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Background: Due to the lack of timely access to resources for critical care, strategic use of antiviral drugs is crucial for mitigating the impact of novel influenza viruses with pandemic potential in remote and isolated communities. We sought to evaluate the effect of antiviral treatment and prophylaxis of close contacts in a Canadian remote northern community. Methods: We used an agent-based, discrete-time simulation model for disease spread in a remote community, which was developed as an in-silico population using population census data. Relative and cumulative age-specific attack rates, and the total number of infections in simulated model scenarios were obtained. Results: We found that early initiation of antiviral treatment is more critical for lowering attack rates in a remote setting with a low population-average age compared to an urban population. Our results show that a significant reduction in the relative, age-specific attack rates due to increasing treatment coverage does not necessarily translate to a significant reduction in the overall arrack rate. When treatment coverage varies from low to moderate, targeted prophylaxis has a very limited impact in reducing attack rates and should be offered at a low level (below 10%) to avoid excessive waste of drugs. Conclusions: In contrast to previous work, for conservative treatment coverages, our results do not provide any convincing evidence for the implementation of targeted prophylaxis. The findings suggest that public health strategies in remote communities should focus on the wider availability (higher coverage) and timely distribution of antiviral drugs for treatment of clinically ill individuals. [ABSTRACT FROM AUTHOR]

Cisplatin, a commonly used chemotherapeutic, is associated with ototoxicity, renal toxicity and neurotoxicity, thus identifying means to increase the therapeutic index of cisplatin may allow for improved outcomes. A SNP (rs4343077) within EPS8, discovered through a genome wide association study of cisplatin-induced cytotoxicity and apoptosis in lymphoblastoid cell lines (LCLs), provided impetus to further study this gene. The purpose of this work was to evaluate the role of EPS8 in cellular susceptibility to cisplatin in cancerous and non-cancerous cells. We used EPS8 RNA interference to determine the effect of decreased EPS8 expression on LCL and A549 lung cancer cell sensitivity to cisplatin. EPS8 knockdown in LCLs resulted in a 7.9% increase in cisplatin-induced survival (P = 1.98×10−7) and an 8.7% decrease in apoptosis (P = 0.004) compared to control. In contrast, reduced EPS8 expression in lung cancer cells resulted in a 20.6% decrease in cisplatin-induced survival (P = 5.08×10−5). We then investigated an EPS8 inhibitor, mithramycin A, as a potential agent to increase the therapeutic index of cisplatin. Mithramycin A decreased EPS8 expression in LCLs resulting in decreased cellular sensitivity to cisplatin as evidenced by lower caspase 3/7 activation following cisplatin treatment (42.7%±6.8% relative to control P = 0.0002). In 5 non-small-cell lung carcinoma (NSCLC) cell lines, mithramycin A also resulted in decreased EPS8 expression. Adding mithramycin to 4 NSCLC cell lines and a bladder cancer cell line, resulted in increased sensitivity to cisplatin that was significantly more pronounced in tumor cell lines than in LCL lines (p<0.0001). An EGFR mutant NSCLC cell line (H1975) showed no significant change in sensitivity to cisplatin with the addition of mithramycin treatment. Therefore, an inhibitor of EPS8, such as mithramycin A, could improve cisplatin treatment by increasing sensitivity of tumor relative to normal cells. [ABSTRACT FROM AUTHOR]

Background: Communicable disease outbreaks of novel or existing pathogens threaten human health around the globe. It would be desirable to rapidly characterize such outbreaks and develop accurate projections of their duration and cumulative size even when limited preliminary data are available. Here we develop a mathematical model to aid public health authorities in tracking the expansion and contraction of outbreaks with explicit representation of factors (other than population immunity) that may slow epidemic growth. Methodology: The Incidence Decay and Exponential Adjustment (IDEA) model is a parsimonious function that uses the basic reproduction number R0, along with a discounting factor to project the growth of outbreaks using only basic epidemiological information (e.g., daily incidence counts). Principal Findings: Compared to simulated data, IDEA provides highly accurate estimates of total size and duration for a given outbreak when R0 is low or moderate, and also identifies turning points or new waves. When tested with an outbreak of pandemic influenza A (H1N1), the model generates estimated incidence at the i+1th serial interval using data from the ith serial interval within an average of 20% of actual incidence. Conclusions and Significance: This model for communicable disease outbreaks provides rapid assessments of outbreak growth and public health interventions. Further evaluation in the context of real-world outbreaks will establish the utility of IDEA as a tool for front-line epidemiologists. [ABSTRACT FROM AUTHOR]

Respiratory infections stemming from influenza viruses and the Severe Acute Respiratory Syndrome corona virus (SARS-CoV) represent a serious public health threat as emerging pandemics. Despite efforts to identify the critical interactions of these viruses with host machinery, the key regulatory events that lead to disease pathology remain poorly targeted with therapeutics. Here we implement an integrated network interrogation approach, in which proteome and transcriptome datasets from infection of both viruses in human lung epithelial cells are utilized to predict regulatory genes involved in the host response. We take advantage of a novel “crowd-based” approach to identify and combine ranking metrics that isolate genes/proteins likely related to the pathogenicity of SARS-CoV and influenza virus. Subsequently, a multivariate regression model is used to compare predicted lung epithelial regulatory influences with data derived from other respiratory virus infection models. We predicted a small set of regulatory factors with conserved behavior for consideration as important components of viral pathogenesis that might also serve as therapeutic targets for intervention. Our results demonstrate the utility of integrating diverse ‘omic datasets to predict and prioritize regulatory features conserved across multiple pathogen infection models. [ABSTRACT FROM AUTHOR]

Epstein-Barr virus (EBV) is associated with roughly 10% of gastric carcinomas worldwide (EBVaGC). Although previous investigations provide a strong link between EBV and gastric carcinomas, these studies were performed using selected EBV gene probes. Using a cohort of gastric carcinoma RNA-seq data sets from The Cancer Genome Atlas (TCGA), we performed a quantitative and global assessment of EBV gene expression in gastric carcinomas and assessed EBV associated cellular pathway alterations. EBV transcripts were detected in 17% of samples but these samples varied significantly in EBV coverage depth. In four samples with the highest EBV coverage (hiEBVaGC – high EBV associated gastric carcinoma), transcripts from the BamHI A region comprised the majority of EBV reads. Expression of LMP2, and to a lesser extent, LMP1 were also observed as was evidence of abortive lytic replication. Analysis of cellular gene expression indicated significant immune cell infiltration and a predominant IFNG response in samples expressing high levels of EBV transcripts relative to samples expressing low or no EBV transcripts. Despite the apparent immune cell infiltration, high levels of the cytotoxic T-cell (CTL) and natural killer (NK) cell inhibitor, IDO1, was observed in the hiEBVaGCs samples suggesting an active tolerance inducing pathway in this subgroup. These results were confirmed in a separate cohort of 21 Vietnamese gastric carcinoma samples using qRT-PCR and on tissue samples using in situ hybridization and immunohistochemistry. Lastly, a panel of tumor suppressors and candidate oncogenes were expressed at lower levels in hiEBVaGC versus EBV-low and EBV-negative gastric cancers suggesting the direct regulation of tumor pathways by EBV. [ABSTRACT FROM AUTHOR]

Demography impacts the observed standing level of genetic diversity present in populations. Distinguishing the relative impacts of demography from selection requires a baseline of expressed gene variation in naturally occurring populations. Six nuclear genes were sequenced to estimate the patterns and levels of genetic diversity in natural Arabidopsis lyrata subsp. petraea populations that differ in demographic histories since the Pleistocene. As expected, northern European populations have genetic signatures of a strong population bottleneck likely due to glaciation during the Pleistocene. Levels of diversity in the northern populations are about half of that in central European populations. Bayesian estimates of historical population size changes indicate that central European populations also have signatures of population size change since the last glacial maxima, suggesting that these populations are not as stable as previously thought. Time since divergence amongst northern European populations is higher than amongst central European populations, suggesting that the northern European populations were established before the Pleistocene and survived glaciation in small separated refugia. Estimates of demography based on expressed genes are complementary to estimates based on microsatellites and transposable elements, elucidating temporal shifts in population dynamics and confirming the importance of marker selection for tests of demography. [ABSTRACT FROM AUTHOR]