Induction of SerpinB2 and Th1/Th2 Modulation by SerpinB2 during Lentiviral Infections In Vivo

SerpinB2, also known as plasminogen activator inhibitor type 2, is a major product of activated monocytes/macrophages and is often strongly induced during infection and inflammation; however, its physiological function remains somewhat elusive. Herein we show that SerpinB2 is induced in peripheral blood mononuclear cells following infection of pigtail macaques with CCR5-utilizing (macrophage-tropic) SIV_mac239, but not the rapidly pathogenic CXCR4-utilizing (T cell-tropic) SHIV_mn229. To investigate the role of SerpinB2 in lentiviral infections, SerpinB2^−/− mice were infected with EcoHIV, a chimeric HIV in which HIV gp120 has been replaced with gp80 from ecotropic murine leukemia virus. EcoHIV infected SerpinB2^−/− mice produced significantly lower anti-gag IgG1 antibody titres than infected SerpinB2^+/+ mice, and showed slightly delayed clearance of EcoHIV. Analyses of published microarray studies showed significantly higher levels of SerpinB2 mRNA in monocytes from HIV-1 infected patients when compared with uninfected controls, as well as a significant negative correlation between SerpinB2 and T-bet mRNA levels in peripheral blood mononuclear cells. These data illustrate that SerpinB2 can be induced by lentiviral infection in vivo and support the emerging notion that a physiological role of SerpinB2 is modulation of Th1/Th2 responses.     

Influences of temporal independence of data on modelling species distributions

Modelling species distributions has been widely used to understand present and future potential distributions of species, and can provide adaptation and mitigation information as references for conservation and management under climate change. However, various methods of data splitting to develop and validate functions of the models do not get enough attention, which may mislead the interpretation of predicted results. We used the Taiwanese endemic birds to test the influences of temporal independence of datasets on model performance and prediction. Training and testing data were considered to be independent if they were collected during different survey periods (1993–2004 and 2009–2010). The results indicated no significant differences of six model performance measures (AUC, kappa, TSS, accuracy, sensitivity, and specificity) among the combinations of training and testing datasets. Both species- and grid cell-based assessments differed significantly between predictions by the annual and pooled training data. We also found an average of 85.8% similarity for species presences and absences in different survey periods. The remaining dissimilarity was mostly caused by species observed in the late survey period but not in the early one. The method of data splitting, yielding training and testing data, is critical for resulting model species distributions. Even if similar model performance exists, different methods can lead to different species distributional maps. More attention needs to be given to this issue, especially when amplifying these models to project species distributions in a changing world.     

Effect of adenovirus and influenza virus infection on obesity

The purpose of this review is to provide an overview of the effects of adenovirus and influenza virus infections on obesity in various experimental models. We reviewed studies that were conducted within the past 10 years and were related to virus infection and obesity prevalence. Here, we discuss a different causal relationship between adenovirus and influenza infections with obesity. Adenovirus infection can cause obesity, whereas obesity can be a risk factor for increasing influenza virus infection and increases the risk of morbidity and mortality. The prevalence of obesity due to adenovirus infections may be due to an increase in glucose uptake and reduction in lipolysis caused by an increase in corticosterone secretion. Adenovirus infections may lead to increases in appetite by decreasing norepinephrine and leptin levels and also cause immune dysfunction. The relationship between obesity and influenza virus infection could be summarized by the following features: decreases in memory T-cell functionality and interferon (IFN)-α, IFN-β, and IFN-γ mRNA expression, increases in viral titer and infiltration, and impaired dendritic cell function in obese individuals. Moreover, leptin resistance may play an important role in increasing influenza virus infections in obese individuals. In conclusion, prevention of adenovirus infections could be a good approach for reducing obesity prevalence, and prevention of obesity could reduce influenza virus infections from the point of view of viral infections and obesity.