Impaired neonatal macrophage phagocytosis is not explained by overproduction of prostaglandin E2

<p>Abstract</p> <p>Background</p> <p>Neonates and young infants manifest increased susceptibility to bacterial, viral and fungal lung infections. Previous work has identified a role for eicosanoids in mediating host defense functions of macrophages. This study examines the relationship between alveolar macrophage (AM) host defense and production of lipid mediators during the neonatal period compared to adult AMs.</p> <p>Methods</p> <p>AMs were harvested from young (day 7 and day 14) and adult (~10 week) rats. The functionality of these cells was assessed by examining their ability to phagocytose opsonized targets, produce cytokines, eicosanoids and intracellular cAMP measured by enzyme immunoassays, and gene expression of proteins, enzymes and receptors essential for eicosanoid generation and phagocytosis measured by real time RT-PCR.</p> <p>Results</p> <p>AMs from young animals (day 7 and 14) were defective in their ability to phagocytose opsonized targets and produce tumor necrosis factor (TNF)- α. In addition, young AMs produce more prostaglandin (PG) E₂, a suppressor of host defense, and less leukotriene (LT) B₄, a promoter of host defense. Young AMs express higher levels of enzymes responsible for the production of PGE₂and LTB₄; however, there was no change in the expression of E prostanoid (EP) receptors or LT receptors. Despite the similar EP profiles, young AMs are more responsive to PGE₂as evidenced by their increased production of the important second messenger, cyclic AMP. In addition, young AMs express higher levels of PDE3B and lower levels of PDE4C compared to adult AMs. However, even though the young AMs produced a skewed eicosanoid profile, neither the inhibition of PGE₂by aspirin nor the addition of exogenous LTB₄rescued the defective opsonized phagocytosis. Examination of a receptor responsible for mediating opsonized phagocytosis showed a significant decrease in the gene expression levels of the Fcgamma receptor in young (day 7) AMs compared to adult AMs.</p> <p>Conclusion</p> <p>These results suggest that elevated production of PGE₂and decreased production of LTB₄do not contribute to impaired opsonized macrophage phagocytosis and highlight an important difference between young and adult AMs.</p

Environmental metabarcoding reveals contrasting belowground and aboveground fungal communities from poplar at a Hg phytomanagement site

Characterization of microbial communities in stressful conditions at a field level is rather scarce, especially when considering fungal communities from aboveground habitats. We aimed at characterizing fungal communities from different poplar habitats at a Hg-contaminated phytomanagement site by using Illumina-based sequencing, network analysis approach, and direct isolation of Hg-resistant fungal strains. The highest diversity estimated by the Shannon index was found for soil communities, which was negatively affected by soil Hg concentration. Among the significant correlations between soil operational taxonomic units (OTUs) in the co-occurrence network, 80% were negatively correlated revealing dominance of a pattern of mutual exclusion. The fungal communities associated with Populus roots mostly consisted of OTUs from the symbiotic guild, such as members of the Thelephoraceae, thus explaining the lowest diversity found for root communities. Additionally, root communities showed the highest network connectivity index, while rarely detected OTUs from the Glomeromycetes may have a central role in the root network. Unexpectedly high richness and diversity were found for aboveground habitats, compared to the root habitat. The aboveground habitats were dominated by yeasts from the Lalaria, Davidiella, and Bensingtonia genera, not detected in belowground habitats. Leaf and stem habitats were characterized by few dominant OTUs such as those from the Dothideomycete class producing mutual exclusion with other OTUs. Aureobasidium pullulans, one of the dominating OTUs, was further isolated from the leaf habitat, in addition to Nakazawaea populi species, which were found to be Hg resistant. Altogether, these findings will provide an improved point of reference for microbial research on inoculation-based programs of tailings dumps

Using social and behavioural science to support COVID-19 pandemic response

The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behavior with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic, and also highlight important gaps researchers should move quickly to fill in the coming weeks and months

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed

Particulate Fillers in Thermoplastics

The characteristics of particulate filled thermoplastics are determined by four factors: component properties, composition, structure and interfacial interactions. The most important filler characteristics are particle size, size distribution, specific surface area and particle shape, while the main matrix property is stiffness. Segregation, aggregation and the orientation of anisotropic particles determine structure. Interfacial interactions lead to the formation of a stiff interphase considerably influencing properties. Interactions are changed by surface modification, which must be always system specific and selected according to its goal. Under the effect of external load inhomogeneous stress distribution develops around heterogeneities, which initiate local micromechanical deformation processes determining the macroscopic properties of the composites