Promises and Perils of New Global Governance: A Case of the G20 (with C. Kelly)

In the wake of the 2008 financial crisis, a new global governance structure emerged. During and subsequent to the crisis, the G20 arose as a coordinating executive among international governance institutions. It set policy agendas, prioritized initiatives and, working through the Financial Stability Board, drew other governance institutions and networks such as the International Monetary Fund, the Basel Committee on Banking Supervision, the Organization of Economic Cooperation and Development, the World Trade Organization, the International Association of Insurance Supervisors and the International Organization of Securities Commissions to set standards, monitor enforcement and compliance, and aid recovery. Its authority cross-cuts regimes and creates collaborative linkages between economic law and social issues such as food security and the environment. Its leadership role, born out of exigency, now continues to evolve as part of the new international economic law order. The G20’s coordination of institutions and networks exemplifies a new form of global governance. Network coordination offers an opportunity to confront complex problems with a needed comprehensive approach. The institutions and networks engage in an ongoing dialectical process that propels standard setters towards convergence on a number of fronts. The actors in this process employ a variety of tools to forge consensus and the G20 leverages this consensus-creating process to achieve its goals. Unpacking these tools can help us tackle intricate questions that arise from this new structure. In particular, we focus on concerns of effectiveness and legitimacy originating from the G20’s coordination of multiple networks and institutions

A novel human glucocorticoid receptor SNP results in increased transactivation potential.

Glucocorticoids are one of the most widely used therapeutics in the treatment of a variety of inflammatory disorders. However, it is known that there are variable patient responses to glucocorticoid treatment; there are responders and non-responders, or those that need higher dosages. Polymorphisms in the glucocorticoid receptor (GR) have been implicated in this variability. In this study, ninety-seven volunteers were surveyed for polymorphisms in the human GR-alpha (hGRα), the accepted biologically active reference isoform. One isoform identified in our survey, named hGR DL-2, had four single nucleotide polymorphisms (SNPs), one synonymous and three non-synonymous, and a four base pair deletion resulting in a frame shift and early termination to produce a 743 amino acid putative protein. hGR DL-2 had a decrease in transactivation potential of more than 90%. Upon further analysis of the individual SNPs and deletion, one SNP, A829G, which results in a lysine to glutamic acid amino acid change at position 277, was found to increase the transactivation potential of hGR more than eight times the full-length reference. Furthermore, the hGRα-A829G isoform had a differential hyperactive response to various exogenous steroids. Increasing our knowledge as to how various SNPs affect hGR activity may help in understanding the unpredictable patient response to steroid treatment, and is a step towards personalizing patient care

Handling linkage disequilibrium in linkage analysis using dense single-nucleotide polymorphisms

The presence of linkage disequilibrium violates the underlying assumption of linkage equilibrium in most traditional multipoint linkage approaches. Studies have shown that such violation leads to bias in qualitative trait linkage analysis when parental genotypes are unavailable. Appropriate handling of marker linkage disequilibrium can avoid such false positive evidence. Using the rheumatoid arthritis simulated data from Genetic Analysis Workshop 15, we examined and compared the following three approaches to handle linkage disequilibrium among dense markers in both qualitative and quantitative trait linkage analyses: a simple algorithm; SNPLINK, methods for marker selection; and MERLIN-LD, a method for modeling linkage disequilibrium by creating marker clusters. In analysis ignoring linkage disequilibrium between markers, we observed LOD score inflation only in the affected sib-pair linkage analysis without parental genotypes; no such inflation was present in the quantitative trait locus linkage analysis with severity as our phenotype with or without parental genotypes. Using methods to model or adjust for linkage disequilibrium, we found a substantial reduction of inflation of LOD score in affected sib-pair linkage analysis. Greater LOD score reduction was observed by decreasing the amount of tolerable linkage disequilibrium among markers selected or marker clusters using MERLIN-LD; the latter approach showed most reduction. SNPLINK performed better with selected markers based on the D' measure of linkage disequilibrium as opposed to the r2 measure and outperformed the simple algorithm. Our findings reiterate the necessity of properly handling dense markers in linkage analysis, especially when parental genotypes are unavailable

Comparing objective measures of environmental supports for pedestrian travel in adults

Background: Evidence is growing that the built environment has the potential to influence walking--both positively and negatively. However, uncertainty remains on the best approaches to representing the pedestrian environment in order to discern associations between walking and the environment. Research into the relationship between environment and walking is complex; challenges include choice of measures (objective and subjective), quality and availability of data, and methods for managing quantitative data through aggregation and weighting. In particular, little research has examined how to aggregate built environment data to best represent the neighborhood environments expected to influence residents' behavior. This study examined associations between walking and local pedestrian supports (as measured with an environmental audit), comparing the results of models using three different methods to aggregate and weight pedestrian features. Methods: Using data collected in 2005-2006 for a sample of 251 adult residents of Montgomery County, MD, we examined associations between pedestrian facilities and walking behaviors (pedestrian trips and average daily steps). Adjusted negative binomial and ordinary least-squares regression models were used to compare three different data aggregation techniques (raw averages, length weighting, distance weighting) for measures of pedestrian facilities that included presence, condition, width and connectivity of sidewalks, and presence of crossing aids and crosswalks. Results: Participants averaged 8.9 walk trips during the week; daily step counts averaged 7042. The three aggregation techniques revealed different associations between walk trips and the various pedestrian facilities. Crossing aids and good sidewalk conditions were associated with walk trips more than were other pedestrian facilities, while sidewalk facilities and features showed associations with steps not observed for crossing aids and crosswalks. Conclusion: Among three methods of aggregation examined, the method that accounted for distance from participant's home to the pedestrian facility (distance weighting) is promising; at the same time, it requires the most time and effort to calculate. This finding is consistent with the behavioral assumption that travelers may respond to environmental features closer to their residence more strongly than to more distant environmental qualities.close0

Changes in the reproductive function and developmental phenotypes in mice following intramuscular injection of an activin betaA-expressing plasmid

<p>Abstract</p> <p>Background</p> <p>The TGF-beta family protein activin has numerous reported activities with some uncertainty in the reproductive axis and development. The precise roles of activin in in vivo system were investigated using a transient gain of function model.</p> <p>Methods</p> <p>To this end, an expression plasmid, pCMV-rAct, with the activin betaA cDNA fused to the cytomegalovirus promoter, was introduced into muscle of the female adult mice by direct injection.</p> <p>Results</p> <p>Activin betaA mRNA was detected in the muscle by RT-PCR and subsequent Southern blot analysis. Activin betaA was also detected, and western blot analysis revealed a relatively high level of serum activin with correspondingly increased FSH. In the pCMV-rAct-injected female mice, estrus stage within the estrous cycle was extended. Moreover, increased numbers of corpora lutea and a thickened granulosa cell layer with a small antrum in tertiary follicles within the ovary were observed. When injected female mice were mated with males of proven fertility, a subset of embryos died in utero, and most of those that survived exhibited increased body weight.</p> <p>Conclusion</p> <p>Taken together, our data reveal that activin betaA can directly influence the estrous cycle, an integral part of the reproduction in female mice and activin betaA can also influence the embryo development as an endocrine fashion.</p

Biofiltration of reduced sulphur compounds and community analysis of sulphur-oxidizing bacteria.

http://dx.doi.org/10.1016/j.biortech.2010.12.018The present work aims to use a two-stage biotrickling filters for simultaneous treatment of hydrogen sulphide (H2S), methyl mercaptan (MM), dimethyl sulphide (DMS) and dimethyl disulphide (DMDS). The first biofilter was inoculated with Acidithiobacillus thiooxidans (BAT) and the second one with Thiobacillus thioparus (BTT). For separate feeds of reduced sulphur compounds (RSC), the elimination capacity (EC) order was DMDS > DMS > MM. The EC values were 9.8 gMM-S/m3/h (BTT; 78% removal efficiency (RE); empty bed residence time (EBRT) 58 s), 36 gDMDS-S/m3/h (BTT; 94.4% RE; EBRT 76 s) and 57.5 gH2S-S/m3/h (BAT; 92% RE; EBRT 59 s). For the simultaneous removal of RSC in BTT, an increase in the H2S concentration from 23 to 293 ppmv (EBRT of 59 s) inhibited the RE of DMS (97–84% RE), DMDS (86–76% RE) and MM (83–67% RE). In the two-stage biofiltration, the RE did not decrease on increasing the H2S concentration from 75 to 432 ppmv

Memory management in genome-wide association studies

Genome-wide association is a powerful tool for the identification of genes that underlie common diseases. Genome-wide association studies generate billions of genotypes and pose significant computational challenges for most users including limited computer memory. We applied a recently developed memory management tool to two analyses of North American Rheumatoid Arthritis Consortium studies and measured the performance in terms of central processing unit and memory usage. We conclude that our memory management approach is simple, efficient, and effective for genome-wide association studies

A genome-wide association analysis of Framingham Heart Study longitudinal data using multivariate adaptive splines

The Framingham Heart Study is a well known longitudinal cohort study. In recent years, the community-based Framingham Heart Study has embarked on genome-wide association studies. In this paper, we present a Framingham Heart Study genome-wide analysis for fasting triglycerides trait in the Genetic Analysis Workshop16 Problem 2 using multivariate adaptive splines for the analysis of longitudinal data (MASAL). With MASAL, we are able to perform analysis of genome-wide data with longitudinal phenotypes and covariates, making it possible to identify genes, gene-gene, and gene-environment (including time) interactions associated with the trait of interest. We conducted a permutation test to assess the associations between MASAL selected markers and triglycerides trait and report significant gene-gene and gene-environment interaction effects on the trait of interest