Integration Preferences of Wildtype AAV-2 for Consensus Rep-Binding Sites at Numerous Loci in the Human Genome

Adeno-associated virus type 2 (AAV) is known to establish latency by preferential integration in human chromosome 19q13.42. The AAV non-structural protein Rep appears to target a site called AAVS1 by simultaneously binding to Rep-binding sites (RBS) present on the AAV genome and within AAVS1. In the absence of Rep, as is the case with AAV vectors, chromosomal integration is rare and random. For a genome-wide survey of wildtype AAV integration a linker-selection-mediated (LSM)-PCR strategy was designed to retrieve AAV-chromosomal junctions. DNA sequence determination revealed wildtype AAV integration sites scattered over the entire human genome. The bioinformatic analysis of these integration sites compared to those of rep-deficient AAV vectors revealed a highly significant overrepresentation of integration events near to consensus RBS. Integration hotspots included AAVS1 with 10% of total events. Novel hotspots near consensus RBS were identified on chromosome 5p13.3 denoted AAVS2 and on chromsome 3p24.3 denoted AAVS3. AAVS2 displayed seven independent junctions clustered within only 14 bp of a consensus RBS which proved to bind Rep in vitro similar to the RBS in AAVS3. Expression of Rep in the presence of rep-deficient AAV vectors shifted targeting preferences from random integration back to the neighbourhood of consensus RBS at hotspots and numerous additional sites in the human genome. In summary, targeted AAV integration is not as specific for AAVS1 as previously assumed. Rather, Rep targets AAV to integrate into open chromatin regions in the reach of various, consensus RBS homologues in the human genome

Evaluation of DNA ploidy in relation with established prognostic factors in patients with locally advanced (unresectable) or metastatic pancreatic adenocarcinoma: a retrospective analysis

<p>Abstract</p> <p>Background</p> <p>Most patients with ductal pancreatic adenocarcinoma are diagnosed with locally advanced (unresectable) or metastatic disease. The aim of this study was to evaluate the prognostic significance of DNA ploidy in relation with established clinical and laboratory variables in such patients.</p> <p>Methods</p> <p>Two hundred and twenty six patients were studied retrospectively. Twenty two potential prognostic variables (demographics, clinical parameters, biochemical markers, treatment modality) were examined.</p> <p>Results</p> <p>Mean survival time was 38.41 weeks (95% c.i.: 33.17–43.65), median survival 27.00 weeks (95% c.i.: 23.18–30.82). On multivariate analysis, 10 factors had an independent effect on survival: performance status, local extension of tumor, distant metastases, ploidy score, anemia under epoetin therapy, weight loss, pain, steatorrhoea, CEA, and palliative surgery and chemotherapy. Patients managed with palliative surgery and chemotherapy had 6.7 times lower probability of death in comparison with patients without any treatment. Patients with ploidy score > 3.6 had 5.0 times higher probability of death in comparison with patients with ploidy score < 2.2 and these with ploidy score 2.2–3.6 had 6.3 times higher probability of death in comparison with patients with ploidy score < 2.2.</p> <p>Conclusion</p> <p>According to the significance of the examined factor, survival was improved mainly by the combination of surgery and chemotherapy, and the presence of low DNA ploidy score.</p

Saccharomyces cerevisiae: Population Divergence and Resistance to Oxidative Stress in Clinical, Domesticated and Wild Isolates

BACKGROUND: Saccharomyces cerevisiae has been associated with human life for millennia in the brewery and bakery. Recently it has been recognized as an emerging opportunistic pathogen. To study the evolutionary history of S. cerevisiae, the origin of clinical isolates and the importance of a virulence-associated trait, population genetics and phenotypic assays have been applied to an ecologically diverse set of 103 strains isolated from clinics, breweries, vineyards, fruits, soil, commercial supplements and insect guts. METHODOLOGY/PRINCIPAL FINDINGS: DNA sequence data from five nuclear DNA loci were analyzed for population structure and haplotype distribution. Additionally, all strains were tested for survival of oxidative stress, a trait associated with microbial pathogenicity. DNA sequence analyses identified three genetic subgroups within the recombining S. cerevisiae strains that are associated with ecology, geography and virulence. Shared alleles suggest that the clinical isolates contain genetic contribution from the fruit isolates. Clinical and fruit isolates exhibit high levels of recombination, unlike the genetically homogenous soil isolates in which no recombination was detected. However, clinical and soil isolates were more resistant to oxidative stress than any other population, suggesting a correlation between survival in oxidative stress and yeast pathogenicity. CONCLUSIONS/SIGNIFICANCE: Population genetic analyses of S. cerevisiae delineated three distinct groups, comprising primarily the (i) human-associated brewery and vineyard strains, (ii) clinical and fruit isolates (iii) and wild soil isolates from eastern U.S. The interactions between S. cerevisiae and humans potentiate yeast evolution and the development of genetically, ecologically and geographically divergent groups

Stochastic flowering phenology in Dactylis Glomerata populations described by Markov chain modelling

Understanding the relationship between flowering patterns and pollen dispersal is important in climate change modelling, pollen forecasting, forestry and agriculture. Enhanced understanding of this connection can be gained through detailed spatial and temporal flowering observations on a population level, combined with modelling simulating the dynamics. Species with large distribution ranges, long flowering seasons, high pollen production and naturally large populations can be used to illustrate these dynamics. Revealing and simulating species-specific demographic and stochastic elements in the flowering process will likely be important in determining when pollen release is likely to happen in flowering plants. Spatial and temporal dynamics of eight populations of Dactylis glomerata were collected over the course of two years to determine high-resolution demographic elements. Stochastic elements were accounted for using Markov Chain approaches in order to evaluate tiller-specific contribution to overall population dynamics. Tiller-specific developmental dynamics were evaluated using three different RV matrix correlation coefficients. We found that the demographic patterns in population development were the same for all populations with key phenological events differing only by a few days over the course of the seasons. Many tillers transitioned very quickly from non-flowering to full flowering, a process that can be replicated with Markov Chain modelling. Our novel approach demonstrates the identification and quantification of stochastic elements in the flowering process of D. glomerata, an element likely to be found in many flowering plants. The stochastic modelling approach can be used to develop detailed pollen release models for Dactylis, other grass species and probably other flowering plants

What Can Studying Designed Marital Argument Interventions Contribute To Argumentation Scholarship?

In this chapter, I take a design approach to the study of marital argumentation. Two marriage education programs, the prevention and relationship enhancement program (PREP) and the practical application of intimate relationship skills (PAIRS) program are examined. Each curriculum presents communication tools/guides/procedures for either directly improving argumentation behavior or by indirectly improving arguments by enhancing the partners\u27 commitment and intimacy. After discussing specific communication tools from each program, I identify design hypotheses underlying the programs that can then be applied to more general issues related to argumentation theory