Maternal fluoxetine exposure alters cortical hemodynamic and calcium response of offspring to somatosensory stimuli

Epidemiological studies have found an increased incidence of neurodevelopmental disorders in populations prenatally exposed to selective serotonin reuptake inhibitors (SSRIs). Optical imaging provides a minimally invasive way to determine if perinatal SSRI exposure has long-term effects on cortical function. Herein we probed the functional neuroimaging effects of perinatal SSRI exposure in a fluoxetine (FLX)-exposed mouse model. While resting-state homotopic contralateral functional connectivity was unperturbed, the evoked cortical response to forepaw stimulation was altered in FLX mice. The stimulated cortex showed decreased activity for FLX versus controls, by both hemodynamic responses [oxyhemoglobin (Hb

ISO spectroscopy of circumstellar dust in the Herbig Ae systems AB Aur and HD 163296

Using both the Short- and Long-wavelength Spectrometers on board the Infrared Space Observatory (ISO), we have obtained infrared spectra of the Herbig Ae systems AB Aur and HD 163296. In addition, we obtained ground-based N band images of HD 163296. Our results can be summarized as follows: (1) The main dust components in AB Aur are amorphous silicates, iron oxide and PAHs; (2) The circumstellar dust in HD 163296 consists of amorphous silicates, iron oxide, water ice and a small fraction of crystalline silicates; (3) The infrared fluxes of HD 163296 are dominated by solid state features; (4) The colour temperature of the underlying continuum is much cooler in HD 163296 than in AB Aur, pointing to the existence of a population of very large (mm sized) dust grains in HD 163296; (5) The composition and degree of crystallization of circumstellar dust are poorly correlated with the age of the central star. The processes of crystallization and grain growth are also not necessarily coupled. This means that either the evolution of circumstellar dust in protoplanetary disks happens very rapidly (within a few Myr), or that this evolution is governed by factors other than stellar mass and age.Comment: 6 pages, 2 figures, accepted for publication in Astronomy & Astrophysic

Structure of a Cyclophane Host Molecule

The cyclophane tetramethyl 3,8,13,18a,2l,26,31,36aoctahydro- 4,6:9,12:22,24:27,30-tetraetheno-l5,18,21:-33,36,39-diethenylylidenedibenzo[k,ɑl][1,8,17,24]tetraoxacyclodotriacontene-1,2,19,20-tetracarboxylate acetonitrile solvate, C_(56)H_(44)O_(12).CH_3C=N, contains a large cavity and forms host-guest complexes in solution with a variety of quaternary nitrogen compounds. Crystallization from an acetonitrile solution that contained damantyltrimethylammonium iodide led, though, to crystals of the uncomplexed cyclophane (but containing one molecule of acetonitrile of crystallization). The cavity, about 7.6 x 4.0 Å and roughly rectangular in cross section, is occupied by ester groupings from two adjacent cyclophanes, entering from opposite sides. Crystal data: orthorhombic, P2_12_12_1, with a= 11.741 (6), b = 16.155 (5), c = 25.895 (7) Å, v = 4912 Å^3, T = 296 K, Z = 4, M_r= 950.01, D_x = 1.28 g cm^(-3), F(000) = 1992, Mo Kɑ, λ = 0.7107 Å, μ = 0.84 cm^(-1), R = 0.0538 for 2410 independent reflections with I> 0, S = 2.29 for 2610 total reflections

Suite of simple metrics reveals common movement syndromes across vertebrate taxa

ecause empirical studies of animal movement are most-often site- and species-specific, we lack understanding of the level of consistency in movement patterns across diverse taxa, as well as a framework for quantitatively classifying movement patterns. We aim to address this gap by determining the extent to which statistical signatures of animal movement patterns recur across ecological systems. We assessed a suite of movement metrics derived from GPS trajectories of thirteen marine and terrestrial vertebrate species spanning three taxonomic classes, orders of magnitude in body size, and modes of movement (swimming, flying, walking). Using these metrics, we performed a principal components analysis and cluster analysis to determine if individuals organized into statistically distinct clusters. Finally, to identify and interpret commonalities within clusters, we compared them to computer-simulated idealized movement syndromes representing suites of correlated movement traits observed across taxa (migration, nomadism, territoriality, and central place foraging)

Non-thermal high-energy emission from colliding winds of massive stars

Colliding winds of massive star binary systems are considered as potential sites of non-thermal high-energy photon production. This is motivated merely by the detection of synchrotron radio emission from the expected colliding wind location. Here we investigate the properties of high-energy photon production in colliding winds of long-period WR+OB-systems. We found that in the dominating leptonic radiation process anisotropy and Klein-Nishina effects may yield spectral and variability signatures in the gamma-ray domain at or above the sensitivity of current or upcoming gamma-ray telescopes. Analytical formulae for the steady-state particle spectra are derived assuming diffusive particle acceleration out of a pool of thermal wind particles, and taking into account adiabatic and all relevant radiative losses. For the first time we include their advection/convection in the wind collision zone, and distinguish two regions within this extended region: the acceleration region where spatial diffusion is superior to convective/advective motion, and the convection region defined by the convection time shorter than the diffusion time scale. The calculation of the Inverse Compton radiation uses the full Klein-Nishina cross section, and takes into account the anisotropic nature of the scattering process. This leads to orbital flux variations by up to several orders of magnitude which may, however, be blurred by the geometry of the system. The calculations are applied to the typical WR+OB-systems WR 140 and WR 147 to yield predictions of their expected spectral and temporal characteristica and to evaluate chances to detect high-energy emission with the current and upcoming gamma-ray experiments. (abridged)Comment: 67 pages, 24 figures, submitted to Ap

A Very Large Array 3.6cm continuum survey of Galactic Wolf-Rayet stars

We report the results of a survey of radio continuum emission of Galactic Wolf-Rayet stars north of declination -46 degrees. The observations were obtained at 8.46 GHz (3.6cm) using the Very Large Array (VLA), with an angular resolution of about 6 x 9 arcsec and typical rms noise of 0.04 mJy/beam. Our survey of 34 WR stars resulted in 15 definite and 5 probable detections, 13 of these for the first time at radio wavelengths. All detections are unresolved. Time variations in flux are confirmed in the cases of WR98a, WR104, WR105 and WR125. WR79a and WR89 are also variable in flux and we suspect they are also non-thermal emitters. Thus, of our sample 20-30% of the detected stars are non-thermal emiters. Average mass loss rates determinations obtained excluding definite and suspected non-thermal cases give similar values for WN (all subtypes) and WC5-7 stars, while a lower value was obtained for WC8-9 stars. Uncertainties in stellar distances largely contribute to the observed scatter in mass loss rates. Upper limits to the mass loss rates were obtained in cases of undetected sources or for sources which probably show additional non-thermal emission.Comment: 21 pages, Latex, 21 postscript figures, to be published in The Astronomical Journal, May 200

Knowledge-based gene expression classification via matrix factorization

Motivation: Modern machine learning methods based on matrix decomposition techniques, like independent component analysis (ICA) or non-negative matrix factorization (NMF), provide new and efficient analysis tools which are currently explored to analyze gene expression profiles. These exploratory feature extraction techniques yield expression modes (ICA) or metagenes (NMF). These extracted features are considered indicative of underlying regulatory processes. They can as well be applied to the classification of gene expression datasets by grouping samples into different categories for diagnostic purposes or group genes into functional categories for further investigation of related metabolic pathways and regulatory networks. Results: In this study we focus on unsupervised matrix factorization techniques and apply ICA and sparse NMF to microarray datasets. The latter monitor the gene expression levels of human peripheral blood cells during differentiation from monocytes to macrophages. We show that these tools are able to identify relevant signatures in the deduced component matrices and extract informative sets of marker genes from these gene expression profiles. The methods rely on the joint discriminative power of a set of marker genes rather than on single marker genes. With these sets of marker genes, corroborated by leave-one-out or random forest cross-validation, the datasets could easily be classified into related diagnostic categories. The latter correspond to either monocytes versus macrophages or healthy vs Niemann Pick C disease patients.Siemens AG, MunichDFG (Graduate College 638)DAAD (PPP Luso - Alem˜a and PPP Hispano - Alemanas