507 research outputs found
Thermodynamics of Large N Gauge Theories with Chemical Potentials in a 1/D Expansion
In order to understand thermodynamical properties of N D-branes with chemical
potentials associated with R-symmetry charges, we study a one dimensional large
N gauge theory (bosonic BFSS type model) as a first step. This model is
obtained through a dimensional reduction of a 1+D dimensional SU(N) Yang-Mills
theory and we use a 1/D expansion to investigate the phase structure. We find
three phases in the \mu-T plane. We also show that all the adjoint scalars
condense at large D and obtain a mass dynamically. This dynamical mass protects
our model from the usual perturbative instability of massless scalars in a
non-zero chemical potential. We find that the system is at least meta-stable
for arbitrary large values of the chemical potentials in D \to \infty limit. We
also explore the existence of similar condensation in higher dimensional gauge
theories in a high temperature limit. In 2 and 3 dimensions, the condensation
always happens as in one dimensional case. On the other hand, if the dimension
is higher than 4, there is a critical chemical potential and the condensation
happens only if the chemical potentials are below it.Comment: 37 pages, 4 figures; v2: minor corrections, references added; v3:
minor corrections, to appear in JHE
Mono-dispersed Functional Polymeric Nanocapsules with Multi-lacuna via Soapless Microemulsion Polymerization with Spindle-like α-Fe2O3Nanoparticles as Templates
The mono-dispersed crosslinked polymeric multi-lacuna nanocapsules (CP(St–OA) nanocapsules) about 40 nm with carboxylic groups on their inner and outer surfaces were fabricated in the present work. The small conglomerations of the oleic acid modified spindle-like α-Fe2O3nanoparticles (OA–Fe2O3) were encapsulated in the facile microemulsion polymerization with styrene (St) as monomer and divinyl benzene (DVB) as crosslinker. Then the templates, small conglomerations of OA–Fe2O3, were etched with HCl in tetrahydrofuran (THF). The surface carboxylic groups of the crosslinked polymeric multi-lacuna nanocapsules were validated by the Zeta potential analysis
Soil Contamination Interpretation by the Use of Monitoring Data Analysis
The presented study deals with the interpretation of soil quality monitoring data using hierarchical cluster analysis (HCA) and principal components analysis (PCA). Both statistical methods contributed to the correct data classification and projection of the surface (0–20 cm) and subsurface (20–40 cm) soil layers of 36 sampling sites in the region of Burgas, Bulgaria. Clustering of the variables led to formation of four significant clusters corresponding to possible sources defining the soil quality like agricultural activity, industrial impact, fertilizing, etc. Two major clusters were found to explain the sampling site locations according to soil composition—one cluster for coastal and mountain sites and another—for typical rural and industrial sites. Analogous results were obtained by the use of PCA. The advantage of the latter was the opportunity to offer more quantitative interpretation of the role of identified soil quality sources by the level of explained total variance. The score plots and the dendrogram of the sampling sites indicated a relative spatial homogeneity according to geographical location and soil layer depth. The high-risk areas and pollution profiles were detected and visualized using surface maps based on Kriging algorithm
Genomic Organization, Tissue Distribution and Functional Characterization of the Rat Pate Gene Cluster
The cysteine rich prostate and testis expressed (Pate) proteins identified till date are thought to resemble the three fingered protein/urokinase-type plasminogen activator receptor proteins. In this study, for the first time, we report the identification, cloning and characterization of rat Pate gene cluster and also determine the expression pattern. The rat Pate genes are clustered on chromosome 8 and their predicted proteins retained the ten cysteine signature characteristic to TFP/Ly-6 protein family. PATE and PATE-F three dimensional protein structure was found to be similar to that of the toxin bucandin. Though Pate gene expression is thought to be prostate and testis specific, we observed that rat Pate genes are also expressed in seminal vesicle and epididymis and in tissues beyond the male reproductive tract. In the developing rats (20–60 day old), expression of Pate genes seem to be androgen dependent in the epididymis and testis. In the adult rat, androgen ablation resulted in down regulation of the majority of Pate genes in the epididymides. PATE and PATE-F proteins were found to be expressed abundantly in the male reproductive tract of rats and on the sperm. Recombinant PATE protein exhibited potent antibacterial activity, whereas PATE-F did not exhibit any antibacterial activity. Pate expression was induced in the epididymides when challenged with LPS. Based on our results, we conclude that rat PATE proteins may contribute to the reproductive and defense functions
Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble
<p>Abstract</p> <p>Background</p> <p>Automated, image based high-content screening is a fundamental tool for discovery in biological science. Modern robotic fluorescence microscopes are able to capture thousands of images from massively parallel experiments such as RNA interference (RNAi) or small-molecule screens. As such, efficient computational methods are required for automatic cellular phenotype identification capable of dealing with large image data sets. In this paper we investigated an efficient method for the extraction of quantitative features from images by combining second order statistics, or Haralick features, with curvelet transform. A random subspace based classifier ensemble with multiple layer perceptron (MLP) as the base classifier was then exploited for classification. Haralick features estimate image properties related to second-order statistics based on the grey level co-occurrence matrix (GLCM), which has been extensively used for various image processing applications. The curvelet transform has a more sparse representation of the image than wavelet, thus offering a description with higher time frequency resolution and high degree of directionality and anisotropy, which is particularly appropriate for many images rich with edges and curves. A combined feature description from Haralick feature and curvelet transform can further increase the accuracy of classification by taking their complementary information. We then investigate the applicability of the random subspace (RS) ensemble method for phenotype classification based on microscopy images. A base classifier is trained with a RS sampled subset of the original feature set and the ensemble assigns a class label by majority voting.</p> <p>Results</p> <p>Experimental results on the phenotype recognition from three benchmarking image sets including HeLa, CHO and RNAi show the effectiveness of the proposed approach. The combined feature is better than any individual one in the classification accuracy. The ensemble model produces better classification performance compared to the component neural networks trained. For the three images sets HeLa, CHO and RNAi, the Random Subspace Ensembles offers the classification rates 91.20%, 98.86% and 91.03% respectively, which compares sharply with the published result 84%, 93% and 82% from a multi-purpose image classifier WND-CHARM which applied wavelet transforms and other feature extraction methods. We investigated the problem of estimation of ensemble parameters and found that satisfactory performance improvement could be brought by a relative medium dimensionality of feature subsets and small ensemble size.</p> <p>Conclusions</p> <p>The characteristics of curvelet transform of being multiscale and multidirectional suit the description of microscopy images very well. It is empirically demonstrated that the curvelet-based feature is clearly preferred to wavelet-based feature for bioimage descriptions. The random subspace ensemble of MLPs is much better than a number of commonly applied multi-class classifiers in the investigated application of phenotype recognition.</p
Optimization of xylanase production by filamentous fungi in solid state fermentation and scale-up to horizontal tube bioreactor
Five microorganisms, namely Aspergillus niger CECT 2700, A. niger CECT 2915, A. niger CECT 2088, Aspergillus terreus CECT 2808, and Rhizopus stolonifer CECT 2344, were grown on corncob to produce cell wall polysaccharide-degrading enzymes, mainly xylanases, by solid-state fermentation (SSF). A. niger CECT 2700 produced the highest amount of xylanases of 504±7 U/g dry corncob (dcc) after 3 days of fermentation. The optimization of the culture broth (5.0 g/L NaNO3, 1.3 g/L (NH4)2SO4, 4.5 g/L KH2PO4, and 3 g/L yeast extract) and operational conditions (5 g of bed loading, using an initial substrate to moistening medium of 1:3.6 (w/v)) allowed increasing the predicted maximal xylanase activity up to 2,452.7 U/g dcc. However, different pretreatments of materials, including destarching, autoclaving, microwave, and alkaline treatments, were detrimental.
Finally, the process was successfully established in a laboratory-scale horizontal tube biore- actor, achieving the highest xylanase activity (2,926 U/g dcc) at a flow rate of 0.2 L/min. The result showed an overall 5.8-fold increase in xylanase activity after optimization of culture media, operational conditions, and scale-up.We are grateful to the Spanish Ministry of Science and Innovation for the financial support of this work (project CTQ2011-28967), which has partial financial support from the FEDER funds of the European Union; to the Leonardo da Vinci Programme for founding the stay of Felisbela Oliveira in Vigo University; to MAEC-AECID (Spanish Government) for the financial support for Perez-Bibbins, B. and to Spanish Ministry of Education, Culture and Sports for Perez-Rodriguez's FPU; and to Solla E. and Mendez J. (CACTI-University of Vigo) for their excellent technical assistance in microscopy
High Resolution Methylome Map of Rat Indicates Role of Intragenic DNA Methylation in Identification of Coding Region
DNA methylation is crucial for gene regulation and maintenance of genomic stability. Rat has been a key model system in understanding mammalian systemic physiology, however detailed rat methylome remains uncharacterized till date. Here, we present the first high resolution methylome of rat liver generated using Methylated DNA immunoprecipitation and high throughput sequencing (MeDIP-Seq) approach. We observed that within the DNA/RNA repeat elements, simple repeats harbor the highest degree of methylation. Promoter hypomethylation and exon hypermethylation were common features in both RefSeq genes and expressed genes (as evaluated by proteomic approach). We also found that although CpG islands were generally hypomethylated, about 6% of them were methylated and a large proportion (37%) of methylated islands fell within the exons. Notably, we obeserved significant differences in methylation of terminal exons (UTRs); methylation being more pronounced in coding/partially coding exons compared to the non-coding exons. Further, events like alternate exon splicing (cassette exon) and intron retentions were marked by DNA methylation and these regions are retained in the final transcript. Thus, we suggest that DNA methylation could play a crucial role in marking coding regions thereby regulating alternative splicing. Apart from generating the first high resolution methylome map of rat liver tissue, the present study provides several critical insights into methylome organization and extends our understanding of interplay between epigenome, gene expression and genome stability
Design considerations in a sib-pair study of linkage for susceptibility loci in cancer
<p>Abstract</p> <p>Background</p> <p>Modern approaches to identifying new genes associated with disease allow very fine analysis of associaton and can be performed in population based case-control studies. However, the sibpair design is still valuable because it requires few assumptions other than acceptably high penetrance to identify genetic loci.</p> <p>Methods</p> <p>We conducted simulation studies to assess the impact of design factors on relative efficiency for a linkage study of colorectal cancer. We considered two test statistics, one comparing the mean IBD probability in affected pairs to its null value of 0.5, and one comparing the mean IBD probabilities between affected and discordant pairs. We varied numbers of parents available, numbers of affected and unaffected siblings, reconstructing the genotype of an unavailable affected sibling by a spouse and offspring, and elimination of sibships where the proband carries a mutation at another locus.</p> <p>Results</p> <p>Power and efficiency were most affected by the number of affected sibs, the number of sib pairs genotyped, and the risk attributable to linked and unlinked loci. Genotyping unaffected siblings added little power for low penetrance models, but improved validity of tests when there was genetic heterogeneity and for multipoint testing. The efficiency of the concordant-only test was nearly always better than the concordant-discordant test. Replacement of an unavailable affected sibling by a spouse and offspring recovered some linkage information, particularly if several offspring were available. In multipoint analysis, the concordant-only test was showed a small anticonservative bias at 5 cM, while the multipoint concordant-discordant test was generally the most powerful test, and was not biased away from the null at 5 cM.</p> <p>Conclusion</p> <p>Genotyping parents and unaffected siblings is useful for detecting genotyping errors and if allele frequencies are uncertain. If adequate allele frequency data are available, we suggest a single-point affecteds-only analysis for an initial scan, followed by a multipoint analysis of affected and unaffected members of all available sibships with additional markers around initial hits.</p
Genome-Wide Identification of Molecular Pathways and Biomarkers in Response to Arsenic Exposure in Zebrafish Liver
10.1371/journal.pone.0068737PLoS ONE87-POLN
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