Cytoarchitectonic and chemoarchitectonic characterization of the prefrontal cortical areas in the mouse

This study describes cytoarchitectonic criteria to define the prefrontal cortical areas in the mouse brain (C57BL/6 strain). Currently, well-illustrated mouse brain stereotaxic atlases are available, which, however, do not provide a description of the distinctive cytoarchitectonic characteristics of individual prefrontal areas. Such a description is of importance for stereological, neuronal tracing, and physiological, molecular and neuroimaging studies in which a precise parcellation of the prefrontal cortex (PFC) is required. The present study describes and illustrates: the medial prefrontal areas, i.e., the infralimbic, prelimbic, dorsal and ventral anterior cingulate and Fr2 area; areas of the lateral PFC, i.e., the dorsal agranular insular cortical areas and areas of the ventral PFC, i.e., the lateral, ventrolateral, ventral and medial orbital areas. Each cytoarchitectonically defined boundary is corroborated by one or more chemoarchitectonic stainings, i.e., acetylcholine esterase, SMI32, SMI311, dopamine, parvalbumin, calbindin and myelin staining

Imaging of Functional Connectivity in the Mouse Brain

Functional neuroimaging (e.g., with fMRI) has been difficult to perform in mice, making it challenging to translate between human fMRI studies and molecular and genetic mechanisms. A method to easily perform large-scale functional neuroimaging in mice would enable the discovery of functional correlates of genetic manipulations and bridge with mouse models of disease. To satisfy this need, we combined resting-state functional connectivity mapping with optical intrinsic signal imaging (fcOIS). We demonstrate functional connectivity in mice through highly detailed fcOIS mapping of resting-state networks across most of the cerebral cortex. Synthesis of multiple network connectivity patterns through iterative parcellation and clustering provides a comprehensive map of the functional neuroarchitecture and demonstrates identification of the major functional regions of the mouse cerebral cortex. The method relies on simple and relatively inexpensive camera-based equipment, does not require exogenous contrast agents and involves only reflection of the scalp (the skull remains intact) making it minimally invasive. In principle, fcOIS allows new paradigms linking human neuroscience with the power of molecular/genetic manipulations in mouse models

Phenological response of grassland species to manipulative snowmelt and drought along an altitudinal gradient

Plant communities in the European Alps are assumed to be highly affected by climate change since temperature rise in this region is above the global average. It is predicted that higher temperatures will lead to advanced snowmelt dates and that the number of extreme weather events will increase. The aims of this study were to determine the impacts of extreme climatic events on flower phenology and to assess whether those impacts differed between lower and higher altitudes. In 2010 an experiment simulating advanced and delayed snowmelt as well as drought event was conducted along an altitudinal transect ca. every 250m (600-2000 m a.s.l.) in the Berchtesgaden National Park, Germany. The study showed that flower phenology is strongly affected by altitude; however there were few effects of the manipulative treatments on flowering. The effects of advanced snowmelt were significantly greater at higher than at lower sites, but no significant difference was found between both altitudinal bands for the other treatments. The response of flower phenology to temperature declined through the season and the length of flowering duration was not significantly influenced by treatments. The stronger effect of advanced snowmelt at higher altitudes might be a response to differences in treatment intensity across the gradient. Consequently, shifts in the date of snowmelt due to global warming may affect species more at higher than at lower altitudes since changes may be more pronounced at higher altitudes. Our data indicate a rather low risk of drought events on flowering phenology in the Bavarian Alps

MINOT: Modeling the intracluster medium (non-)thermal content and observable prediction tools

International audienceIn the past decade, the observations of diffuse radio synchrotron emission toward galaxy clusters revealed cosmic-ray (CR) electrons and magnetic fields on megaparsec scales. However, their origin remains poorly understood to date, and several models have been discussed in the literature. CR protons are also expected to accumulate during the formation of clusters and probably contribute to the production of these high-energy electrons. In order to understand the physics of CRs in clusters, combining of observations at various wavelengths is particularly relevant. The exploitation of such data requires using a self-consistent approach including both the thermal and the nonthermal components, so that it is capable of predicting observables associated with the multiwavelength probes at play, in particular in the radio, millimeter, X-ray, and γ-ray bands. We develop and describe such a self-consistent modeling framework, called MINOT (modeling the intracluster medium (non-)thermal content and observable prediction tools) and make this tool available to the community. MINOT models the intracluster diffuse components of a cluster (thermal and nonthermal) as spherically symmetric. It therefore focuses on CRs associated with radio halos. The spectral properties of the cluster CRs are also modeled using various possible approaches. All the thermodynamic properties of a cluster can be computed self-consistently, and the particle physics interactions at play are processed using a framework based on the Naima software. The multiwavelength observables (spectra, profiles, flux, and images) are computed based on the relevant physical process, according to the cluster location (sky and redshift), and based on the sampling defined by the user. With a standard personal computer, the computing time for most cases is far shorter than one second and it can reach about one second for the most complex models. This makes MINOT suitable for instance for Monte Carlo analyses. We describe the implementation of MINOT and how to use it. We also discuss the different assumptions and approximations that are involved and provide various examples regarding the production of output products at different wavelengths. As an illustration, we model the clusters Abell 1795, Abell 2142, and Abell 2255 and compare the MINOT predictions to literature data. While MINOT was originally build to simulate and model data in the γ-ray band, it can be used to model the cluster thermal and nonthermal physical processes for a wide variety of datasets in the radio, millimeter, X-ray, and γ-ray bands, as well as the neutrino emission

MINOT: Modeling the intracluster medium (non-)thermal content and observable prediction tools

In the past decade, the observations of diffuse radio synchrotron emission toward galaxy clusters revealed cosmic-ray (CR) electrons and magnetic fields on megaparsec scales. However, their origin remains poorly understood to date, and several models have been discussed in the literature. CR protons are also expected to accumulate during the formation of clusters and probably contribute to the production of these high-energy electrons. In order to understand the physics of CRs in clusters, combining of observations at various wavelengths is particularly relevant. The exploitation of such data requires using a self-consistent approach including both the thermal and the nonthermal components, so that it is capable of predicting observables associated with the multiwavelength probes at play, in particular in the radio, millimeter, X-ray, and γ-ray bands. We develop and describe such a self-consistent modeling framework, called MINOT (modeling the intracluster medium (non-)thermal content and observable prediction tools) and make this tool available to the community. MINOT models the intracluster diffuse components of a cluster (thermal and nonthermal) as spherically symmetric. It therefore focuses on CRs associated with radio halos. The spectral properties of the cluster CRs are also modeled using various possible approaches. All the thermodynamic properties of a cluster can be computed self-consistently, and the particle physics interactions at play are processed using a framework based on the Naima software. The multiwavelength observables (spectra, profiles, flux, and images) are computed based on the relevant physical process, according to the cluster location (sky and redshift), and based on the sampling defined by the user. With a standard personal computer, the computing time for most cases is far shorter than one second and it can reach about one second for the most complex models. This makes MINOT suitable for instance for Monte Carlo analyses. We describe the implementation of MINOT and how to use it. We also discuss the different assumptions and approximations that are involved and provide various examples regarding the production of output products at different wavelengths. As an illustration, we model the clusters Abell 1795, Abell 2142, and Abell 2255 and compare the MINOT predictions to literature data. While MINOT was originally build to simulate and model data in the γ-ray band, it can be used to model the cluster thermal and nonthermal physical processes for a wide variety of datasets in the radio, millimeter, X-ray, and γ-ray bands, as well as the neutrino emission

Neurotrophin-3 induced by tri-iodothyronine in cerebellar granule cells promotes Purkinje cell differentiation

Thyroid hormones play an important role in brain development, but the mechanism(s) by which triiodothyronine (T3) mediates neuronal differentiation is poorly understood. Here we demonstrate that T3 regulates the neurotrophic factor, neurotrophin-3 (NT-3), in developing rat cerebellar granule cells both in cell culture and in vivo. In situ hybridization experiments showed that developing Purkinje cells do not express NT-3 mRNA but do express trkC, the putative neuronal receptor for NT-3. Addition of recombinant NT-3 to cerebellar cultures from embryonic rat brain induces hypertrophy and neurite sprouting of Purkinje cells, and upregulates the mRNA encoding the calcium-binding protein, calbindin-28 kD. The present study demonstrates a novel interaction between cerebellar granule neurons and developing Purkinje cells in which NT-3 induced by T3 in the granule cells promotes Purkinje cell differentiation