Program Correctness by Transformation

Deductive program verification can be used effectively to verify high-level programs, but can be challenging for low-level, high-performance code. In this paper, we argue that compilation and program transformations should be made annotation-aware, i.e. during compilation and program transformation, not only the code should be changed, but also the corresponding annotations. As a result, if the original high-level program could be verified, also the resulting low-level program can be verified. We illustrate this approach on a concrete case, where loop annotations that capture possible loop parallelisations are translated into specifications of an OpenCL kernel that corresponds to the parallel loop. We also sketch how several commonly used OpenCL kernel transformations can be adapted to also transform the corresponding program annotations. Finally, we conclude the paper with a list of research challenges that need to be addressed to further develop this approach

South African dyslipidaemia guideline consensus statement

The European Society of Cardiology together with the European Atherosclerosis Society published updated dyslipidaemia guidelines in 2011. SA Heart and the Lipid and Atherosclerosis Society of Southern Africa officially adopt these guidelines. This statement adapts aspects of the guidelines to the South African situation. Using the updated Framingham risk charts, interventional strategies are based according to the cardiovascular risk score and low-density lipoprotein cholesterol (LDL-C) levels. The Framingham risk score refers to the 10-year risk of any cardiovascular event, and includes four categories of risk. Treatment targets are those of the European guidelines. The LDL-C goal is 1.8mmol/l for the very high-risk group (>30%), 2.5mmol/l for the high-risk group (15 - 30%), and 3mmol/l for those below 15% risk. Intensive management of dyslipidaemia in South Africa will significantly reduce the cardiovascular disease health burden

South African Dyslipidaemia Guideline Consensus Statement: A joint statement from the South African Heart Association (SA Heart) and the Lipid and Atherosclerosis Society of Southern Africa (LASSA)

The European Society of Cardiology together with the European Atherosclerosis Society published updated dyslipidaemia guidelines in 2011. SA Heart and the Lipid and Atherosclerosis Society of Southern Africa officially adopt these guidelines. This statement adapts aspects of the guidelines to the South African situation. Using the updated Framingham risk charts, interventional strategies are based according to the cardiovascular risk score and low-density lipoprotein cholesterol (LDL-C) levels. The Framingham risk score refers to the 10-year risk of any cardiovascular event, and includes four categories of risk. Treatment targets are those of the European guidelines. The LDL-C goal is 1.8 mmol/l for the very high-risk group (>30%), 2.5 mmol/l for the high-risk group (15 - 30%), and 3 mmol/l for those below 15% risk. Intensive management of dyslipidaemia in South Africa will significantly reduce the cardiovascular disease health burden

Fine Mapping of the Interaction between C4b-Binding Protein and Outer Membrane Proteins LigA and LigB of Pathogenic Leptospira interrogans.

The complement system consists of more than 40 proteins that participate in the inflammatory response and in pathogen killing. Complement inhibitors are necessary to avoid the excessive consumption and activation of this system on host cells. Leptospirosis is a worldwide zoonosis caused by spirochetes from the genus Leptospira. Pathogenic leptospires are able to escape from complement activation by binding to host complement inhibitors Factor H [FH] and C4b-binding protein (C4BP) while non-pathogenic leptospires are rapidly killed in the presence of fresh serum. In this study, we demonstrate that complement control protein domains (CCP) 7 and 8 of C4BP α-chain interact with the outer membrane proteins LcpA, LigA and LigB from the pathogenic leptospire L. interrogans. The interaction between C4BP and LcpA, LigA and LigB is sensitive to ionic strength and inhibited by heparin. We fine mapped the LigA and LigB domains involved in its binding to C4BP and heparin and found that both interactions are mediated through the bacterial immunoglobulin-like (Big) domains 7 and 8 (LigA7-8 and LigB7-8) of both LigA and LigB and also through LigB9-10. Therefore, C4BP and heparin may share the same binding sites on Lig proteins

Fine Mapping of the Interaction between C4b-Binding Protein and Outer Membrane Proteins LigA and LigB of Pathogenic Leptospira interrogans.

The complement system consists of more than 40 proteins that participate in the inflammatory response and in pathogen killing. Complement inhibitors are necessary to avoid the excessive consumption and activation of this system on host cells. Leptospirosis is a worldwide zoonosis caused by spirochetes from the genus Leptospira. Pathogenic leptospires are able to escape from complement activation by binding to host complement inhibitors Factor H [FH] and C4b-binding protein (C4BP) while non-pathogenic leptospires are rapidly killed in the presence of fresh serum. In this study, we demonstrate that complement control protein domains (CCP) 7 and 8 of C4BP α-chain interact with the outer membrane proteins LcpA, LigA and LigB from the pathogenic leptospire L. interrogans. The interaction between C4BP and LcpA, LigA and LigB is sensitive to ionic strength and inhibited by heparin. We fine mapped the LigA and LigB domains involved in its binding to C4BP and heparin and found that both interactions are mediated through the bacterial immunoglobulin-like (Big) domains 7 and 8 (LigA7-8 and LigB7-8) of both LigA and LigB and also through LigB9-10. Therefore, C4BP and heparin may share the same binding sites on Lig proteins

Heterogeneous network embedding enabling accurate disease association predictions.

BackgroundIt is significant to identificate complex biological mechanisms of various diseases in biomedical research. Recently, the growing generation of tremendous amount of data in genomics, epigenomics, metagenomics, proteomics, metabolomics, nutriomics, etc., has resulted in the rise of systematic biological means of exploring complex diseases. However, the disparity between the production of the multiple data and our capability of analyzing data has been broaden gradually. Furthermore, we observe that networks can represent many of the above-mentioned data, and founded on the vector representations learned by network embedding methods, entities which are in close proximity but at present do not actually possess direct links are very likely to be related, therefore they are promising candidate subjects for biological investigation.ResultsWe incorporate six public biological databases to construct a heterogeneous biological network containing three categories of entities (i.e., genes, diseases, miRNAs) and multiple types of edges (i.e., the known relationships). To tackle the inherent heterogeneity, we develop a heterogeneous network embedding model for mapping the network into a low dimensional vector space in which the relationships between entities are preserved well. And in order to assess the effectiveness of our method, we conduct gene-disease as well as miRNA-disease associations predictions, results of which show the superiority of our novel method over several state-of-the-arts. Furthermore, many associations predicted by our method are verified in the latest real-world dataset.ConclusionsWe propose a novel heterogeneous network embedding method which can adequately take advantage of the abundant contextual information and structures of heterogeneous network. Moreover, we illustrate the performance of the proposed method on directing studies in biology, which can assist in identifying new hypotheses in biological investigation

A family history of breast cancer will not predict female early onset breast cancer in a population-based setting

ABSTRACT: BACKGROUND: An increased risk of breast cancer for relatives of breast cancer patients has been demonstrated in many studies, and having a relative diagnosed with breast cancer at an early age is an indication for breast cancer screening. This indication has been derived from estimates based on data from cancer-prone families or from BRCA1/2 mutation families, and might be biased because BRCA1/2 mutations explain only a small proportion of the familial clustering of breast cancer. The aim of the current study was to determine the predictive value of a family history of cancer with regard to early onset of female breast cancer in a population based setting. METHODS: An unselected sample of 1,987 women with and without breast cancer was studied with regard to the age of diagnosis of breast cancer. RESULTS: The risk of early-onset breast cancer was increased when there were: (1) at least 2 cases of female breast cancer in first-degree relatives (yes/no; HR at age 30: 3.09; 95% CI: 128-7.44), (2) at least 2 cases of female breast cancer in first or second-degree relatives under the age of 50 (yes/no; HR at age 30: 3.36; 95% CI: 1.12-10.08), (3) at least 1 case of female breast cancer under the age of 40 in a first- or second-degree relative (yes/no; HR at age 30: 2.06; 95% CI: 0.83-5.12) and (4) any case of bilateral breast cancer (yes/no; HR at age 30: 3.47; 95%: 1.33-9.05). The positive predictive value of having 2 or more of these characteristics was 13% for breast cancer before the age of 70, 11% for breast cancer before the age of 50, and 1% for breast cancer before the age of 30. CONCLUSION: Applying family history related criteria in an unselected population could result in the screening of many women who will not develop breast cancer at an early age