A computational intelligent approach to multi-factor analysis of violent crime information systems

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

Functional and genetic analysis of the colon cancer network

Cancer is a complex disease that has proven to be difficult to understand on the single-gene level. For this reason a functional elucidation needs to take interactions among genes on a systems-level into account. In this study, we infer a colon cancer network from a large-scale gene expression data set by using the method BC3Net. We provide a structural and a functional analysis of this network and also connect its molecular interaction structure with the chromosomal locations of the genes enabling the definition of cis- and trans-interactions. Furthermore, we investigate the interaction of genes that can be found in close neighborhoods on the chromosomes to gain insight into regulatory mechanisms. To our knowledge this is the first study analyzing the genome-scale colon cancer network.

Bone tool analysis

This article examines the osseous technologies that can be created from animal skeletons. 'Tool' status is accorded to a skeletal element or fragment that has been modified subsequent to its isolation from the carcass. Such anthropic adaptation may be deliberate (e.g., through manufacture) and/or appear as a result of utilization, and is granted in instances where these details cannot otherwise be ascribed to alternative nonanthropic causes. Implements can display a combination of traces from both human and natural sources and as such the study of them involves both zooarchaeological (i.e., via animal ecology, hunting, and butchery) and technological analysis.... As an exemplar of this, the following discussion will present some of the similarities and differences that exist between osseous and lithic raw materials and tool-blank production, and will situate both in an operational sequence of animal procurement and processing. It will then give an account of principal manufacturing techniques, methods for establishing tool function, and the phenomenon of 'pseudo tools'. © 2008 Copyright © 2008 Elsevier Inc.

Hydrophilic Interaction Ultra-High Performance Liquid Chromatography Coupled with Triple-Quadrupole Mass Spectrometry for Determination of Nucleosides and Nucleobases in Animal Horns

Traditional Chinese Medicines (TCMs) derived from animal horns are one of the most important types of Chinese medicine. In the present study, a fast and sensitive analytical method was established for qualitative and quantitative determination of 14 nucleosides and nucleobases in animal horns using hydrophilic interaction ultra-high performance liquid chromatography coupled with triple-quadruple tandem mass spectrometry (HILIC-UPLC-QQQ-MS/MS) in selective reaction monitoring (SRM) mode. The method was optimized and validated, and showed good linearity, precision, repeatability, and accuracy. The method was successfully used to determine contents of the 14 nucleosides and nucleobases in 25 animal horn samples. Hierarchical clustering analysis (HCA) and principal component analysis (PCA) were performed and the 25 samples were thereby divided into two groups, which agreed with taxonomy. The method may enable quick and effective search of substitutes for precious horns.

Determining adsorbate configuration on alumina surfaces with 13C nuclear magnetic resonance relaxation time analysis

Relative strengths of surface interaction for individual carbon atoms in acyclic and cyclic hydrocarbons adsorbed on alumina surfaces are determined using chemically resolved 13C nuclear magnetic resonance (NMR) T1 relaxation times. The ratio of relaxation times for the adsorbed atoms T1,ads to the bulk liquid relaxation time T1,bulk provides an indication of the mobility of the atom. Hence a low T1,ads/T1,bulk ratio indicates a stronger surface interaction. The carbon atoms associated with unsaturated bonds in the molecules are seen to exhibit a larger reduction in T1 on adsorption relative to the aliphatic carbons, consistent with adsorption occurring through the carbon-carbon multiple bonds. The relaxation data are interpreted in terms of proximity of individual carbon atoms to the alumina surface and adsorption conformations are inferred. Furthermore, variations of interaction strength and molecular configuration have been explored as a function of adsorbate coverage, temperature, surface pre-treatment, and in the presence of co-adsorbates. This relaxation time analysis is appropriate for studying the behaviour of hydrocarbons adsorbed on a wide range of catalyst support and supported-metal catalyst surfaces, and offers the potential to explore such systems under realistic operating conditions when multiple chemical components are present at the surface.

A kinetic analysis methodology to elucidate the roles of metal, support and solvent for the hydrogenation of 4-phenyl-2-butanone over Pt/TiO2

The rate and, more importantly, selectivity (ketone vs aromatic ring) of the hydrogenation of 4-phenyl-2-butanone over a Pt/TiO2 catalyst have been shown to vary with solvent. In this study, a fundamental kinetic model for this multi-phase reaction has been developed incorporating statistical analysis methods to strengthen the foundations of mechanistically sound kinetic models. A 2-site model was determined to be most appropriate, describing aromatic hydrogenation (postulated to be over a platinum site) and ketone hydrogenation (postulated to be at the platinum–titania interface). Solvent choice has little impact on the ketone hydrogenation rate constant but strongly impacts aromatic hydrogenation due to solvent-catalyst interaction. Reaction selectivity is also correlated to a fitted product adsorption constant parameter. The kinetic analysis method shown has demonstrated the role of solvents in influencing reactant adsorption and reaction selectivity.

Dynamic Modeling and Interaction of Hybrid Natural Gas and Electricity Supply System in Microgrid

Natural gas (NG) network and electric network are becoming tightly integrated by microturbines in the microgrid. Interactions between these two networks are not well captured by the traditional microturbine (MT) models. To address this issue, two improved models for single-shaft MT and split-shaft MT are proposed in this paper. In addition, dynamic models of the hybrid natural gas and electricity system (HGES) are developed for the analysis of their interactions. Dynamic behaviors of natural gas in pipes are described by partial differential equations (PDEs), while the electric network is described by differential algebraic equations (DAEs). So the overall network is a typical two-time scale dynamic system. Numerical studies indicate that the two-time scale algorithm is faster and can capture the interactions between the two networks. The results also show the HGES with a single-shaft MT is a weakly coupled system in which disturbances in the two networks mainly influence the dc link voltage of the MT, while the split-shaft MT is a strongly coupled system where the impact of an event will affect both networks.

Simulating reinforced concrete members. Part 1: partial interaction properties

Reinforced concrete members are extremely complex under loading because of localised deformations in the concrete (cracks, sliding planes) and between the reinforcement and concrete (slip). An ideal model for simulating behaviour of reinforced concrete members should incorporate both global behaviour and the localised behaviours that are seen and measured in practice; these localised behaviours directly affect the global behaviour. Most commonly used models do not directly simulate these localised behaviours that can be seen or measured in real members; instead, they overcome these limitations by using empirically or semi-empirically derived strain-based pseudo properties such as the use of effective flexural rigidities for deflection; plastic hinge lengths for strength and ductility; and energy-based approaches for both concrete softening in compression and concrete softening after tensile cracking to allow for tension stiffening. Most reinforced concrete member experimental testing is associated with deriving these pseudo properties for use in design and analysis, and this component of development is thus costly. The aim of the present research is to reduce this cost substantially. In this paper, localised material behaviours and the mechanisms they induce are described. Their incorporation into reinforced concrete member behaviour without the need for empirically derived pseudo properties is described in a companion paper.

New androgen receptor genomic targets show an interaction with the ETS1 transcription factor

The androgen receptor (AR) initiates important developmental and oncogenic transcriptional pathways. The AR is known to bind as a homodimer to 15-base pair bipartite palindromic androgen-response elements; however, few direct AR gene targets are known. To identify AR promoter targets, we used chromatin immunoprecipitation with on-chip detection of genomic fragments. We identified 1,532 potential AR-binding sites, including previously known AR gene targets. Many of the new AR target genes show altered expression in prostate cancer. Analysis of sequences underlying AR-binding sites showed that more than 50% of AR-binding sites did not contain the established 15 bp AR-binding element. Unbiased sequence analysis showed 6-bp motifs, which were significantly enriched and were bound directly by the AR in vitro. Binding sequences for the avian erythroblastosis virus E26 homologue (ETS) transcription factor family were also highly enriched, and we uncovered an interaction between the AR and ETS1 at a subset of AR promoter targets.

Does childhood bullying lead to the development of psychotic symptoms? A meta-analysis and review of prospective studies

Purpose: Researchers have demonstrated associations between trauma and psychosis. Childhood trauma, in particular, appears to be an important determinant. Recently, bullying has become considered a traumatic experience in its own right. This review aims to analyse research with prospective designs, which will enable conclusions about whether or not bullying causes psychosis.

Methods: A systematic review of the literature was carried out independently by two reviewers. Eligibility and quality assessment criteria were applied. A meta-analysis and narrative synthesis were then completed.

Results: Ten studies met inclusion criteria. Four used data from the same large database, and were combined as one. The majority provided confirmation that bullying appears to cause later development of psychosis. A meta-analysis yielded an unadjusted odds ratio (OR) of 2.148 [95% confidence interval (CI) 1.140–4.044].

Conclusions: The studies reviewed here suggest that bullying does predict the later development of psychotic symptoms. What is lacking from the literature is adequate investigation into other potential mediating factors. The current review highlights the significant role of bullying within this complex interaction. Potential mediating variables are explored, including a dose–response effect for the severity and frequency of victimization. Suggestions for targeting intervention are also suggested alongside clinical implications and recommendations for future research.

Label-free based quantitative proteomics analysis of primary neonatal porcine Leydig cells exposed to the persistent contaminant 3-methylsulfonyl-DDE

Evidence that persistent environmental pollutants may target the male reproductive system is increasing. The male reproductive system is regulated by secretion of testosterone by testicular Leydig cells, and perturbation of Leydig cell function may have ultimate consequences. 3-Methylsulfonyl-DDE (3-MeSO₂-DDE) is a potent adrenal toxicants formed from the persistent insecticide DDT. Although studies have revealed the endocrine disruptive effect of 3-MeSO₂-DDE, the underlying mechanisms at cellular level in steroidogenic Leydig cells remains to be established. The current study addresses the effect of 3-MeSO₂-DDE on viability, hormone production and proteome response of primary neonatal porcine Leydig cells. The AlamarBlue™ assay was used to evaluate cell viability. Solid phase radioimmunoassay was used to measure concentration of hormones produced by both unstimulated and Luteinizing hormone (LH)-stimulated Leydig cells following 48h exposure. Protein samples from Leydig cells exposed to a non-cytotoxic concentration of 3-MeSO₂-DDE (10μM) were subjected to nano-LC-MS/MS and analyzed on a Q Exactive mass spectrometer and quantified using label-free quantitative algorithm. Gene Ontology (GO) and Ingenuity Pathway Analysis (IPA) were carried out for functional annotation and identification of protein interaction networks. 3-MeSO₂-DDE regulated Leydig cell steroidogenesis differentially depending on cell culture condition. Whereas its effect on testosterone secretion at basal condition was stimulatory, the effect on LH-stimulated cells was inhibitory. From triplicate experiments, a total of 6804 proteins were identified in which the abundance of 86 proteins in unstimulated Leydig cells and 145 proteins in LH-stimulated Leydig cells was found to be significantly regulated in response to 3-MeSO₂-DDE exposure. These proteins not only are the first reported in relation to 3-MeSO₂-DDE exposure, but also display small number of proteins shared between culture conditions, suggesting the action of 3-MeSO₂-DDE on several targeted pathways, including mitochondrial dysfunction, oxidative phosphorylation, EIF2-signaling, and glutathione-mediated detoxification. Further identification and characterization of these proteins and pathways may build our understanding to the molecular basis of 3-MeSO₂-DDE induced endocrine disruption in Leydig cells.

The value of adjuvant radiotherapy on survival and recurrence in triple-negative breast cancer: a systematic review and meta-analysis of 5,507 patients

BACKGROUND: The value of adjuvant radiotherapy in triple negative breast cancer (TNBC) remains unclear. A systematic review and meta-analysis was conducted in TNBC patients to assess survival and recurrence outcomes associated with radiotherapy following either breast conserving therapy (BCT) or post-mastectomy radiotherapy (PMRT). METHODS: Four electronic databases were searched from January 2000 to November 2015 (PubMed, MEDLINE, EMBASE and Web of Science). Studies investigating overall survival and/or recurrence in TNBC patients according to radiotherapy administration were included. A random effects meta-analysis was conducted using mastectomy only patients as the reference.  RESULTS: Twelve studies were included. The pooled hazard ratio (HR) for locoregional recurrence comparing BCT and PMRT to mastectomy only was 0.61 (95% confidence interval [CI] 0.41-0.90) and 0.62 (95% CI 0.44-0.86), respectively. Adjuvant radiotherapy was not significantly associated with distant recurrence. The pooled HR for overall survival comparing BCT and PMRT to mastectomy only was 0.57 (95% CI 0.36-0.88) and HR 1.12 (95% CI 0.75, 1.69). Comparing PMRT to mastectomy only, tests for interaction were not significant for stage (p=0.98) or age at diagnosis (p=0.85). However, overall survival was improved in patients with late-stage disease (T3-4, N2-3) pooled HR 0.53 (95% CI 0.32-0.86), and women <40 years, pooled HR 0.30 (95% CI 0.11-0.82). CONCLUSIONS: Adjuvant radiotherapy was associated with a significantly lower risk of locoregional recurrence in TNBC patients, irrespective of the type of surgery. While radiotherapy was not consistently associated with an overall survival gain, benefits may be obtained in women with late-stage disease and younger patients. 

Network signatures based on gene pair expression ratios improve classification and the analysis of muscle-invasive urothelial cancer

Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.