H2AX phosphorylation screen of cells from radiosensitive cancer patients reveals a novel DNA double-strand break repair cellular phenotype

BACKGROUND: About 1-5% of cancer patients suffer from significant normal tissue reactions as a result of radiotherapy (RT). It is not possible at this time to predict how most patients' normal tissues will respond to RT. DNA repair dysfunction is implicated in sensitivity to RT particularly in genes that mediate the repair of DNA double-strand breaks (DSBs). Phosphorylation of histone H2AX (phosphorylated molecules are known as gammaH2AX) occurs rapidly in response to DNA DSBs, and, among its other roles, contributes to repair protein recruitment to these damaged sites. Mammalian cell lines have also been crucial in facilitating the successful cloning of many DNA DSB repair genes; yet, very few mutant cell lines exist for non-syndromic clinical radiosensitivity (RS). METHODS: Here, we survey DNA DSB induction and repair in whole cells from RS patients, as revealed by gammaH2AX foci assays, as potential predictive markers of clinical radiation response. RESULTS: With one exception, both DNA focus induction and repair in cell lines from RS patients were comparable with controls. Using gammaH2AX foci assays, we identified a RS cancer patient cell line with a novel ionising radiation-induced DNA DSB repair defect; these data were confirmed by an independent DNA DSB repair assay. CONCLUSION: gammaH2AX focus measurement has limited scope as a pre-RT predictive assay in lymphoblast cell lines from RT patients; however, the assay can successfully identify novel DNA DSB repair-defective patient cell lines, thus potentially facilitating the discovery of novel constitutional contributions to clinical RS.

Histogram matching and global initialization for laser-only SLAM in large unstructured environments

This paper presents an enhanced algorithm for matching laser scan maps using histogram correlations. The histogram representation effectively summarizes a map's salient features such that pairs of maps can be matched efficiently without any prior guess as to their alignment. The histogram matching algorithm has been enhanced in order to work well in outdoor unstructured environments by using entropy metrics, weighted histograms and proper thresholding of quality metrics. Thus our large-scale scan-matching SLAM implementation has a vastly improved ability to close large loops in real-time even when odometry is not available. Our experimental results have demonstrated a successful mapping of the largest area ever mapped to date using only a single laser scanner. We also demonstrate our ability to solve the lost robot problem by localizing a robot to a previously built map without any prior initialization.

Spatiotemporal analysis of indigenous and imported dengue fever cases in Guangdong province, China

Background Dengue fever has been a major public health concern in China since it re-emerged in Guangdong province in 1978. This study aimed to explore spatiotemporal characteristics of dengue fever cases for both indigenous and imported cases during recent years in Guangdong province, so as to identify high-risk areas of the province and thereby help plan resource allocation for dengue interventions. Methods Notifiable cases of dengue fever were collected from all 123 counties of Guangdong province from 2005 to 2010. Descriptive temporal and spatial analysis were conducted, including plotting of seasonal distribution of cases, and creating choropleth maps of cumulative incidence by county. The space-time scan statistic was used to determine space-time clusters of dengue fever cases at the county level, and a geographical information system was used to visualize the location of the clusters. Analysis were stratified by imported and indigenous origin. Results 1658 dengue fever cases were recorded in Guangdong province during the study period, including 94 imported cases and 1564 indigenous cases. Both imported and indigenous cases occurred more frequently in autumn. The areas affected by the indigenous and imported cases presented a geographically expanding trend over the study period. The results showed that the most likely cluster of imported cases (relative risk = 7.52, p < 0.001) and indigenous cases (relative risk = 153.56, p < 0.001) occurred in the Pearl River Delta Area; while a secondary cluster of indigenous cases occurred in one district of the Chao Shan Area (relative risk = 471.25, p < 0.001). Conclusions This study demonstrated that the geographic range of imported and indigenous dengue fever cases has expanded over recent years, and cases were significantly clustered in two heavily urbanised areas of Guangdong province. This provides the foundation for further investigation of risk factors and interventions in these high-risk areas.

Centroid training to achieve effective text classification

Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant and irrelevant objects in binary classification due to much uncertainty produced in the process of the traditional algorithms. The proposed model CTTC (Centroid Training for Text Classification) aims to build an uncertainty boundary to absorb as many indeterminate objects as possible so as to elevate the certainty of the relevant and irrelevant groups through the centroid clustering and training process. The clustering starts from the two training subsets labelled as relevant or irrelevant respectively to create two principal centroid vectors by which all the training samples are further separated into three groups: POS, NEG and BND, with all the indeterminate objects absorbed into the uncertain decision boundary BND. Two pairs of centroid vectors are proposed to be trained and optimized through the subsequent iterative multi-learning process, all of which are proposed to collaboratively help predict the polarities of the incoming objects thereafter. For the assessment of the proposed model, F1 and Accuracy have been chosen as the key evaluation measures. We stress the F1 measure because it can display the overall performance improvement of the final classifier better than Accuracy. A large number of experiments have been completed using the proposed model on the Reuters Corpus Volume 1 (RCV1) which is important standard dataset in the field. The experiment results show that the proposed model has significantly improved the binary text classification performance in both F1 and Accuracy compared with three other influential baseline models.

Country review on the main building energy-efficiency policy instrument

Building energy-efficiency (BEE) is the key to drive the promotion of energy saving in building sector. A large variety of building energy-efficiency policy instrument exist. Some are mandatory, some are soft scheme, and some use economic incentives from country to country. This paper presents the current development of implementing BEE policy instruments by examining the practices of BEE in seven selected countries and regions. In the study, BEE policy instruments are classified into three groups, including mandatory administration control instruments, economic incentive instruments and voluntary scheme instruments. The study shows that different countries have adopted different instruments in their practices for achieving the target of energy-saving and gained various kinds of experiences. It is important to share these experiences gained.

Sustainable construction trends in journal papers

Sustainable construction is gaining worldwide attention and has inspired research to identify and solve the problems involved in its implementation over a project lifecycle. While an impressive number of papers have been published on the topic to date, little has been done to review these papers to identify current research status or provide guidance for future research. This paper reviews existing sustainability papers in 12 internationally renowned construction journals. Based on a three-stage literature review, sustainability papers published in these journals from 2000 to 2012 are analyzed in terms of the annual number of papers published and the research interests involved. The number of sustainability-related papers in construction increases from 30 papers in 2000 to 127 papers in 2012, which shows an increasing trend in sustainability topics. A content analysis identifies seven major research interest in sustainability, including: (1) sustainable project management; (2) sustainability assessment/evaluation; (3) sustainable technology/innovation implementation; (4) sustainable building/infrastructure performance; (5) government policy on sustainability; (6) enterprise sustainability, and; (7) sustainability education. The results of this study provide a reference for scholars and academics to understand the current status of sustainability research in major construction journals.

Measuring sustainability performance within the Australian energy industry

Sustainability has become crucial for the energy industry as projects in this industry are extensively large and complex and have significant impacts on the environment, community and economy. It demands the energy industry to proactively incorporate sustainability ideas and commit to sustainable project development. This study aims to investigate how the Australian energy industry responds to sustainability requirements and in particular what indicators used to measure sustainability performance. To achieve this, content analysis of sustainability reports, vision statements and policy statements of Australian energy companies listed in the 2013 PLATTS Top 250 Global Energy Company Rankings and government reports relating to sustainability has been conducted. The findings show that the energy companies extensively discuss sustainability aspects within three dimensions, i.e. community, environment, and economy. Their primary goals in sustainability are supplying cleaner energy for future, and doing business in a way that improves outcomes for shareholders, employees, business partners and the communities. In particular, energy companies have valued the employees of the business as a one of the key area that needs to be considered. Furthermore, the energy industry has become increasingly aware of the importance of measuring sustainability performance to achieve sustainability goals. A number of sustainability indicators have been developed on the basis of the key themes beyond economic measures. It is envisaged that findings from this research will help stakeholders in the energy industry to adopt different indicators to evaluate and ultimately achieve sustainability performance.

Defining green road infrastructure projects—A critical review

Green infrastructure is considered as a strategic approach to address the ecological and social impacts of urban sprawl. The main elements of green infrastructure have been well established and include a series of multifunctional ecological systems, such as green urban space, green road infrastructure and the links between these systems. However, it should be noted that the elements of green road infrastructure have only been briefly mentioned in isolated life cycle stages, e.g. design, procurement, construction, maintenance and operation. The definition of green road infrastructure and the elements in green road infrastructure projects remain largely unknown. To explore the elements in green road infrastructure, a critical review was adopted. As the development of green road infrastructure projects is guided by rating systems, a comparison of three major green roads rating systems, including GreenroadsTM, EnvisionTM and Infrastructure Sustainability Rating Tool—IS, was conducted. The comparison reveals that green roads can be defined as road projects that have superior performance in economic, social and environmental sustainability. The sustainability features in green roads mainly include environmental sustainability, social sustainability, economic sustainability, quality, pavement technology and innovation. The results will contribute to an increased understanding of green roads and will be useful to improve the performance of road projects on these sustainability features.

Are green project management practices applicable to traditional projects?

As the social environment begins to create more awareness in the area of conserving the natural environment, a new generation of building has emerged. A trend of constructing buildings that minimise impacts on the environment has been established in the construction industry. Therefore, suitable project management practices have been adopted to efficiently manage the construction of these green buildings. This study aims at investigating practices of project management in traditional and accredited green construction projects, with the purpose of discovering if Green Project Management (GPM) practices can be applied to traditional projects to achieve more successful outcomes. The process of GPM contains what applied to traditional projects, could possibly result in benefits in terms of budget control and constructability. Currently the construction industry has been known to suffer difficulties within these areas; therefore GPM practices could possibly hold a solution to these common problems.

Incentivizing innovation: A review of the Brazilian federal innovation support programs

Innovation is the transformation of knowledge of any kind into new products or services in the market. Its importance as a production factor is widely acknowledged. In the age of the knowledge-based economy innovation became critical for any company or even country to compete globally. Many countries are encouraging innovation through various mechanisms, and one of the most widely used is the provision of special incentives for innovation. This paper investigates incentive systems for the growth of technology companies as a strategy to promote knowledge-based economic development. As for the case investigations the study focuses on an emerging economy, Brazil. The research is based upon the available literature, best practices, government policy and review of incentive systems. The findings provide insights from the case study in a country context and some lessons learned for other countries using incentive systems to boost the innovation capabilities of their technology companies.

Directional synthesis of tin oxide@graphene nanocomposites via a one-step up-scalable wet-mechanochemical route for lithium ion batteries

Directional synthesis of SnO2@graphene nanocomposites via a one-step, low-cost, and up-scalable wetmechanochemical method is achieved using graphene oxide and SnCl2 as precursors. The graphene oxides are reduced to graphene while the SnCl2 is oxidized to SnO2 nanoparticles that are in situ anchored onto the graphene sheets evenly and densely, resulting in uniform SnO2@graphene nanocomposites. The prepared nanocomposites possess excellent electrochemical performance and outstanding cycling in Li-ion batteries.

Prognostic value of BRAF mutations in localized cutaneous melanoma

BACKGROUND: BRAF mutations are frequent in melanoma but their prognostic significance remains unclear. OBJECTIVE: We sought to further evaluate the prognostic value of BRAF mutations in localized cutaneous melanoma. METHODS: We undertook an observational retrospective study of 147 patients with localized invasive (stages I and II) cutaneous melanomas to determine the prognostic value of BRAF mutation status. RESULTS: After a median follow-up of 48 months, patients with localized melanomas with BRAF-mutant melanomas exhibited poorer disease-free survival than those with BRAF-wt genotype (hazard ratio 2.2, 95% confidence interval 1.1-4.3) even after adjustment for Breslow thickness, tumor ulceration, location, age, sex, and tumor mitotic rate. LIMITATIONS: The retrospective design and the small number of events are limitations. CONCLUSIONS: Our findings suggest that reappraisal of clinical treatment approaches for patients with localized melanoma harboring tumors with BRAF mutation might be warranted