159 research outputs found
Механизм формирования экстремистских установок у несовершеннолетних
In this paper key trends in the development of extremist and near-extremist youth subcultures are outlined, and characteristic features of criminal and near-criminal youth organizations are described. The results of an empirical study of the activity of existing harmful groups and organizations that are known to involve minors in their ranks are presented, including a description of their dissemination platforms, size and gender composition, declared and actual goals, and external manifestations. Mechanisms for the formation of extremist attitudes in minors are identified, and the special role of psycho-linguistic and forensic psychological expertise in the investigation of extremist crimes is demonstrated. Recommendations are offered towards the implementation of effective counteraction to extremism among minors.Рассмотрены основные тенденции развития экстремистских и околоэкстремистских молодежных субкультур, выявлены и описаны характерные черты молодежных криминальных и околокриминальных организаций. Представлены результаты эмпирического исследования деятельности деструктивных групп и организаций, в настоящее время вовлекающих в свои ряды несовершеннолетних, с описанием платформы их распространения, численного и гендерного состава, декларируемых и истинных целей, внешних проявлений. Определены механизмы формирования экстремистских установок у несовершеннолетних. Показана особая роль психолого-лингвистических и судебно-психологических экспертиз в расследовании преступлений экстремистской направленности. Даны рекомендации по эффективному противодействию экстремизму в среде несовершеннолетних
The PathOlogist: an automated tool for pathway-centric analysis
<p>Abstract</p> <p>Background</p> <p>The PathOlogist is a new tool designed to transform large sets of gene expression data into quantitative descriptors of pathway-level behavior. The tool aims to provide a robust alternative to the search for single-gene-to-phenotype associations by accounting for the complexity of molecular interactions.</p> <p>Results</p> <p>Molecular abundance data is used to calculate two metrics - 'activity' and 'consistency' - for each pathway in a set of more than 500 canonical molecular pathways (source: Pathway Interaction Database, <url>http://pid.nci.nih.gov</url>). The tool then allows a detailed exploration of these metrics through integrated visualization of pathway components and structure, hierarchical clustering of pathways and samples, and statistical analyses designed to detect associations between pathway behavior and clinical features.</p> <p>Conclusions</p> <p>The PathOlogist provides a straightforward means to identify the functional processes, rather than individual molecules, that are altered in disease. The statistical power and biologic significance of this approach are made easily accessible to laboratory researchers and informatics analysts alike. Here we show as an example, how the PathOlogist can be used to establish pathway signatures that robustly differentiate breast cancer cell lines based on response to treatment.</p
Recommended from our members
Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design.
Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)-many of which are refractory to current standard-of-care treatments-from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer
Characterizing genomic alterations in cancer by complementary functional associations.
Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes
Standardisierungswettbewerb zwischen parametrisierbarer Standardsoftware und komponentenbasierten Anwendungssystemen
Standardisierungswettbewerb zwischen parametrisierbarer Standardsoftware und komponentenbasierten Anwendungssystemen / Stefan Volkert ; Bernd Reitwiesner. - In: Information age economy / Hans Ulrich Buhl ... (Hrsg.). - Heidelberg : Physica-Verl., 2001. - S. 667-68
Deterministic Effects Propagation Networks for reconstructing protein signaling networks from multiple interventions
<p>Abstract</p> <p>Background</p> <p>Modern gene perturbation techniques, like RNA interference (RNAi), enable us to study effects of targeted interventions in cells efficiently. In combination with mRNA or protein expression data this allows to gain insights into the behavior of complex biological systems.</p> <p>Results</p> <p>In this paper, we propose Deterministic Effects Propagation Networks (DEPNs) as a special Bayesian Network approach to reverse engineer signaling networks from a combination of protein expression and perturbation data. DEPNs allow to reconstruct protein networks based on combinatorial intervention effects, which are monitored via changes of the protein expression or activation over one or a few time points. Our implementation of DEPNs allows for latent network nodes (i.e. proteins without measurements) and has a built in mechanism to impute missing data. The robustness of our approach was tested on simulated data. We applied DEPNs to reconstruct the <it>ERBB </it>signaling network in <it>de novo </it>trastuzumab resistant human breast cancer cells, where protein expression was monitored on Reverse Phase Protein Arrays (RPPAs) after knockdown of network proteins using RNAi.</p> <p>Conclusion</p> <p>DEPNs offer a robust, efficient and simple approach to infer protein signaling networks from multiple interventions. The method as well as the data have been made part of the latest version of the R package "nem" available as a supplement to this paper and via the Bioconductor repository.</p
Effect of the estrogen receptor locus on reproduction and production traits in four commercial pig lines.
We investigated the effect of the estrogen receptor (ESR) gene on growth and reproductive traits in four Large White-based commercial pig lines. A total of 9,015 litter records from 4,262 sows genotyped at the ESR locus were analyzed to determine whether ESR influenced total number born (TNB) or number born alive (NBA). Teat number (TN), test ADG, ADFI, feed:gain ratio (F/G), and ultrasonic backfat (BF) were also analyzed to determine effects of ESR. The TNB and NBA were increased per favorable allele of ESR (P .10), although ADF was reduced 18 g/d per copy of the favorable litter size allele (P This is an article from Journal of Animal Science 75 (1997): 3138, doi:/1997.75123138x. Posted with permission.</p
Short-term movements and habitat preferences of sailfish, Istiophorus platypterus (Istiophoridae), along the southeast coast of Brazil
Integrated Analyses of Copy Number Variations and Gene Expression in Lung Adenocarcinoma
Numerous efforts have been made to elucidate the etiology and improve the treatment of lung cancer, but the overall five-year survival rate is still only 15%. Identification of prognostic biomarkers for lung cancer using gene expression microarrays poses a major challenge in that very few overlapping genes have been reported among different studies. To address this issue, we have performed concurrent genome-wide analyses of copy number variation and gene expression to identify genes reproducibly associated with tumorigenesis and survival in non-smoking female lung adenocarcinoma. The genomic landscape of frequent copy number variable regions (CNVRs) in at least 30% of samples was revealed, and their aberration patterns were highly similar to several studies reported previously. Further statistical analysis for genes located in the CNVRs identified 475 genes differentially expressed between tumor and normal tissues (p<10−5). We demonstrated the reproducibility of these genes in another lung cancer study (p = 0.0034, Fisher's exact test), and showed the concordance between copy number variations and gene expression changes by elevated Pearson correlation coefficients. Pathway analysis revealed two major dysregulated functions in lung tumorigenesis: survival regulation via AKT signaling and cytoskeleton reorganization. Further validation of these enriched pathways using three independent cohorts demonstrated effective prediction of survival. In conclusion, by integrating gene expression profiles and copy number variations, we identified genes/pathways that may serve as prognostic biomarkers for lung tumorigenesis
From little things, big things grow: trends and fads in 110 years of Australian ornithology
Publishing histories can reveal changes in ornithological effort, focus or direction through time. This study presents a bibliometric content analysis of Emu (1901–2011) which revealed 115 trends (long-term changes in publication over time) and 18 fads (temporary increases in publication activity) from the classification of 9,039 articles using 128 codes organised into eight categories (author gender, author affiliation, article type, subject, main focus, main method, geographical scale and geographical location). Across 110 years, private authorship declined, while publications involving universities and multiple institutions increased; from 1960, female authorship increased. Over time, question-driven studies and incidental observations increased and decreased in frequency, respectively. Single species and ‘taxonomic group’ subjects increased while studies of birds at specific places decreased. The focus of articles shifted from species distribution and activities of the host organisation to breeding, foraging and other biological/ecological topics. Site- and Australian-continental-scales slightly decreased over time; non-Australian studies increased from the 1970s. A wide variety of fads occurred (e.g. articles on bird distribution, 1942–1951, and using museum specimens, 1906–1913) though the occurrence of fads decreased over time. Changes over time are correlated with technological, theoretical, social and institutional changes, and suggest ornithological priorities, like those of other scientific disciplines, are temporally labil
- …