Temple University

About: Temple University is a education organization based out in Philadelphia, Pennsylvania, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 32154 authors who have published 64375 publications receiving 2219828 citations.

Treating Trauma and Traumatic Grief in Children and Adolescents

Abstract: Treating trauma and traumatic grief in children and adolescents by Cohen, Mannarino, and Deblinger describes what some consider the best available treatment for children who are suffering from the sequelae to trauma. The information offered in this book extends that which was presented in an earlier book and treatment manuals on trauma-focused cognitive-behavioral therapy for traumatized children, childhood traumatic grief and children who have experienced sexual abuse written by the authors. Treating trauma and traumatic grief in children and adolescents extends upon earlier publications by including published research on traumafocused cognitive-behavioral therapy and more recent work that the authors have conducted with community-based practitioners. Importantly, the more recent collaborations with community practitioners have informed how trauma-focused cognitive-behavioral therapy can be implemented with children from diverse cultural backgrounds and children with complex family situations. In terms of the empirical support, trauma-focused cognitive-behavioral therapy has been shown to significantly reduce posttraumatic stress symptoms, depression, and behavior problems in children (Cohen, Deblinger, Mannarino, & Steer, 2004), and these treatment gains are maintained for at least two years (Deblinger, Steer, & Lippman, 1999). The treatment is also geared toward a fairly large age range. Treating trauma and traumatic grief in children and adolescents is divided into three sections. The first section

Connective tissue growth factor coordinates chondrogenesis and angiogenesis during skeletal development

Abstract: Coordinated production and remodeling of the extracellular matrix is essential during development. It is of particular importance for skeletogenesis, as the ability of cartilage and bone to provide structural support is determined by the composition and organization of the extracellular matrix. Connective tissue growth factor (CTGF, CCN2) is a secreted protein containing several domains that mediate interactions with growth factors, integrins and extracellular matrix components. A role for CTGF in extracellular matrix production is suggested by its ability to mediate collagen deposition during wound healing. CTGF also induces neovascularization in vitro, suggesting a role in angiogenesis in vivo. To test whether CTGF is required for extracellular matrix remodeling and/or angiogenesis during development, we examined the pattern of Ctgf expression and generated Ctgf -deficient mice. Ctgf is expressed in a variety of tissues in midgestation embryos, with highest levels in vascular tissues and maturing chondrocytes. We confirmed that CTGF is a crucial regulator of cartilage extracellular matrix remodeling by generating Ctgf -/- mice. Ctgf deficiency leads to skeletal dysmorphisms as a result of impaired chondrocyte proliferation and extracellular matrix composition within the hypertrophic zone. Decreased expression of specific extracellular matrix components and matrix metalloproteinases suggests that matrix remodeling within the hypertrophic zones in Ctgf mutants is defective. The mutant phenotype also revealed a role for Ctgf in growth plate angiogenesis. Hypertrophic zones of Ctgf mutant growth plates are expanded, and endochondral ossification is impaired. These defects are linked to decreased expression of vascular endothelial growth factor (VEGF) in the hypertrophic zones of Ctgf mutants. These results demonstrate that CTGF is important for cell proliferation and matrix remodeling during chondrogenesis, and is a key regulator coupling extracellular matrix remodeling to angiogenesis at the growth plate.

Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis

Abstract: A DEA-based stochastic frontier estimation framework is presented to evaluate contextual variables affecting productivity that allows for both one-sided inefficiency deviations as well as two-sided random noise. Conditions are identified under which a two-stage procedure consisting of DEA followed by ordinary least squares (OLS) regression analysis yields consistent estimators of the impact of contextual variables. Conditions are also identified under which DEA in the first stage followed by maximum likelihood estimation (MLE) in the second stage yields consistent estimators of the impact of contextual variables. This requires the contextual variables to be independent of the input variables, but the contextual variables may be correlated with each other. Monte Carlo simulations are carried out to compare the performance of our two-stage approach with one-stage and two-stage parametric approaches. Simulation results indicate that DEA-based procedures with OLS, maximum likelihood, or even Tobit estimation in the second stage perform as well as the best of the parametric methods in the estimation of the impact of contextual variables on productivity. Simulation results also indicate that DEA-based procedures perform better than parametric methods in the estimation of individual decision-making unit (DMU) productivity. Overall, the results establish DEA as a nonparametric stochastic frontier estimation (SFE) methodology.

Accurate first-principles structures and energies of diversely bonded systems from an efficient density functional

Abstract: One atom or molecule binds to another through various types of bond, the strengths of which range from several meV to several eV. Although some computational methods can provide accurate descriptions of all bond types, those methods are not efficient enough for many studies (for example, large systems, ab initio molecular dynamics and high-throughput searches for functional materials). Here, we show that the recently developed non-empirical strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation (meta-GGA) within the density functional theory framework predicts accurate geometries and energies of diversely bonded molecules and materials (including covalent, metallic, ionic, hydrogen and van der Waals bonds). This represents a significant improvement at comparable efficiency over its predecessors, the GGAs that currently dominate materials computation. Often, SCAN matches or improves on the accuracy of a computationally expensive hybrid functional, at almost-GGA cost. SCAN is therefore expected to have a broad impact on chemistry and materials science.