Acute Pancreatitis in Type 2 Diabetes Treated With Exenatide or Sitagliptin: A retrospective observational pharmacy claims analysis

OBJECTIVE Cases of acute pancreatitis have been reported in association with exenatide, sitagliptin, and type 2 diabetes without use of these medications. It remains unknown whether exenatide or sitagliptin increase the risk of acute pancreatitis. RESEARCH DESIGN AND METHODS A retrospective cohort study of a large medical and pharmacy claims database was performed. Data for 786,656 patients were analyzed. Cox proportional hazard models were built to compare the risk of acute pancreatitis between diabetic and nondiabetic subjects and between exenatide, sitagliptin, and control diabetes medication use. RESULTS Incidence of acute pancreatitis in the nondiabetic control group, diabetic control group, exenatide group, and sitagliptin group was 1.9, 5.6, 5.7, and 5.6 cases per 1,000 patient years, respectively. The risk of acute pancreatitis was significantly higher in the combined diabetic groups than in the nondiabetic control group (adjusted hazard ratio 2.1 [95% CI 1.7–2.5]). Risk of acute pancreatitis was similar in the exenatide versus diabetic control group (0.9 [0.6–1.5]) and sitagliptin versus diabetic control group (1.0 [0.7–1.3]). CONCLUSIONS Our study demonstrated increased incidence of acute pancreatitis in diabetic versus nondiabetic patients but did not find an association between the use of exenatide or sitagliptin and acute pancreatitis. The limitations of this observational claims-based analysis cannot exclude the possibility of an increased risk. </jats:sec

Toward Environmentally Sustainable Digital Preservation

Digital preservation relies on technological infrastructure (information and communication technology, ICT) that has considerable negative environmental impacts, which in turn threaten the very organizations tasked with preserving digital content. While altering technology use can reduce the impact of digital preservation practices, this alone is not a strategy for sustainable practice. Moving toward environmentally sustainable digital preservation requires critically examining the motivations and assumptions that shape current practice. Building on Goldman's challenge to current practices for digital authenticity and using Ehrenfeld's sustainability framework, we propose explicitly integrating environmental sustainability into digital preservation practice by shifting cultural heritage professionals' paradigm of appraisal, permanence, and availability of digital content. The article is organized in four parts. First, we review the literature for differing uses of the term “sustainability” in the cultural heritage field: financial, staffing, and environmental. Second, we examine the negative environmental effects of ICT throughout the full life cycle of its components to fill a gap in the cultural heritage literature, which primarily focuses on the electricity use of ICT. Next, we offer suggestions for reducing digital preservation's negative environmental impacts through altered technology use as a stopgap measure. Finally, we call for a paradigm shift in digital preservation practice in the areas of appraisal, permanence, and availability. For each area, we propose a model for sustainable practice, providing a framework for sustainable choices moving forward

Investigating the relationship between mitochondrial genetic variation and cardiovascular-related traits to develop a framework for mitochondrial phenome-wide association studies

BACKGROUND: Mitochondria play a critical role in the cell and have DNA independent of the nuclear genome. There is much evidence that mitochondrial DNA (mtDNA) variation plays a role in human health and disease, however, this area of investigation has lagged behind research into the role of nuclear genetic variation on complex traits and phenotypic outcomes. Phenome-wide association studies (PheWAS) investigate the association between a wide range of traits and genetic variation. To date, this approach has not been used to investigate the relationship between mtDNA variants and phenotypic variation. Herein, we describe the development of a PheWAS framework for mtDNA variants (mt-PheWAS). Using the Metabochip custom genotyping array, nuclear and mitochondrial DNA variants were genotyped in 11,519 African Americans from the Vanderbilt University biorepository, BioVU. We employed both polygenic modeling and association testing with mitochondrial single nucleotide polymorphisms (mtSNPs) to explore the relationship between mtDNA variants and a group of eight cardiovascular-related traits obtained from de-identified electronic medical records within BioVU. RESULTS: Using polygenic modeling we found evidence for an effect of mtDNA variation on total cholesterol and type 2 diabetes (T2D). After performing comprehensive mitochondrial single SNP associations, we identified an increased number of single mtSNP associations with total cholesterol and T2D compared to the other phenotypes examined, which did not have more significantly associated SNPs than would be expected by chance. Among the mtSNPs significantly associated with T2D we identified variant mt16189, an association previously reported only in Asian and European-descent populations. CONCLUSIONS: Our replication of previous findings and identification of novel associations from this initial study suggest that our mt-PheWAS approach is robust for investigating the relationship between mitochondrial genetic variation and a range of phenotypes, providing a framework for future mt-PheWAS

Simulation of surface ozone pollution in the Central Gulf Coast region during summer synoptic condition using WRF/Chem air quality model

AbstractWRF/Chem, a fully coupled meteorology–chemistry model, was used for the simulation of surface ozone pollution over the Central Gulf Coast region in Southeast United States of America (USA). Two ozone episodes during June 8–11, 2006 and July 18–22, 2006 characterized with hourly mixing ratios of 60–100ppbv, were selected for the study. Suite of sensitivity experiments were conducted with three different planetary boundary layer (PBL) schemes and three land surface models (LSM). The results indicate that Yonsei–University (YSU) PBL scheme in combination with NOAH and SOIL LSMs produce better simulations of both the meteorological and chemical species than others. YSU PBL scheme in combination with NOAH LSM had slightly better simulation than with SOIL scheme. Spatial comparison with observations showed that YSUNOAH experiment well simulated the diurnal mean ozone mixing ratio, timing of diurnal cycle as well as range in ozone mixing ratio at most monitoring stations with an overall correlation of 0.726, bias of –1.55ppbv, mean absolute error of 8.11ppbv and root mean square error of 14.5ppbv; and with an underestimation of 7ppbv in the daytime peak ozone and about 8% in the daily average ozone. Model produced 1–hr, and 8–hr average ozone values were well correlated with corresponding observed means. The minor underestimation of daytime ozone is attributed to the slight underestimation of air temperature which tend to slow–down the ozone production and overestimation of wind speeds which transport the produced ozone at a faster rate. Simulated mean horizontal and vertical flow patterns suggest the role of the horizontal transport and the PBL diffusion in the development of high ozone during the episode. Overall, the model is found to perform reasonably well to simulate the ozone and other precursor pollutants with good correlations and low error metrics. Thus the study demonstrates the potential of WRF/Chem model for air quality prediction in coastal environments

Challenges in quantifying changes in the global water cycle

Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes

Deep Brain Stimulation Targeting the Fornix for Mild Alzheimer Dementia: Design of the ADvance Randomized Controlled Trial

Background: There are currently few available treatments and no cure for Alzheimer disease (AD), a growing public health burden. Animal models and an open-label human trial have indicated that deep brain stimulation (DBS) of memory circuits may improve symptoms and possibly slow disease progression. The ADvance trial was designed to examine DBS of the fornix as a treatment for mild AD. Methods: ADvance is a randomized, double-blind, placebo-controlled, delayed-start, multicenter clinical trial conducted at six sites in the US and one site in Canada. Eighty-five subjects initially consented to be screened for the trial. Of these, 42 subjects who met inclusion and exclusion criteria were implanted with DBS leads anterior to the columns of the fornix bilaterally. They were randomized 1:1 to DBS off or DBS on groups for the initial 12 months of follow-up. After 1 year, all subjects will have their devices turned on for the remainder of the study. Postimplantation, subjects will return for 13 follow-up visits over 48 months for cognitive and psychiatric assessments, brain imaging (up to 12 months), and safety monitoring. The primary outcome measures include Alzheimer\u27s Disease Assessment Scale -- cognitive component (ADAS-cog-13), Clinical Dementia Rating sum of boxes (CDR-SB), and cerebral glucose metabolism measured with positron emission tomography. This report details the study methods, baseline subject characteristics of screened and implanted participants, and screen-to-baseline test€“retest reliability of the cognitive outcomes. Results: Implanted subjects had a mean age of 68.2 years, were mostly male (55%), and had baseline mean ADAS-cog-13 and CDR-SB scores of 28.9 (SD, 5.2) and 3.9 (SD, 1.6), respectively. There were no significant differences between screened and implanted or nonimplanted subjects on most demographic or clinical assessments. Implanted subjects had significantly lower (better) ADAS-cog-11 (17.5 vs 21.1) scores, but did not differ on CDR-SB. Scores on the major outcome measures for the trial were consistent at screening and baseline. Conclusion: ADvance was successful in enrolling a substantial group of patients for this novel application of DBS, and the study design is strengthened by rigorous subject selection from seven sites, a double-blind placebo-controlled design, and extensive open-label follow-up