Correlates of immune-mediated protection to most viral and cancer vaccines are still unknown. This impedes the development of novel vaccines to incurable diseases such as HIV and cancer. In this study, we have used functional genomics and polychromatic flow cytometry to define the signature of the immune response to the yellow fever (YF) vaccine 17D (YF17D) in a cohort of 40 volunteers followed for up to 1 yr after vaccination. We show that immunization with YF17D leads to an integrated immune response that includes several effector arms of innate immunity, including complement, the inflammasome, and interferons, as well as adaptive immunity as shown by an early T cell response followed by a brisk and variable B cell response. Development of these responses is preceded, as demonstrated in three independent vaccination trials and in a novel in vitro system of primary immune responses (modular immune in vitro construct [MIMIC] system), by the coordinated up-regulation of transcripts for specific transcription factors, including STAT1, IRF7, and ETS2, which are upstream of the different effector arms of the immune response. These results clearly show that the immune response to a strong vaccine is preceded by coordinated induction of master transcription factors that lead to the development of a broad, polyfunctional, and persistent immune response that integrates all effector cells of the immune system.

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River‐groundwater interactions are at the core of a wide range of major contemporary challenges, including the provision of high‐quality drinking water in sufficient quantities, the loss of biodiversity in river ecosystems, or the management of environmental flow regimes. This paper reviews state of the art approaches in characterizing and modeling river and groundwater interactions. Our review covers a wide range of approaches, including remote sensing to characterize the streambed, emerging methods to measure exchange fluxes between rivers and groundwater, and developments in several disciplines relevant to the river‐groundwater interface. We discuss approaches for automated calibration, and real‐time modeling, which improve the simulation and understanding of river‐groundwater interactions. Although the integration of these various approaches and disciplines is advancing, major research gaps remain to be filled to allow more complete and quantitative integration across disciplines. New possibilities for generating realistic distributions of streambed properties, in combination with more data and novel data types, have great potential to improve our understanding and predictive capabilities for river‐groundwater systems, especially in combination with the integrated simulation of the river and groundwater flow as well as calibration methods. Understanding the implications of different data types and resolution, the development of highly instrumented field sites, ongoing model development, and the ultimate integration of models and data are important future research areas. These developments are required to expand our current understanding to do justice to the complexity of natural systems.

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s u m m a r yBaseflow is often considered to be the groundwater discharge component of streamflow. It is commonly estimated using conceptual models, recursive filters or a combination of the two. However, it is difficult to validate these methods due to the current challenges of measuring baseflow in the field. In this study, simulation of a synthetic catchment's response to rainfall is carried out using a fully integrated surface water-groundwater flow model. A series of rainfall events with differing recovery periods and varied antecedent moisture conditions is considered to span a range of different streamflow generation dynamics. Baseflow is estimated for the outlet hydrograph of the synthetic catchment using a selection of commonly used automated baseflow separation methods. These estimates are compared to the baseflow signal obtained from the numerical model, which serves as the control experiment. Results from these comparisons show that depending on the method used, automated baseflow separation underestimates the simulated baseflow by as much as 28%, or overestimates it by up to 74%, during rainfall events. No separation method is found to be clearly superior to the others, as the performance of the various methods varies with different soil types, antecedent moisture conditions and rainfall events. The differences between the various approaches clearly demonstrate that the baseflow separation methods investigated are not universally applicable.