Dynamics of the nasal microbiota in infancy: A prospective cohort study.

BACKGROUND Understanding the composition and dynamics of the upper respiratory tract microbiota in healthy infants is a prerequisite to investigate the role of the microbiota in patients with respiratory diseases. This is especially true in early life, when the immune system is in development. OBJECTIVE We sought to describe the dynamics of the upper respiratory tract microbiota in healthy infants within the first year of life. METHODS After exclusion of low-quality samples, microbiota characterization was performed by using 16S rDNA pyrosequencing of 872 nasal swabs collected biweekly from 47 unselected infants. RESULTS Bacterial density increased and diversity decreased within the first year of life (R(2) = 0.95 and 0.73, respectively). A distinct profile for the first 3 months of life was found with increased relative abundances of Staphlyococcaceae and Corynebacteriaceae (exponential decay: R(2) = 0.94 and 0.96, respectively). In addition, relative bacterial abundance and composition differed significantly from summer to winter months. The individual composition of the microbiota changed with increasing time intervals between samples and was best modeled by an exponential function (R(2) = 0.97). Within-subject dissimilarity in a 2-week time interval was consistently lower than that between subjects, indicating a personalized microbiota. CONCLUSION This study reveals age and seasonality as major factors driving the composition of the nasal microbiota within the first year of life. A subject's microbiota is personalized but dynamic throughout the first year. These data are indispensable to interpretation of cross-sectional studies and investigation of the role of the microbiota in both healthy subjects and patients with respiratory diseases. They might also serve as a baseline for future intervention studies.

Detection efficiency of microchannel plates for e(-) and pi(-) in the momentum range from 17.5 to 345 MeV/c

High-energy e(-) and pi(-) were measured by the multichannel plate (MCP) detector at the PiM1 beam line of the High Intensity Proton Accelerator Facilities located at the Paul Scherrer Institute, Villigen, Switzerland. The measurements provide the absolute detection efficiencies for these particles: 5.8% +/- 0.5% for electrons in the beam momenta range 17.5-300 MeV/c and 6.0% +/- 1.3% for pions in the beam momenta range 172-345 MeV/c. The pulse height distribution determined from the measurements is close to an exponential function with negative exponent, indicating that the particles penetrated the MCP material before producing the signal somewhere inside the channel. Low charge extraction and nominal gains of the MCP detector observed in this study are consistent with the proposed mechanism of the signal formation by penetrating radiation. A very similar MCP ion detector will be used in the Neutral Ion Mass (NIM) spectrometer designed for the JUICE mission of European Space Agency (ESA) to the Jupiter system, to perform measurements of the chemical composition of the Galilean moon exospheres. The detection efficiency for penetrating radiation determined in the present studies is important for the optimisation of the radiation shielding of the NIM detector against the high-rate and high-energy electrons trapped in Jupiter's magnetic field. Furthermore, the current studies indicate that MCP detectors can be useful to measure high-energy particle beams at high temporal resolution. (C) 2015 AIP Publishing LLC.

Non-exponential return time distributions for vorticity extremes explained by fractional Poisson processes

Serial correlation of extreme midlatitude cyclones observed at the storm track exits is explained by deviations from a Poisson process. To model these deviations, we apply fractional Poisson processes (FPPs) to extreme midlatitude cyclones, which are defined by the 850 hPa relative vorticity of the ERA interim reanalysis during boreal winter (DJF) and summer (JJA) seasons. Extremes are defined by a 99% quantile threshold in the grid-point time series. In general, FPPs are based on long-term memory and lead to non-exponential return time distributions. The return times are described by a Weibull distribution to approximate the Mittag–Leffler function in the FPPs. The Weibull shape parameter yields a dispersion parameter that agrees with results found for midlatitude cyclones. The memory of the FPP, which is determined by detrended fluctuation analysis, provides an independent estimate for the shape parameter. Thus, the analysis exhibits a concise framework of the deviation from Poisson statistics (by a dispersion parameter), non-exponential return times and memory (correlation) on the basis of a single parameter. The results have potential implications for the predictability of extreme cyclones.