The Improving Rural Cancer Outcomes Trial: a cluster-randomised controlled trial of a complex intervention to reduce time to diagnosis in rural cancer patients in Western Australia.

BACKGROUND: Rural Australians have poorer survival for most common cancers, due partially to later diagnosis. Internationally, several initiatives to improve cancer outcomes have focused on earlier presentation to healthcare and timely diagnosis. We aimed to measure the effect of community-based symptom awareness and general practice-based educational interventions on the time to diagnosis in rural patients presenting with breast, prostate, colorectal or lung cancer in Western Australia. METHODS: 2 × 2 factorial cluster randomised controlled trial. Community Intervention: cancer symptom awareness campaign tailored for rural Australians. GP intervention: resource card with symptom risk assessment charts and local cancer referral pathways implemented through multiple academic detailing visits. Trial Area A received the community symptom awareness and Trial Area B acted as the community campaign control region. Within both Trial Areas general practices were randomised to the GP intervention or control. PRIMARY OUTCOME: total diagnostic interval (TDI). RESULTS: 1358 people with incident breast, prostate, colorectal or lung cancer were recruited. There were no significant differences in the median or ln mean TDI at either intervention level (community intervention vs control: median TDI 107.5 vs 92 days; ln mean difference 0.08 95% CI -0.06-0.23 P=0.27; GP intervention vs control: median TDI 97 vs 96.5 days; ln mean difference 0.004 95% CI -0.18-0.19 P=0.99). There were no significant differences in the TDI when analysed by factorial design, tumour group or sub-intervals of the TDI. CONCLUSIONS: This is the largest trial to test the effect of community campaign or GP interventions on timeliness of cancer diagnosis. We found no effect of either intervention. This may reflect limited dose of the interventions, or the limited duration of follow-up. Alternatively, these interventions do not have a measurable effect on time to cancer diagnosis

Accelerated discovery of two crystal structure types in a complex inorganic phase field

The discovery of new materials is hampered by the lack of efficient approaches to the exploration of both the large number of possible elemental compositions for such materials, and of the candidate structures at each composition1. For example, the discovery of inorganic extended solid structures has relied on knowledge of crystal chemistry coupled with time-consuming materials synthesis with systematically varied elemental ratios2,3. Computational methods have been developed to guide synthesis by predicting structures at specific compositions4,5,6 and predicting compositions for known crystal structures7,8, with notable successes9,10. However, the challenge of finding qualitatively new, experimentally realizable compounds, with crystal structures where the unit cell and the atom positions within it differ from known structures, remains for compositionally complex systems. Many valuable properties arise from substitution into known crystal structures, but materials discovery using this approach alone risks both missing best-in-class performance and attempting design with incomplete knowledge8,11. Here we report the experimental discovery of two structure types by computational identification of the region of a complex inorganic phase field that contains them. This is achieved by computing probe structures that capture the chemical and structural diversity of the system and whose energies can be ranked against combinations of currently known materials. Subsequent experimental exploration of the lowest-energy regions of the computed phase diagram affords two materials with previously unreported crystal structures featuring unusual structural motifs. This approach will accelerate the systematic discovery of new materials in complex compositional spaces by efficiently guiding synthesis and enhancing the predictive power of the computational tools through expansion of the knowledge base underpinning them

Accelerated large-scale multiple sequence alignment

<p>Abstract</p> <p>Background</p> <p>Multiple sequence alignment (MSA) is a fundamental analysis method used in bioinformatics and many comparative genomic applications. Prior MSA acceleration attempts with reconfigurable computing have only addressed the first stage of progressive alignment and consequently exhibit performance limitations according to Amdahl's Law. This work is the first known to accelerate the third stage of progressive alignment on reconfigurable hardware.</p> <p>Results</p> <p>We reduce subgroups of aligned sequences into discrete profiles before they are pairwise aligned on the accelerator. Using an FPGA accelerator, an overall speedup of up to 150 has been demonstrated on a large data set when compared to a 2.4 GHz Core2 processor.</p> <p>Conclusions</p> <p>Our parallel algorithm and architecture accelerates large-scale MSA with reconfigurable computing and allows researchers to solve the larger problems that confront biologists today. Program source is available from <url>http://dna.cs.byu.edu/msa/</url>.</p

MISHIMA - a new method for high speed multiple alignment of nucleotide sequences of bacterial genome scale data

<p>Abstract</p> <p>Background</p> <p>Large nucleotide sequence datasets are becoming increasingly common objects of comparison. Complete bacterial genomes are reported almost everyday. This creates challenges for developing new multiple sequence alignment methods. Conventional multiple alignment methods are based on pairwise alignment and/or progressive alignment techniques. These approaches have performance problems when the number of sequences is large and when dealing with genome scale sequences.</p> <p>Results</p> <p>We present a new method of multiple sequence alignment, called MISHIMA (Method for Inferring Sequence History In terms of Multiple Alignment), that does not depend on pairwise sequence comparison. A new algorithm is used to quickly find rare oligonucleotide sequences shared by all sequences. Divide and conquer approach is then applied to break the sequences into fragments that can be aligned independently by an external alignment program. These partial alignments are assembled together to form a complete alignment of the original sequences.</p> <p>Conclusions</p> <p>MISHIMA provides improved performance compared to the commonly used multiple alignment methods. As an example, six complete genome sequences of bacteria species <it>Helicobacter pylori </it>(about 1.7 Mb each) were successfully aligned in about 6 hours using a single PC.</p

Toward a Detailed Description of the Thermally Induced Dynamics of the Core Promoter

Establishing the general and promoter-specific mechanistic features of gene transcription initiation requires improved understanding of the sequence-dependent structural/dynamic features of promoter DNA. Experimental data suggest that a spontaneous dsDNA strand separation at the transcriptional start site is likely to be a requirement for transcription initiation in several promoters. Here, we use Langevin molecular dynamic simulations based on the Peyrard-Bishop-Dauxois nonlinear model of DNA (PBD LMD) to analyze the strand separation (bubble) dynamics of 80-bp-long promoter DNA sequences. We derive three dynamic criteria, bubble probability, bubble lifetime, and average strand separation, to characterize bubble formation at the transcriptional start sites of eight mammalian gene promoters. We observe that the most stable dsDNA openings do not necessarily coincide with the most probable openings and the highest average strand displacement, underscoring the advantages of proper molecular dynamic simulations. The dynamic profiles of the tested mammalian promoters differ significantly in overall profile and bubble probability, but the transcriptional start site is often distinguished by large (longer than 10 bp) and long-lived transient openings in the double helix. In support of these results are our experimental transcription data demonstrating that an artificial bubble-containing DNA template is transcribed bidirectionally by human RNA polymerase alone in the absence of any other transcription factors

Global Transcriptome Profiling of the Pine Shoot Beetle, Tomicus yunnanensis (Coleoptera: Scolytinae)

Background: The pine shoot beetle Tomicus yunnanensis (Coleoptera: Scolytinae) is an economically important pest of Pinus yunnanensis in southwestern China. Developed resistance to insecticides due to chemical pesticides being used for a long time is a factor involved in its serious damage, which poses a challenge for management. In addition, highly efficient adaptation to divergent environmental ecologies results in this pest posing great potential threat to pine forests. However, the molecular mechanisms remain unknown as only limited nucleotide sequence data for this species is available. Methodology/Principal Findings: In this study, we applied next generation sequencing (Illumina sequencing) to sequence the adult transcriptome of T. yunnanensis. A total of 51,822,230 reads were obtained. They were assembled into 140,702 scaffolds, and 60,031 unigenes. The unigenes were further functionally annotated with gene descriptions, Gene Ontology (GO), Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genome (KEGG). In total, 80,932 unigenes were classified into GO, 13,599 unigenes were assigned to COG, and 33,875 unigenes were found in KO categories. A biochemical pathway database containing 219 predicted pathways was also created based on the annotations. In depth analysis of the data revealed a large number of genes related to insecticides resistance and heat shock protein genes associated with environmental stress. Conclusions/Significance: The results facilitate the investigations of molecular resistance mechanisms to insecticides an

ACE Inhibition and Endothelial Function: Main Findings of PERFECT, a Sub-Study of the EUROPA Trial

Background: ACE inhibition results in secondary prevention of coronary artery disease (CAD) through different mechanisms including improvement of endothelial dysfunction. The Perindopril-Function of the Endothelium in Coronary artery disease Trial (PERFECT) evaluated whether long-term administration of perindopril improves endothelial dysfunction. Methods: PERFECT is a 3-year double blind randomised placebo controlled trial to determine the effect of perindopril 8 mg once daily on brachial artery endothelial function in patients with stable CAD without clinical heart failure. Endothelial function in response to ischaemia was assessed using ultrasound. Primary endpoint was difference in flow-mediated vasodilatation (FMD) assessed at 36 months. Results: In 20 centers, 333 patients randomly received perindopril or matching placebo. Ischemia-induced FMD was 2.7% (SD 2.6). In the perindopril group FMD went from 2.6% at baseline to 3.3% at 36 months and in the placebo group from 2.8 to 3.0%. Change in FMD after 36 month treatment was 0.55% (95% confidence interval −0.36, 1.47; p = 0.23) higher in perindopril than in placebo group. The rate of change in FMD per 6 months was 0.14% (SE 0.05, p = 0.02) in perindopril and 0.02% (SE 0.05, p = 0.74) in placebo group (0.12% difference in rate of change p = 0.07). Conclusion: Perindopril resulted in a modest, albeit not statistically significant, improvement in FMD

The cellular geography of Aurora kinases

Aurora is the name given to a family of highly conserved protein kinases with essential roles in many aspects of cell division. Yeasts have a single Aurora kinase, whereas mammals have three: Aurora A, B and C. During mitosis, Aurora kinases regulate the structure and function of the cytoskeleton and chromosomes and the interactions between these two at the kinetochore. They also regulate signalling by the spindle-assembly checkpoint pathway and cytokinesis. Perturbation of Aurora kinase expression or function might lead to cancer