Enhancing the Capacity of Community Health Centers to Achieve High Performance

Based on a survey of community health centers, assesses access to care, care coordination, quality improvement efforts, health information technology adoption, and ability to serve as patient-centered medical homes. Suggests policy to strengthen clinics

Closing the Divide: How Medical Homes Promote Equity in Health Care

Presents findings from the Commonwealth Fund 2006 Health Care Quality Survey, and demonstrates how having stable insurance, a regular provider and, in particular, a medical home, improves health care access and quality among vulnerable populations

ARHGEF18/p114RhoGEF Coordinates PKA/CREB Signaling and Actomyosin Remodeling to Promote Trophoblast Cell-Cell Fusion During Placenta Morphogenesis

Coordination of cell-cell adhesion, actomyosin dynamics and gene expression is crucial for morphogenetic processes underlying tissue and organ development. Rho GTPases are main regulators of the cytoskeleton and adhesion. They are activated by guanine nucleotide exchange factors in a spatially and temporally controlled manner. However, the roles of these Rho GTPase activators during complex developmental processes are still poorly understood. ARHGEF18/p114RhoGEF is a tight junction-associated RhoA activator that forms complexes with myosin II, and regulates actomyosin contractility. Here we show that p114RhoGEF/ARHGEF18 is required for mouse syncytiotrophoblast differentiation and placenta development. In vitro and in vivo experiments identify that p114RhoGEF controls expression of AKAP12, a protein regulating protein kinase A (PKA) signaling, and is required for PKA-induced actomyosin remodeling, cAMP-responsive element binding protein (CREB)-driven gene expression of proteins required for trophoblast differentiation, and, hence, trophoblast cell-cell fusion. Our data thus indicate that p114RhoGEF links actomyosin dynamics and cell-cell junctions to PKA/CREB signaling, gene expression and cell-cell fusion

Should I grow wildflowers? Agrilink, your growing guide to better farming

Each Agrilink kit has been designed to be both comprehensive and practical. As the kits are arranged to answer questions of increasing complexity, they are useful references for both new and experienced producers of specific crops. Agrilink integrates the technology of horticultural production with the management of horticultural enterprises. REPRINT INFORMATION - PLEASE READ! For updated information please call 13 25 23 or visit the website www.deedi.qld.gov.au (Select: Queensland Industries – Agriculture link) This publication has been reprinted as a digital book without any changes to the content published in 2000. We advise readers to take particular note of the areas most likely to be out-of-date and so requiring further research: see detailed information on first page of the kit. Even with these limitations we believe this information kit provides important and valuable information for intending and existing growers. This publication was last revised in 2000. The information is not current and the accuracy of the information cannot be guaranteed by the State of Queensland. This information has been made available to assist users to identify issues involved in the production of wildflowers. This information is not to be used or relied upon by users for any purpose which may expose the user or any other person to loss or damage. Users should conduct their own inquiries and rely on their own independent professional advice. While every care has been taken in preparing this publication, the State of Queensland accepts no responsibility for decisions or actions taken as a result of any data, information, statement or advice, expressed or implied, contained in this publication

Comparing families of dynamic causal models

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This “best model” approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data

Complex sequencing rules of birdsong can be explained by simple hidden Markov processes

Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical propertiesof the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable sequences, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. This property is shared with other complex sequential behaviors. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model (GMM)), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex sequences with higher-order dependencies

Isotope effect in superconductors with coexisting interactions of phonon and nonphonon mechanisms

We examine the isotope effect of superconductivity in systems with coexisting interactions of phonon and nonphonon mechanisms in addition to the direct Coulomb interaction. The interaction mediated by the spin fluctuations is discussed as an example of the nonphonon interaction. Extended formulas for the transition temperature Tc and the isotope-effect coefficient alpha are derived for cases (a) omega_np omega_D, where omega_np is an effective cutoff frequency of the nonphonon interaction that corresponds to the Debye frequency omega_D in the phonon interaction. In case (a), it is found that the nonphonon interaction does not change the condition for the inverse isotope effect, i.e., mu^* > lambda_ph/2, but it modifies the magnitude of alpha markedly. In particular, it is found that a giant isotope shift occurs when the phonon and nonphonon interactions cancel each other largely. For instance, strong critical spin fluctuations may give rise to the giant isotope effect. In case (b), it is found that the inverse isotope effect occurs only when the nonphonon interaction and the repulsive Coulomb interaction, in total effect, work as repulsive interactions against the superconductivity. We discuss the relevance of the present result to some organic superconductors, such as kappa-(ET)2Cu(NCS)2 and Sr2RuO4 superconductors, in which inverse isotope effects have been observed, and briefly to high-Tc cuprates, in which giant isotope effects have been observed.Comment: 4 pages, 2 figures, (with jpsj2.cls, ver.1.2), v2:linguistic correction

Macrophage subsets exhibit distinct E. coli-LPS tolerisable cytokines associated with the negative regulators, IRAK-M and Tollip

<div><p>Macrophages (Mϕs) play a central role in mucosal immunity by pathogen sensing and instruction of adaptive immune responses. Prior challenge to endotoxin can render Mφs refractory to secondary exposure, suppressing the inflammatory response. Previous studies demonstrated a differential subset-specific sensitivity to endotoxin tolerance (ET), mediated by LPS from the oral pathogen, <i>Porphyromonas gingivalis</i> (PG). The aim of this study was to investigate ET mechanisms associated with Mφ subsets responding to entropathogenic <i>E</i>. <i>coli</i> K12-LPS. M1- and M2-like Mφs were generated <i>in vitro</i> from the THP-1 cell line by differentiation with PMA and Vitamin D₃, respectively. This study investigated ET mechanisms induced in M1 and M2 Mφ subsets, by measuring modulation of expression by RT-PCR, secretion of cytokines by sandwich ELISA, LPS receptor, TLR4, as well as endogenous TLR inhibitors, IRAK-M and Tollip by Western blotting. In contrast to PG-LPS tolerisation, <i>E</i>. <i>coli</i> K12-LPS induced ET failed to exhibit a subset-specific response with respect to the pro-inflammatory cytokine, TNFα, whereas exhibited a differential response for IL-10 and IL-6. TNFα expression and secretion was significantly suppressed in both M1- and M2-like Mφs. IL-10 and IL-6, on the other hand, were suppressed in M1s and refractory to suppression in M2s. ET suppressed TLR4 mRNA, but not TLR4 protein, yet induced differential augmentation of the negative regulatory molecules, Tollip in M1 and IRAK-M in M2 Mφs. In conclusion, <i>E</i>. <i>coli</i> K12-LPS differentially tolerises Mφ subsets at the level of anti-inflammatory cytokines, associated with a subset-specific divergence in negative regulators and independent of TLR4 down-regulation.</p></div

Indirect Exchange Interaction between two Quantum Dots in an Aharonov-Bohm Ring

We investigate the Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction between two spins located at two quantum dots embedded in an Aharonov-Bohm (AB) ring. In such a system the RKKY interaction, which oscillates as a function of the distance between two local spins, is affected by the flux. For the case of the ferromagnetic RKKY interaction, we find that the amplitude of AB oscillations is enhanced by the Kondo correlations and an additional maximum appears at half flux, where the interaction is switched off. For the case of the antiferromagnetic RKKY interaction, we find that the phase of AB oscillations is shifted by pi, which is attributed to the formation of a singlet state between two spins for the flux value close to integer value of flux.Comment: 10 pages, 5 figure

Electric Field Effects on Graphene Materials

Understanding the effect of electric fields on the physical and chemical properties of two-dimensional (2D) nanostructures is instrumental in the design of novel electronic and optoelectronic devices. Several of those properties are characterized in terms of the dielectric constant which play an important role on capacitance, conductivity, screening, dielectric losses and refractive index. Here we review our recent theoretical studies using density functional calculations including van der Waals interactions on two types of layered materials of similar two-dimensional molecular geometry but remarkably different electronic structures, that is, graphene and molybdenum disulphide (MoS$_2$). We focus on such two-dimensional crystals because of they complementary physical and chemical properties, and the appealing interest to incorporate them in the next generation of electronic and optoelectronic devices. We predict that the effective dielectric constant ($\varepsilon$) of few-layer graphene and MoS$_2$ is tunable by external electric fields ($E_{\rm ext}$). We show that at low fields ($E_{\rm ext}^{}<0.01$ V/\AA) $\varepsilon$ assumes a nearly constant value $\sim$4 for both materials, but increases at higher fields to values that depend on the layer thickness. The thicker the structure the stronger is the modulation of $\varepsilon$ with the electric field. Increasing of the external field perpendicular to the layer surface above a critical value can drive the systems to an unstable state where the layers are weakly coupled and can be easily separated. The observed dependence of $\varepsilon$ on the external field is due to charge polarization driven by the bias, which show several similar characteristics despite of the layer considered.Comment: Invited book chapter on Exotic Properties of Carbon Nanomatter: Advances in Physics and Chemistry, Springer Series on Carbon Materials. Editors: Mihai V. Putz and Ottorino Ori (11 pages, 4 figures, 30 references