The CD14 functional gene polymorphism -260 C>T is not involved in either the susceptibility to Chlamydia trachomatis infection or the development of tubal pathology

BACKGROUND: The functional polymorphism -260 C>T in the LPS sensing TLR4 co-receptor CD14 gene enhances the transcriptional activity and results in a higher CD14 receptor density. Individuals carrying the T/T genotype also have significantly higher serum levels of soluble CD14. The T allele of this polymorphism has recently been linked to Chlamydia pneumoniae infection. We investigated the role of the CD14 -260 C>T polymorphism in the susceptibility to and severity (defined as subfertility and/or tubal pathology) of C. trachomatis infection in Dutch Caucasian women. METHODS: The different CD14 -260 C>T genotypes were assessed by PCR-based RFLP analysis in three cohorts: 1) A cohort (n = 576) of women attending a STD clinic, 2) a cohort (n = 253) of women with subfertility, and 3) an ethnically matched control cohort (n = 170). The following variables were used in the analysis: In cohort 1 the CT-DNA status, CT IgG serology status, self-reported symptoms and in cohort 2, the CT IgG serology status and the tubal status at laparoscopy. RESULTS: In the control cohort the CC, CT and TT genotype distribution was: 28.2%, 48.2%, and 23.5% respectively. No differences were found in the overall prevalence of CD14 -260 genotypes (28.1%, 50.7%, and 21.2%) in cohort 1 when compared to the control cohort. Also no differences were observed in women with or without CT-DNA, with or without serological CT responses, with or without symptoms, or in combinations of these three variables. In subfertile women with tubal pathology (cohort 2, n = 50) the genotype distribution was 28.0%, 48.0%, and 24.0% and in subfertile women without tubal pathology (n = 203), 27.6%, 49.3% and 23.2%. The genotype distribution was unchanged when CT IgG status was introduced in the analyses. CONCLUSION: The CD14 -260 C>T genotype distributions were identical in all three cohorts, showing that this polymorphism is not involved in the susceptibility to or severity of sequelae of C. trachomatis infection

The Biochemistry, Ultrastructure, and Subunit Assembly Mechanism of AMPA Receptors

The AMPA-type ionotropic glutamate receptors (AMPA-Rs) are tetrameric ligand-gated ion channels that play crucial roles in synaptic transmission and plasticity. Our knowledge about the ultrastructure and subunit assembly mechanisms of intact AMPA-Rs was very limited. However, the new studies using single particle EM and X-ray crystallography are revealing important insights. For example, the tetrameric crystal structure of the GluA2cryst construct provided the atomic view of the intact receptor. In addition, the single particle EM structures of the subunit assembly intermediates revealed the conformational requirement for the dimer-to-tetramer transition during the maturation of AMPA-Rs. These new data in the field provide new models and interpretations. In the brain, the native AMPA-R complexes contain auxiliary subunits that influence subunit assembly, gating, and trafficking of the AMPA-Rs. Understanding the mechanisms of the auxiliary subunits will become increasingly important to precisely describe the function of AMPA-Rs in the brain. The AMPA-R proteomics studies continuously reveal a previously unexpected degree of molecular heterogeneity of the complex. Because the AMPA-Rs are important drug targets for treating various neurological and psychiatric diseases, it is likely that these new native complexes will require detailed mechanistic analysis in the future. The current ultrastructural data on the receptors and the receptor-expressing stable cell lines that were developed during the course of these studies are useful resources for high throughput drug screening and further drug designing. Moreover, we are getting closer to understanding the precise mechanisms of AMPA-R-mediated synaptic plasticity

Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges

Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype–phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome-sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challenges serve as a vehicle for sharing clinical and research exome data in a secure manner with scientists who have a broad range of expertise, contributing to a collaborative effort to advance our understanding of genotype–phenotype relationships

Managing Carbon

Storing carbon (C) and offsetting carbon dioxide (CO2) emissions with the use of wood for energy, both of which slow emissions of CO2 into the atmosphere, present significant challenges for forest management (IPCC 2001). In the United States, there has been a net increase in C in forests and in harvested wood products stocks (Tables 7.1 and 7.2), a result of historical and recent ecological conditions, management practices, and use of forest products (Birdsey et al. 2006). However, recent projections for the forest sector suggest that annual C storage could begin to decline, and U.S. forests could become a net C emitter of tens to hundreds of Tg C year ¹ within a few decades (USDA FS 2012a). It is therefore urgent to identify effective C management strategies, given the complexity of factors that drive the forest C cycle and the multiple objectives for which forests are managed. An ideal C management activity contributes benefits beyond increasing C storage by achieving other management objectives and providing ecosystem services in a sustainable manner. Strategies for effectively managing forest C stocks and offsetting C emissions requires a thorough understanding of biophysical and social influences on the forest C cycle (Birdsey et al. 1993). Successful policies and incentives may be chosen to support strategies if sufficient knowledge of social processes (e.g., landowner or wood-user response to incentives and markets) is available. For example, if C stocks are expected to decrease owing to decreasing forest land area caused by exurban development, policies or incentives to avoid deforestation in those areas may be effective. If C stocks are expected to decrease owing to the effects of a warmer climate, reducing stand densities may retain C over the long term by increasing resilience to drought and other stressors and by reducing crown fire hazard (Jackson et al. 2005; Reinhardt et al. 2008). Protecting old forests and other forests that have high C stocks may be more effective than seeking C offsets associated with wood use, especially if those forests would recover C more slowly in an altered climate. If climate change increases productivity in a given area over a long period of time, increasing forest C stocks through intensive management and forest products, including biomass energy, may be especially effective. It is equally important to know which strategies might make some management practices unacceptable (e.g., reducing biodiversity). However, no standard evaluation framework exists to aid decision making on alternative management strategies for maximizing C storage while minimizing risks and tradeoffs. Here we discuss (1) where forest C is stored in the United States, (2) how to measure forest C through space and time, (3) effectiveness of various management strategies in reducing atmospheric greenhouse gases (GHG), and (4) effectiveness of incentives, regulations, and institutional arrangements for implementing C management. Understanding of biophysical and social influences on the forest C cycle (Birdsey et al. 1993). Successful policies and incentives may be chosen to support strategies if sufficient knowledge of social processes (e.g., landowner or wood-user response to incentives and markets) is available. For example, if C stocks are expected to decrease owing to decreasing forest land area caused by exurban development, policies or incentives to avoid deforestation in those areas may be effective. If C stocks are expected to decrease owing to the effects of a warmer climate, reducing stand densities may retain C over the long term by increasing resilience to drought and other stressors and by reducing crown fire hazard (Jackson et al. 2005; Reinhardt et al. 2008). Protecting old forests and other forests that have high C stocks may be more effective than seeking C offsets associated with wood use, especially if those forests would recover C more slowly in an altered climate. If climate change increases productivity in a given area over a long period of time, increasing forest C stocks through intensive management and forest products, including biomass energy, may be especially effective. It is equally important to know which strategies might make some management practices unacceptable (e.g., reducing biodiversity). However, no standard evaluation framework exists to aid decision making on alternative management strategies for maximizing C storage while minimizing risks and tradeoffs. Here we discuss (1) where forest C is stored in the United States, (2) how to measure forest C through space and time, (3) effectiveness of various management strategies in reducing atmospheric greenhouse gases (GHG), and (4) effectiveness of incentives, regulations, and institutional arrangements for implementing C management