Roadmap for implementing the Chronic Care Model for weight management: Healthcare Institution's Response to Obesity (HIRO)

Background. Excess weight and obesity are at epidemic proportions in the United States and place individuals at increased risk for a variety of chronic conditions. Rates of diabetes, high blood pressure, coronary artery disease, stroke, cancer, and arthritis are all influenced by the presence of obesity. Small reductions in excess weight can produce significant positive clinical outcomes. Healthcare organizations have a vital role to play in the identification and management of obesity. Currently, healthcare providers do not adequately diagnose and manage excess weight in patients. Lack of skill, time, and knowledge are commonly cited as reasons for non-adherence to recommended standards of care. The Chronic Care Model offers an approach to healthcare organizations for chronic disease management. The model consists of six elements that work together to empower both providers and patients to have more productive interactions: the community, the health system itself, self-management support, delivery system design, decision support, and clinical information systems. The model and its elements may offer a framework through which healthcare organizations can adapt to support, educate, and empower providers and patients in the management of excess weight and obesity. Successful management of excess weight will reduce morbidity and mortality of many chronic conditions. Purpose. The purpose of this review is to synthesize existing research on the effectiveness of the Chronic Care Model and its elements as they relate to weight management and behaviors associated with maintaining a healthy weight. Methods: A narrative review of the literature between November 1998 and November 2008 was conducted. The review focused on clinical trials, systematic reviews, and reports related to the chronic care model or its elements and weight management, physical activity, nutrition, or diabetes. Fifty-nine articles are included in the review. Results. This review highlights the use of the Chronic Care Model and its elements that can result in improved quality of care and clinical outcomes related to weight management, physical activity, nutrition, and diabetes. Conclusions. Healthcare organizations can use the Chronic Care Model framework to implement changes within their systems to successfully address overweight and obesity in their patient populations. Specific recommendations for operationalizing the Chronic Care Model elements for weight management are presented.^

RNA binding characteristics and overall topology of the vaccinia virus polyadenylation complex

mRNA 3′ polyadenylation is central to mRNA biogenesis in prokaryotes and eukaryotes, and is implicated in numerous aspects of mRNA metabolism, including efficiency of mRNA export from the nucleus, message stability, and initiation of translation. However, due to the great complexity of the eukaryotic polyadenylation apparatus, the mechanisms of RNA 3 ′ end processing have remained elusive. Although the RNA processing reactions leading to polyadenylated messenger RNA have been studied in many systems, and much progress has been made, a complete understanding of the biochemistry of the poly(A) polymerase enzyme is still lacking. My research uses Vaccinia virus as a model system to gain a better understanding of this complicated polyadenylation process, which consist of RNA binding, catalysis and polymerase translocation. ^ Vaccinia virus replicates in the cytoplasm of its host cell, so it must employ its own poly(A) polymerase (PAP), a heterodimer of two virus encoded proteins, VP55 and VP39. VP55 is the catalytic subunit, adding 30 adenylates to a non-polyadenylated RNA in a rapid processive manner before abruptly changing to a slow, non-processive mode of adenylate addition and dissociating from the RNA. VP39 is the stimulatory subunit. It has no polyadenylation catalytic activity by itself, but when associated with VP55 it facilitates the semi-processive synthesis of tails several hundred adenylates in length. ^ Oligonucleotide selection and competition studies have shown that the heterodimer binds a minimal motif of (rU)2 (N)25 U, the “heterodimer binding motif”, within an oligonucleotide, and its primer selection for polyadenylation is base-type specific. ^ Crosslinking studies using photosensitive uridylate analogs show that within a VP55-VP39-primer ternary complex, VP55 comes into contact with all three required uridylates, while VP39 only contacts the downstream uridylate. Further studies, using a backbone-anchored photosensitive crosslinker show that both PAP subunits are in close proximity to the downstream −10 to −21 region of 50mer model primers containing the heterodimer binding motif. This equal crosslinking to both subunits suggests that the dimerization of VP55 and VP39 creates either a cleft or a channel between the two subunits through which this region of RNA passes. ^ Peptide mapping studies of VP39 covalently crosslinked to the oligonucleotide have identified residue R107 as the amino acid in close proximity to the −10 uridylate. This helps us project a conceptual model onto the known physical surface of this subunit. In the absence of any tertiary structural data for VP55, we have used a series of oligonucleotide selection assays, as well as crosslinking, nucleotide transfer assays, and gel shift assays to gain insight into the requirements for binding, polyadenylation and translocation. Collectively, these data allow us to put together a comprehensive model of the structure and function of the polyadenylation ternary complex consisting of VP39, VP55 and RNA. ^

Hazardous air pollutants and childhood lymphohematopoietic cancer in Southeast Texas, 1995--2004

Southeast Texas, including Houston, has a large presence of industrial facilities and has been documented to have poorer air quality and significantly higher cancer rates than the remainder of Texas. Given citizens’ concerns in this 4th largest city in the U.S., Mayor Bill White recently partnered with the UT School of Public Health to determine methods to evaluate the health risks of hazardous air pollutants (HAPs). Sexton et al. (2007) published a report that strongly encouraged analytic studies linking these pollutants with health outcomes. In response, we set out to complete the following aims: 1. determine the optimal exposure assessment strategy to assess the association between childhood cancer rates and increased ambient levels of benzene and 1,3-butadiene (in an ecologic setting) and 2. evaluate whether census tracts with the highest levels of benzene or 1,3-butadiene have higher incidence of childhood lymphohematopoietic cancer compared with census tracts with the lowest levels of benzene or 1,3-butadiene, using Poisson regression. The first aim was achieved by evaluating the usefulness of four data sources: geographic information systems (GIS) to identify proximity to point sources of industrial air pollution, industrial emission data from the U.S. EPA’s Toxic Release Inventory (TRI), routine monitoring data from the U.S. EPA Air Quality System (AQS) from 1999-2000 and modeled ambient air levels from the U.S. EPA’s 1999 National Air Toxic Assessment Project (NATA) ASPEN model. Further, once these four data sources were evaluated, we narrowed them down to two: the routine monitoring data from the AQS for the years 1998-2000 and the 1999 U.S. EPA NATA ASPEN modeled data. We applied kriging (spatial interpolation) methodology to the monitoring data and compared the kriged values to the ASPEN modeled data. Our results indicated poor agreement between the two methods. Relative to the U.S. EPA ASPEN modeled estimates, relying on kriging to classify census tracts into exposure groups would have caused a great deal of misclassification. To address the second aim, we additionally obtained childhood lymphohematopoietic cancer data for 1995-2004 from the Texas Cancer Registry. The U.S. EPA ASPEN modeled data were used to estimate ambient levels of benzene and 1,3-butadiene in separate Poisson regression analyses. All data were analyzed at the census tract level. We found that census tracts with the highest benzene levels had elevated rates of all leukemia (rate ratio (RR) = 1.37; 95% confidence interval (CI), 1.05-1.78). Among census tracts with the highest 1,3-butadiene levels, we observed RRs of 1.40 (95% CI, 1.07-1.81) for all leukemia. We detected no associations between benzene or 1,3-butadiene levels and childhood lymphoma incidence. This study is the first to examine this association in Harris and surrounding counties in Texas and is among the first to correlate monitored levels of HAPs with childhood lymphohematopoietic cancer incidence, evaluating several analytic methods in an effort to determine the most appropriate approach to test this association. Despite recognized weakness of ecologic analyses, our analysis suggests an association between childhood leukemia and hazardous air pollution.^