Semantic aware Bayesian network model for actionable knowledge discovery in linked data

The majority of the conventional mining algorithms treat the mining process as an isolated data-driven procedure and overlook the semantic of the targeted data. As a result, the generated patterns are abundant and end users cannot act upon them seamlessly. Furthermore, interdisciplinary knowledge can not be obtained from domain-specific silo of data. The emergence of Linked Data (LD) as a new model for knowledge representation, which intertwines data with its semantics, has introduced new opportunities for data miners. Accordingly, this paper proposes an ontology-based Semantic-Aware Bayesian network (BN) model. In contrast to the existing mining algorithms, the proposed model does into transform the original format of the LD set. Therefore, it not only accommodates the semantic aspects in LD, but also caters to the need of connecting different data-sets from different domains. We evaluate the proposed model on a Bone Dysplasia dataset, Experimental results show promising performance

Synergy between EngE, XynA and ManA from Clostridium cellulovorans on corn stalk, grass and pineapple pulp substrates

The synergistic interaction between various hemi/cellulolytic enzymes has become more important in order to achieve effective and optimal degradation of complex lignocellulose substrates for biofuel production. This study investigated the synergistic effect of three enzymes endoglucanase (EngE), mannanase (ManA) and xylanase (XynA) on the degradation of corn stalk, grass, and pineapple fruit pulp and determined the optimal degree of synergy between combinations of these enzymes. It was established that EngE was essential for degradation of all of the substrates, while the hemicellulases were able to contribute in a synergistic fashion to increase the activity on these substrates. Maximum specific activity and degree of synergy on the corn stalk and grass was found with EngE:XynA in a ratio of 75:25%, with a specific activity of 41.1 U/mg protein and a degree of synergy of 6.3 for corn stalk, and 44.1 U/mg protein and 3.4 for grass, respectively. The pineapple fruit pulp was optimally digested using a ManA:EngE combination in a 50:50% ratio; the specific activity and degree of synergy achieved were 52.4 U/mg protein and 2.7, respectively. This study highlights the importance of hemicellulases for the synergistic degradation of complex lignocellulose. The inclusion of a mannanase in an enzyme consortium for biomass degradation should be examined further as this study suggests that it may play an important, although mostly overlooked, role in the synergistic saccharification of lignocellulose

A Policy-Driven Large Scale Ecological Restoration: Quantifying Ecosystem Services Changes in the Loess Plateau of China

As one of the key tools for regulating human-ecosystem relations, environmental conservation policies can promote ecological rehabilitation across a variety of spatiotemporal scales. However, quantifying the ecological effects of such policies at the regional level is difficult. A case study was conducted at the regional level in the ecologically vulnerable region of the Loess Plateau, China, through the use of several methods including the Universal Soil Loss Equation (USLE), hydrological modeling and multivariate analysis. An assessment of the changes over the period of 2000–2008 in four key ecosystem services was undertaken to determine the effects of the Chinese government's ecological rehabilitation initiatives implemented in 1999. These ecosystem services included water regulation, soil conservation, carbon sequestration and grain production. Significant conversions of farmland to woodland and grassland were found to have resulted in enhanced soil conservation and carbon sequestration, but decreased regional water yield under a warming and drying climate trend. The total grain production increased in spite of a significant decline in farmland acreage. These trends have been attributed to the strong socioeconomic incentives embedded in the ecological rehabilitation policy. Although some positive policy results have been achieved over the last decade, large uncertainty remains regarding long-term policy effects on the sustainability of ecological rehabilitation performance and ecosystem service enhancement. To reduce such uncertainty, this study calls for an adaptive management approach to regional ecological rehabilitation policy to be adopted, with a focus on the dynamic interactions between people and their environments in a changing world

Molecular targeting of prostate cancer cells by a triple drug combination down-regulates integrin driven adhesion processes, delays cell cycle progression and interferes with the cdk-cyclin axis

Background: Single drug use has not achieved satisfactory results in the treatment of prostate cancer, despite application of increasingly widespread targeted therapeutics. In the present study, the combined impact of the mammalian target of rapamycin (mTOR)-inhibitor RAD001, the dual EGFr and VGEFr tyrosine kinase inhibitor AEE788 and the histone deacetylase (HDAC)-inhibitor valproic acid (VPA) on prostate cancer growth and adhesion in vitro was investigated. Methods: PC-3, DU-145 and LNCaP cells were treated with RAD001, AEE788 or VPA or with a RAD-AEE-VPA combination. Tumor cell growth, cell cycle progression and cell cycle regulating proteins were then investigated by MTT-assay, flow cytometry and western blotting, respectively. Furthermore, tumor cell adhesion to vascular endothelium or to immobilized extracellular matrix proteins as well as migratory properties of the cells was evaluated, and integrin alpha and beta subtypes were analyzed. Finally, effects of drug treatment on cell signaling pathways were determined. Results: All drugs, separately applied, reduced tumor cell adhesion, migration and growth. A much stronger anti-cancer effect was evoked by the triple drug combination. Particularly, cdk1, 2 and 4 and cyclin B were reduced, whereas p27 was elevated. In addition, simultaneous application of RAD001, AEE788 and VPA altered the membranous, cytoplasmic and gene expression pattern of various integrin alpha and beta subtypes, reduced integrin-linked kinase (ILK) and deactivated focal adhesion kinase (FAK). Signaling analysis revealed that EGFr and the downstream target Akt, as well as p70S6k was distinctly modified in the presence of the drug combination. Conclusions: Simultaneous targeting of several key proteins in prostate cancer cells provides an advantage over targeting a single pathway. Since strong anti-tumor properties became evident with respect to cell growth and adhesion dynamics, the triple drug combination might provide progress in the treatment of advanced prostate cancer

Effects of Different Correlation Metrics and Preprocessing Factors on Small-World Brain Functional Networks: A Resting-State Functional MRI Study

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01–0.027 Hz) versus slow-4 (0.027–0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the “best” network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027–0.073 Hz band exhibited greater reliability than those in the 0.01–0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies

Auxin Response Factor2 (ARF2) and Its Regulated Homeodomain Gene HB33 Mediate Abscisic Acid Response in Arabidopsis

The phytohormone abscisic acid (ABA) is an important regulator of plant development and response to environmental stresses. In this study, we identified two ABA overly sensitive mutant alleles in a gene encoding Auxin Response Factor2 (ARF2). The expression of ARF2 was induced by ABA treatment. The arf2 mutants showed enhanced ABA sensitivity in seed germination and primary root growth. In contrast, the primary root growth and seed germination of transgenic plants over-expressing ARF2 are less inhibited by ABA than that of the wild type. ARF2 negatively regulates the expression of a homeodomain gene HB33, the expression of which is reduced by ABA. Transgenic plants over-expressing HB33 are more sensitive, while transgenic plants reducing HB33 by RNAi are more resistant to ABA in the seed germination and primary root growth than the wild type. ABA treatment altered auxin distribution in the primary root tips and made the relative, but not absolute, auxin accumulation or auxin signal around quiescent centre cells and their surrounding columella stem cells to other cells stronger in arf2-101 than in the wild type. These results indicate that ARF2 and HB33 are novel regulators in the ABA signal pathway, which has crosstalk with auxin signal pathway in regulating plant growth

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe