellite applications at 12 GHz are proposed (centre feed centre beam, centre feed offset beam, offset feed centre beam, and finally, offset feed offset beam). The finite integration technique is used to analyse the plasma reflectarray.     

Intake of Farmed Atlantic Salmon Fed Soybean Oil Increases Insulin Resistance and Hepatic Lipid Accumulation in Mice

Background

To ensure sustainable aquaculture, fish derived raw materials are replaced by vegetable ingredients. Fatty acid composition and contaminant status of farmed Atlantic salmon (Salmo salar L.) are affected by the use of plant ingredients and a spillover effect on consumers is thus expected. Here we aimed to compare the effects of intake of Atlantic salmon fed fish oil (FO) with intake of Atlantic salmon fed a high proportion of vegetable oils (VOs) on development of insulin resistance and obesity in mice.

Methodology/principal findings

Atlantic salmon were fed diets where FO was partly (80%) replaced with three different VOs; rapeseed oil (RO), olive oil (OO) or soy bean oil (SO). Fillets from Atlantic salmon were subsequently used to prepare Western diets (WD) for a mouse feeding trial. Partial replacement of FO with VOs reduced the levels of polychlorinated biphenyls (PCB) and dichloro-diphenyl-tricloroethanes (DDT) with more than 50% in salmon fillets, in WDs containing the fillets, and in white adipose tissue from mice consuming the WDs. Replacement with VOs, SO in particular, lowered the n−3 polyunsaturated fatty acid (PUFA) content and increased n−6 PUFA levels in the salmon fillets, in the prepared WDs, and in red blood cells collected from mice consuming the WDs. Replacing FO with VO did not influence obesity development in the mice, but replacement of FO with RO improved glucose tolerance. Compared with WD-FO fed mice, feeding mice WD-SO containing lower PCB and DDT levels but high levels of linoleic acid (LA), exaggerated insulin resistance and increased accumulation of fat in the liver.

Conclusion/Significance

Replacement of FO with VOs in aqua feed for farmed salmon had markedly different spillover effects on metabolism in mice. Our results suggest that the content of LA in VOs may be a matter of concern that warrants further investigation.     

Biochemical study on modifying role of variants of leptin gene and its receptor on serum leptin levels in breast cancer

Molecular Biology Reports - The leptin is discharged from breast adipose tissue and is overexpressed in breast cancer (BC). Conflicting relation of leptin with BC was reported. We investigated this...     

Expression of the Arcelin 1 gene from Phaseolus vulgaris L. in cowpea seeds (Vigna unguiculata L.) confers bruchid resistance

Persistent decrease in the productivity of cowpea (Vigna unguiculata L.) has been partly due to attack by bruchids including Zabrotes subfasciatus and Callosobruchus maculatus. Resistance to these insects in Phaseolus vulgaris L. has been shown to be associated with arcelins, a family of seed proteins encoded by a multigenic family of lectins on the APA locus. In this work, we report the construction of an expression vector containing Arc1 gene isolated from P. vulgaris and introduced into cowpea as a strategy to confer resistance to insect attack. Following transformation and selection, feeding experiments in which C. maculatus and Z. subfasciatus were fed with transgenic (L3 and L5) and non-transgenic (control) grains showed that introduced gene protected the transgenic line. Significant differences (p < .05 and p < .01) were found in the number of eggs laid, the number of emerging insects and the loss of grain mass in L3, compared with control, for both insects. Similar observations were made in L5 with the exception of the number of laid eggs. The strategy here described may form the basis for the development of a cowpea variety tolerant to bruchids in a crop cultivated by farmers throughout Latin America and Africa.     

Joint analysis of single-cell and bulk tissue sequencing data to infer intratumor heterogeneity

Many computational methods have been developed to discern intratumor heterogeneity (ITH) using DNA sequence data from bulk tumor samples. These methods share an assumption that two mutations arise from the same subclone if they have similar mutant allele-frequencies (MAFs), and thus it is difficult or impossible to distinguish two subclones with similar MAFs. Single-cell DNA sequencing (scDNA-seq) data can be very informative for ITH inference. However, due to the difficulty of DNA amplification, scDNA-seq data are often very noisy. A promising new study design is to collect both bulk and single-cell DNA-seq data and jointly analyze them to mitigate the limitations of each data type. To address the analytic challenges of this new study design, we propose a computational method named BaSiC (B ulk tumor a nd Si ngle C ell), to discern ITH by jointly analyzing DNA-seq data from bulk tumor and single cells. We demonstrate that BaSiC has comparable or better performance than the methods using either data type. We further evaluate BaSiC using bulk tumor and single-cell DNA-seq data from a breast cancer patient and several leukemia patients.