Recent Advances in the Diagnosis and Treatment of Influenza Pneumonia

A potentially fatal complication of influenza infection is the development of pneumonia, caused either directly by the influenza virus, or by secondary bacterial infection. Pneumonia related to the 2009 influenza A pandemic was found to be underestimated by commonly used pneumonia severity scores in many cases, and to be rapidly progressive, leading to respiratory failure. Confirmation of etiology by laboratory testing is warranted in such cases. Rapid antigen and immunofluorescence testing are useful screening tests, but have limited sensitivity. Confirmation of pandemic H1N1 influenza A infection can only be made by real-time reverse-transcriptase polymerase chain reaction (rRT-PCR) or viral culture. The most effective preventive measure is annual influenza vaccination in selected individuals. Decisions to administer antiviral medications for influenza treatment or chemoprophylaxis should be based upon clinical and epidemiological factors, and should not be delayed by confirmatory laboratory testing results. Neuraminidase inhibitors (NI) are the agents of choice

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Evaluation of coseasonality of influenza and invasive pneumococcal disease: results from prospective surveillance

BACKGROUND: The wintertime co-occurrence of peaks in influenza and invasive pneumococcal disease (IPD) is well documented, but how and whether wintertime peaks caused by these two pathogens are causally related is still uncertain. We aimed to investigate the relationship between influenza infection and IPD in Ontario, Canada, using several complementary methodological tools. METHODS AND FINDINGS: We evaluated a total number of 38,501 positive influenza tests in Central Ontario and 6,191 episodes of IPD in the Toronto/Peel area, Ontario, Canada, between 1 January 1995 and 3 October 2009, reported through population-based surveillance. We assessed the relationship between the seasonal wave forms for influenza and IPD using fast Fourier transforms in order to examine the relationship between these two pathogens over yearly timescales. We also used three complementary statistical methods (time-series methods, negative binomial regression, and case-crossover methods) to evaluate the short-term effect of influenza dynamics on pneumococcal risk. Annual periodicity with wintertime peaks could be demonstrated for IPD, whereas periodicity for influenza was less regular. As for long-term effects, phase and amplitude terms of pneumococcal and influenza seasonal sine waves were not correlated and meta-analysis confirmed significant heterogeneity of influenza, but not pneumococcal phase terms. In contrast, influenza was shown to Granger-cause pneumococcal disease. A short-term association between IPD and influenza could be demonstrated for 1-week lags in both case-crossover (odds ratio [95% confidence interval] for one case of IPD per 100 influenza cases  = 1.10 [1.02-1.18]) and negative binomial regression analysis (incidence rate ratio [95% confidence interval] for one case of IPD per 100 influenza cases  = 1.09 [1.05-1.14]). CONCLUSIONS: Our data support the hypothesis that influenza influences bacterial disease incidence by enhancing short-term risk of invasion in colonized individuals. The absence of correlation between seasonal waveforms, on the other hand, suggests that bacterial disease transmission is affected to a lesser extent. Please see later in the article for the Editors' Summary