Astrocyte-derived interleukin-6 promotes specific neuronal differentiation of neural progenitor cells from adult hippocampus

The purpose of this study was to investigate the ability of astrocyte-derived factors to influence neural progenitor cell differentiation. We previously demonstrated that rat adult hippocampal progenitor cells (AHPCs) immunoreactive for the neuronal marker, class III β-tubulin (TUJ1) were significantly increased in the presence of astrocyte-derived soluble factors under non-contact co-culture conditions. Using whole cell patch clamp analysis, we observed that the co-cultured AHPCs displayed two prominent voltage-gated conductances - tetraethyl ammonium (TEA)- sensitive outward currents and fast transient inward currents. The outward and inward current densities of the co-cultured AHPCs were approximately 2.5-fold and 1.7-fold greater, respectively, than those of cells cultured alone. These results suggest that astrocyte-derived soluble factors induce neuronal commitment of AHPCs. To further investigate the activity of a candidate neurogenic factor on AHPC differentiation, we cultured AHPCs in the presence or absence of purified rat recombinant interleukin-6 (IL-6). We also confirmed that the astrocytes used in this study produced IL-6 by ELISA and RT-qPCR. When AHPCs were cultured with IL-6 for 6-7 days, the TUJ1-immunoreactive AHPCs and the average length of TUJ1-immunoreactive neurites were significantly increased, compared to the cells cultured without IL-6. Moreover, IL-6 increased the inward current density to a comparable extent as did co-culture with astrocytes, with no significant differences in the outward current density, apparent resting potential, or cell capacitance. These results suggest that astrocyte-derived IL-6 may facilitate AHPC neuronal differentiation. Our findings have important implications for understanding injury-induced neurogenesis and developing cell-based therapeutic strategies using neural progenitors

A Mathematical Model for Selective Differentiation of Neural Progenitor Cells on Micropatterned Polymer Substrates

The biological hypothesis that the astrocyte-secreted cytokine, interleukin-6 (IL6), stimulates differentiation of adult rat hippocampal progenitor cells (AHPCs) is considered from a mathematical perspective. The proposed mathematical model includes two different mechanisms for stimulation and is based on mass–action kinetics. Both biological mechanisms involve sequential binding, with one pathway solely utilizing surface receptors while the other pathway also involves soluble receptors. Choosing biologically-reasonable values for parameters, simulations of the mathematical model show good agreement with experimental results. A global sensitivity analysis is also conducted to determine both the most influential and non-influential parameters on cellular differentiation, providing additional insights into the biological mechanisms

Myths and Truths Concerning Estimation of Power Spectra

It is widely believed that maximum likelihood estimators must be used to provide optimal estimates of power spectra. Since such estimators require require of order N_d^3 operations they are computationally prohibitive for N_d greater than a few tens of thousands. Because of this, a large and inhomogeneous literature exists on approximate methods of power spectrum estimation. These range from manifestly sub-optimal, but computationally fast methods, to near optimal but computationally expensive methods. Furthermore, much of this literature concentrates on the power spectrum estimates rather than the equally important problem of deriving an accurate covariance matrix. In this paper, I consider the problem of estimating the power spectrum of cosmic microwave background (CMB) anisotropies from large data sets. Various analytic results on power spectrum estimators are derived, or collated from the literature, and tested against numerical simulations. An unbiased hybrid estimator is proposed that combines a maximum likelihood estimator at low multipoles and pseudo-C_\ell estimates at high multipoles. The hybrid estimator is computationally fast, nearly optimal over the full range of multipoles, and returns an accurate and nearly diagonal covariance matrix for realistic experimental configurations (provided certain conditions on the noise properties of the experiment are satisfied). It is argued that, in practice, computationally expensive methods that approximate the N_d^3 maximum likelihood solution are unlikely to improve on the hybrid estimator, and may actually perform worse. The results presented here can be generalised to CMB polarization and to power spectrum estimation using other types of data, such as galaxy clustering and weak gravitational lensing.Comment: 27 pages, 15 figures, MNRAS in press. Resubmission matches accepted versio

Cosmic Microwave Background Anisotropy Window Functions Revisited

The primary results of most observations of cosmic microwave background (CMB) anisotropy are estimates of the angular power spectrum averaged through some broad band, called band-powers. These estimates are in turn what are used to produce constraints on cosmological parameters due to all CMB observations. Essential to this estimation of cosmological parameters is the calculation of the expected band-power for a given experiment, given a theoretical power spectrum. Here we derive the "band power" window function which should be used for this calculation, and point out that it is not equivalent to the window function used to calculate the variance. This important distinction has been absent from much of the literature: the variance window function is often used as the band-power window function. We discuss the validity of this assumed equivalence, the role of window functions for experiments that constrain the power in {\it multiple} bands, and summarize a prescription for reporting experimental results. The analysis methods detailed here are applied in a companion paper to three years of data from the Medium Scale Anisotropy Measurement.Comment: 5 pages, 1 included .eps figure, PRD in press---final published versio

Oil prices, tourism income and economic growth: A structural VAR approach for European Mediterranean countries

In this study, a Structural VAR model is employed to investigate the relationship among oil price shocks, tourism variables and economic indicators in four European Mediterranean countries. In contrast with the current tourism literature, we distinguish between three oil price shocks, namely, supply-side, aggregate demand and oil specific demand shocks. Overall, our results indicate that oil specific demand shocks contemporaneously affect inflation and the tourism sector equity index, whereas these shocks do not seem to have any lagged effects. By contrast, aggregate demand oil price shocks exercise a lagged effect, either directly or indirectly, to tourism generated income and economic growth. The paper does not provide any evidence that supply-side shocks trigger any responses from the remaining variables. Results are important for tourism agents and policy makers, should they need to create hedging strategies against future oil price movements or plan for economic policy developments

Fast, exact CMB power spectrum estimation for a certain class of observational strategies

We describe a class of observational strategies for probing the anisotropies in the cosmic microwave background (CMB) where the instrument scans on rings which can be combined into an n-torus, the {\em ring torus}. This class has the remarkable property that it allows exact maximum likelihood power spectrum estimation in of order $N^2$ operations (if the size of the data set is $N$) under circumstances which would previously have made this analysis intractable: correlated receiver noise, arbitrary asymmetric beam shapes and far side lobes, non-uniform distribution of integration time on the sky and partial sky coverage. This ease of computation gives us an important theoretical tool for understanding the impact of instrumental effects on CMB observables and hence for the design and analysis of the CMB observations of the future. There are members of this class which closely approximate the MAP and Planck satellite missions. We present a numerical example where we apply our ring torus methods to a simulated data set from a CMB mission covering a 20 degree patch on the sky to compute the maximum likelihood estimate of the power spectrum $C_\ell$ with unprecedented efficiency.Comment: RevTeX, 14 pages, 5 figures. A full resolution version of Figure 1 and additional materials are at http://feynman.princeton.edu/~bwandelt/RT

Bayesian analysis of spatially distorted cosmic signals from Poissonian data

Reconstructing the matter density field from galaxy counts is a problem frequently addressed in current literature. Two main sources of error are shot noise from galaxy counts and insufficient knowledge of the correct galaxy position caused by peculiar velocities and redshift measurement uncertainty. Here we address the reconstruction problem of a Poissonian sampled log-normal density field with velocity distortions in a Bayesian way via a maximum a posteriory method. We test our algorithm on a 1D toy case and find significant improvement compared to simple data inversion. In particular, we address the following problems: photometric redshifts, mapping of extended sources in coded mask systems, real space reconstruction from redshift space galaxy distribution and combined analysis of data with different point spread functions.Comment: 19 pages, 10 figures, accepte

Quantification of the Frequency and Multiplicity of Infection of Respiratory- and Lymph Node–Resident Dendritic Cells During Influenza Virus Infection

Background: Previous studies have demonstrated that DC differentially regulate influenza A virus (IAV)–specific CD8 T cell responses in vivo during high and low dose IAV infections. Furthermore, in vitro infection of DC with IAV at low versus high multiplicities of infection (MOI) results in altered cytokine production and a reduced ability to prime naïve CD8 T cell responses. Flow cytometric detection of IAV proteins within DC, a commonly used method for detection of cellular IAV infection, does not distinguish between the direct infection of these cells or their uptake of viral proteins from dying epithelial cells. Methods/Principal Findings: We have developed a novel, sensitive, single-cell RT-PCR–based approach to assess the infection of respiratory DC (rDC) and lymph node (LN)-resident DC (LNDC) following high and low dose IAV infections. Our results show that, while a fraction of both rDC and LNDC contain viral mRNA following IAV infection, there is little correlation between the percentage of rDC containing viral mRNA and the initial IAV inoculum dose. Instead, increasing IAV inoculums correlate with augmented rDC MOI. Conclusion/Significance: Together, our results demonstrate a novel and sensitive method for the detection of direct IAV infection at the single-cell level and suggest that the previously described ability of DC to differentially regulate IAV-specific T cell responses during high and low dose IAV infections could relate to the MOI of rDC within the LN rather than th

Organ aging signatures in the plasma proteome track health and disease

Animal studies show aging varies between individuals as well as between organs within an individua