Anti-IAV Monoclonal antibody, Clone B2[Biotin]

Influenza B viruses (IBVs) are major contributors to total human influenza disease, responsible for similar to 1/3 of all infections. These viruses, however, are relatively less studied than the related influenza A viruses (IAVs). While it has historically been assumed that the viral biology and mechanisms of pathogenesis for all influenza viruses were highly similar, studies have shown that IBVs possess unique characteristics. Relative to IAV, IBV encodes distinct viral proteins, displays a different mutational rate, has unique patterns of tropism, and elicits different immune responses. More work is therefore required to define the mechanisms of IBV pathogenesis. One valuable approach to characterize mechanisms of microbial disease is the use of genetically modified pathogens that harbor exogenous reporter genes. Over the last few years, IBV reporter viruses have been developed and used to provide new insights into the host response to infection, viral spread, and the testing of antiviral therapeutics. In this review, we will highlight the history and study of IBVs with particular emphasis on the use of genetically modified viruses and discuss some remaining gaps in knowledge that can be addressed using reporter expressing IBVs.

Since global reanalysis datasets first appeared in the 1990s, they have become an essential tool to understand the climate of the past. The wind power industry uses those products extensively for wind resource assessment, while several climate services for energy rely on them as well. Nowadays various datasets coexist, which complicates the selection of the most suitable source for each purpose. In an effort to identify the products that best represent the wind speed features at turbine hub heights, five state-of-the-art global reanalyses have been analysed: ERA5, ERA-Interim, the Japanese 55-year Reanalysis (JRA55), the Modern Era Retrospective Analysis for Research and Applications-2 (MERRA2), and the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) Reanalysis 1 (R1). A multi-reanalysis ensemble approach is used to explore the main differences amongst these datasets in terms of surface wind characteristics. Then, the quality of the surface and near-surface winds is evaluated with a set of 77 instrumented tall towers. Results reveal that important discrepancies exist in terms of boreal winter seasonal means, interannual variability (IAV), and decadal linear trends. The differences in the computation of these parameters, which are mainly concentrated inland, reach up to the order of magnitude of the parameters themselves. Comparison with in situ observations shows that the ERA5 surface winds offer the best agreement, correlating and reproducing the observed variability better than a multi-reanalysis mean in 35.1% of the tall tower sites on a daily time-scale. However, none of the reanalyses stands out from the others when comparing seasonal mean winds. Regarding the IAV, near-surface winds from ERA5 offer the values closest to the observed IAV.