Moving interdisciplinary science forward: integrating participatory modelling with mathematical modelling of zoonotic disease in Africa

This review outlines the benefits of using multiple approaches to improve model design and facilitate multidisciplinary research into infectious diseases, as well as showing and proposing practical examples of effective integration. It looks particularly at the benefits of using participatory research in conjunction with traditional modelling methods to potentially improve disease research, control and management. Integrated approaches can lead to more realistic mathematical models which in turn can assist with making policy decisions that reduce disease and benefit local people. The emergence, risk, spread and control of diseases are affected by many complex bio-physical, environmental and socio-economic factors. These include climate and environmental change, land-use variation, changes in population and people’s behaviour. The evidence base for this scoping review comes from the work of a consortium, with the aim of integrating modelling approaches traditionally used in epidemiological, ecological and development research. A total of five examples of the impacts of participatory research on the choice of model structure are presented. Example 1 focused on using participatory research as a tool to structure a model. Example 2 looks at identifying the most relevant parameters of the system. Example 3 concentrates on identifying the most relevant regime of the system (e.g., temporal stability or otherwise), Example 4 examines the feedbacks from mathematical models to guide participatory research and Example 5 goes beyond the so-far described two-way interplay between participatory and mathematical approaches to look at the integration of multiple methods and frameworks. This scoping review describes examples of best practice in the use of participatory methods, illustrating their potential to overcome disciplinary hurdles and promote multidisciplinary collaboration, with the aim of making models and their predictions more useful for decision-making and policy formulation

Coupled transcriptome and proteome analysis of human lymphotropic tumor viruses: insights on the detection and discovery of viral genes

<p>Abstract</p> <p>Background</p> <p>Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV) are related human tumor viruses that cause primary effusion lymphomas (PEL) and Burkitt's lymphomas (BL), respectively. Viral genes expressed in naturally-infected cancer cells contribute to disease pathogenesis; knowing which viral genes are expressed is critical in understanding how these viruses cause cancer. To evaluate the expression of viral genes, we used high-resolution separation and mass spectrometry coupled with custom tiling arrays to align the viral proteomes and transcriptomes of three PEL and two BL cell lines under latent and lytic culture conditions.</p> <p>Results</p> <p>The majority of viral genes were efficiently detected at the transcript and/or protein level on manipulating the viral life cycle. Overall the correlation of expressed viral proteins and transcripts was highly complementary in both validating and providing orthogonal data with latent/lytic viral gene expression. Our approach also identified novel viral genes in both KSHV and EBV, and extends viral genome annotation. Several previously uncharacterized genes were validated at both transcript and protein levels.</p> <p>Conclusions</p> <p>This systems biology approach coupling proteome and transcriptome measurements provides a comprehensive view of viral gene expression that could not have been attained using each methodology independently. Detection of viral proteins in combination with viral transcripts is a potentially powerful method for establishing virus-disease relationships.</p

Therapeutic potential for phenytoin : targeting Nav1.5 sodium channels to reduce migration and invasion in metastatic breast cancer

Voltage-gated Na(+) channels (VGSCs) are heteromeric membrane protein complexes containing pore-forming α subunits and smaller, non-pore-forming β subunits. VGSCs are classically expressed in excitable cells, including neurons and muscle cells, where they mediate action potential firing, neurite outgrowth, pathfinding, and migration. VGSCs are also expressed in metastatic cells from a number of cancers. The Na(v)1.5 α subunit (encoded by SCN5A) is expressed in breast cancer (BCa) cell lines, where it enhances migration and invasion. We studied the expression of SCN5A in BCa array data, and tested the effect of the VGSC-blocking anticonvulsant phenytoin (5,5-diphenylhydantoin) on Na(+) current, migration, and invasion in BCa cells. SCN5A was up-regulated in BCa samples in several datasets, and was more highly expressed in samples from patients who had a recurrence, metastasis, or died within 5 years. SCN5A was also overexpressed as an outlier in a subset of samples, and associated with increased odds of developing metastasis. Phenytoin inhibited transient and persistent Na(+) current recorded from strongly metastatic MDA-MB-231 cells, and this effect was more potent at depolarized holding voltages. It may thus be an effective VGSC-blocking drug in cancer cells, which typically have depolarized membrane potentials. At a concentration within the therapeutic range used to treat epilepsy, phenytoin significantly inhibited the migration and invasion of MDA-MB-231 cells, but had no effect on weakly metastatic MCF-7 cells, which do not express Na(+) currents. We conclude that phenytoin suppresses Na(+) current in VGSC-expressing metastatic BCa cells, thus inhibiting VGSC-dependent migration and invasion. Together, our data support the hypothesis that SCN5A is up-regulated in BCa, favoring an invasive/metastatic phenotype. We therefore propose that repurposing existing VGSC-blocking therapeutic drugs should be further investigated as a potential new strategy to improve patient outcomes in metastatic BCa