Growth of the South Pyrenean orogenic wedge

A six-step reconstruction of the South Pyrenean foreland fold-and-thrust belt in Spain delineates the topographic slope, basal décollement angle, internal deformation, and thrust-front advance from the Early Eocene until the end of contractional deformation in the Late Oligocene. Style of thrust-front advance, dip of the basal décollement, slope of the upper surface, and internal deformation are decoupled and not simply related. Internal deformation increased, decreased, and maintained surface slope angle at different stages. From the onset to the cessation of deformation, the basal décollement angle decreased overall suggesting translation of the thrust belt onto stronger crust with time. Taper angle of the Pyrenean thrust wedge was fundamentally controlled by the flexural rigidity of the lower plate, the relative rate of creation of structural relief in the rear versus the front of the wedge, the extent of deposition of eroded material within the deforming wedge, and the taper of the pretectonic stratigraphic wedge

Quality of Diabetes Care in U.S. Academic Medical Centers: Low rates of medical regimen change

To assess both standard and novel diabetes quality measures in a national sample of U.S. academic medical centers

Pericardial Fat is Associated With Atrial Conduction: The Framingham Heart Study

Background: Obesity is associated with altered atrial electrophysiology and a prominent risk factor for atrial fibrillation. Body mass index, the most widely used adiposity measure, has been related to atrial electrical remodeling. We tested the hypothesis that pericardial fat is independently associated with electrocardiographic measures of atrial conduction. Methods and Results: We performed a cross‐sectional analysis of 1946 Framingham Heart Study participants (45% women) to determine the relation between pericardial fat and atrial conduction as measured by P wave indices (PWI): PR interval, P wave duration (P‐duration), P wave amplitude (P‐amplitude), P wave area (P‐area), and P wave terminal force (P‐terminal). We performed sex‐stratified linear regression analyses adjusted for relevant clinical variables and ectopic fat depots. Each 1‐SD increase in pericardial fat was significantly associated with PR interval (β=1.7 ms, P=0.049), P‐duration (β=2.3 ms, P<0.001), and P‐terminal (β=297 μV·ms, P<0.001) among women; and P‐duration (β=1.2 ms, P=0.002), P‐amplitude (β=−2.5 μV, P<0. 001), and P‐terminal (β=160 μV·ms, P=0.002) among men. Among both sexes, pericardial fat was significantly associated with P‐duration in analyses additionally adjusting for visceral fat or intrathoracic fat; a similar but non‐significant trend existed with P‐terminal. Among women, pericardial fat was significantly associated with P wave area after adjustment for visceral and intrathoracic fat. Conclusions: Pericardial fat is associated with atrial conduction as quantified by PWI, even with adjustment for extracardiac fat depots. Further studies are warranted to identify the mechanisms through which pericardial fat may modify atrial electrophysiology and promote subsequent risk for arrhythmogenesis

Genome-Wide Association with Select Biomarker Traits in the Framingham Heart Study

BACKGROUND: Systemic biomarkers provide insights into disease pathogenesis, diagnosis, and risk stratification. Many systemic biomarker concentrations are heritable phenotypes. Genome-wide association studies (GWAS) provide mechanisms to investigate the genetic contributions to biomarker variability unconstrained by current knowledge of physiological relations. METHODS: We examined the association of Affymetrix 100K GeneChip single nucleotide polymorphisms (SNPs) to 22 systemic biomarker concentrations in 4 biological domains: inflammation/oxidative stress; natriuretic peptides; liver function; and vitamins. Related members of the Framingham Offspring cohort (n = 1012; mean age 59 ± 10 years, 51% women) had both phenotype and genotype data (minimum-maximum per phenotype n = 507–1008). We used Generalized Estimating Equations (GEE), Family Based Association Tests (FBAT) and variance components linkage to relate SNPs to multivariable-adjusted biomarker residuals. Autosomal SNPs (n = 70,987) meeting the following criteria were studied: minor allele frequency ≥ 10%, call rate ≥ 80% and Hardy-Weinberg equilibrium p ≥ 0.001. RESULTS: With GEE, 58 SNPs had p < 10-6: the top SNPs were rs2494250 (p = 1.00*10-14) and rs4128725 (p = 3.68*10-12) for monocyte chemoattractant protein-1 (MCP1), and rs2794520 (p = 2.83*10-8) and rs2808629 (p = 3.19*10-8) for C-reactive protein (CRP) averaged from 3 examinations (over about 20 years). With FBAT, 11 SNPs had p < 10-6: the top SNPs were the same for MCP1 (rs4128725, p = 3.28*10-8, and rs2494250, p = 3.55*10-8), and also included B-type natriuretic peptide (rs437021, p = 1.01*10-6) and Vitamin K percent undercarboxylated osteocalcin (rs2052028, p = 1.07*10-6). The peak LOD (logarithm of the odds) scores were for MCP1 (4.38, chromosome 1) and CRP (3.28, chromosome 1; previously described) concentrations; of note the 1.5 support interval included the MCP1 and CRP SNPs reported above (GEE model). Previous candidate SNP associations with circulating CRP concentrations were replicated at p < 0.05; the SNPs rs2794520 and rs2808629 are in linkage disequilibrium with previously reported SNPs. GEE, FBAT and linkage results are posted at . CONCLUSION: The Framingham GWAS represents a resource to describe potentially novel genetic influences on systemic biomarker variability. The newly described associations will need to be replicated in other studies.National Heart, Lung, and Blood Institute's Framingham Heart Study (N01-HC25195); National Institutes of Health National Center for Research Resources Shared Instrumentation grant (1S10RR163736-01A1); National Institutes of Health (HL064753, HL076784, AG028321, HL71039, 2 K24HL04334, 1K23 HL083102); Doris Duke Charitable Foundation; American Diabetes Association Career Developement Award; National Center for Research Resources (GCRC M01-RR01066); US Department of Agriculture Agricultural Research Service (58-1950-001, 58-1950-401); National Institute of Aging (AG14759

Flicker Light–Induced Retinal Vasodilation in Diabetes and Diabetic Retinopathy

10.2337/dc09-0075Diabetes Care32112075-2080DICA

Diabetes Risk Perception and Intention to Adopt Healthy Lifest yles Among Primary Care Patients

OBJECTIVE—To examine perceived risk of developing diabetes in primary care patients. RESEARCH DESIGN AND METHODS—We recruited 150 nondiabetic primary care patients. We made standard clinical measurements, collected fasting blood samples, and used the validated Risk Perception Survey for Developing Diabetes questionnaire. RESULTS—Patients with high perceived risk were more likely than those with low perceived risk to have a family history of diabetes (68 vs. 18%; P < 0.0001) and to have metabolic syndrome (53 vs. 35%; P = 0.04). However, patients with high perceived risk were not more likely to have intentions to adopt healthier lifestyle in the coming year (high 26.0% vs. low 29.2%; P = 0.69). CONCLUSIONS—Primary care patients with higher perceived risk of diabetes were at higher actual risk but did not express greater intention to adopt healthier lifestyles. Aspects of health behavior theory other than perceived risk need to be explored to help target efforts in the primary prevention of diabetes

Spatiotemporal dynamics of recent mountain pine beetle and western spruce budworm outbreaks across the Pacific Northwest Region, USA

Across the western US, the two most prevalent native forest insect pests are mountain pine beetle (MPB; Dendroctonus ponderosae; a bark beetle) and western spruce budworm (WSB; Choristoneura freemani; a defoliator). MPB outbreaks have received more forest management attention than WSB outbreaks, but studies to date have not compared their cumulative mortality impacts in an integrated, regional framework. The objectives of this study are to: (1) map tree mortality associated with MPB and WSB outbreaks by integrating forest health aerial detection surveys (ADS; 1970–2012), Landsat time series (1984–2012), and multi-date forest inventory data; (2) compare the timing, extent, and cumulative impacts of recent MPB and WSB outbreaks across forested ecoregions of the US Pacific Northwest Region (PNW; Oregon and Washington). Our Landsat-based insect atlas facilitates comparisons across space, time, and insect agents that have not been possible to date, complementing existing ADS maps in three important ways. The new maps (1) capture variation of insect impacts within ADS polygons at a finer spatial resolution (30 m), substantially reducing estimated insect extent; (2) provide consistent estimates of change for multiple agents, particularly long-duration changes; (3) quantify change in terms of field-measured tree mortality (dead basal area). Despite high variation across the study region, spatiotemporal patterns are evident in both the aerial survey- and Landsat-based maps of insect activity. MPB outbreaks occurred in two phases – first during the 1970s and 1980s in eastern and central Oregon and then more synchronously during the 2000s throughout dry interior conifer forests of the PNW. Reflecting differences in habitat susceptibility and epidemiology, WSB outbreaks exhibited early activity in northern Washington and an apparent spread from the eastern to central PNW during the 1980s, returning to northern Washington during the 1990s and 2000s. At ecoregional and regional scales, WSB outbreaks have exceeded MPB outbreaks in extent as well as total tree mortality, suggesting that ongoing studies should account for both bark beetles and defoliators. Given projected increases of insect and fire activity in western forests, the accurate assessment and monitoring of these disturbances will be crucial for sustainable ecosystem management.Keywords: Bark beetle, Defoliator, Change detection, Landsat time series, Forest disturbance, Tree mortalit

Performance of A1C for the Classification and Prediction of Diabetes

OBJECTIVE Although A1C is now recommended to diagnose diabetes, its test performance for diagnosis and prognosis is uncertain. Our objective was to assess the test performance of A1C against single and repeat glucose measurements for diagnosis of prevalent diabetes and for prediction of incident diabetes. RESEARCH DESIGN AND METHODS We conducted population-based analyses of 12,485 participants in the Atherosclerosis Risk in Communities (ARIC) study and a subpopulation of 691 participants in the Third National Health and Nutrition Examination Survey (NHANES III) with repeat test results. RESULTS Against a single fasting glucose ≥126 mg/dl, the sensitivity and specificity of A1C ≥6.5% for detection of prevalent diabetes were 47 and 98%, respectively (area under the curve 0.892). Against repeated fasting glucose (3 years apart) ≥126 mg/dl, sensitivity improved to 67% and specificity remained high (97%) (AUC 0.936). Similar results were obtained in NHANES III against repeated fasting glucose 2 weeks apart. The accuracy of A1C was consistent across age, BMI, and race groups. For individuals with fasting glucose ≥126 mg/dl and A1C ≥6.5% at baseline, the 10-year risk of diagnosed diabetes was 88% compared with 55% among those individuals with fasting glucose ≥126 mg/dl and A1C 5.7–<6.5%. CONCLUSIONS A1C performs well as a diagnostic tool when diabetes definitions that most closely resemble those used in clinical practice are used as the “gold standard.” The high risk of diabetes among individuals with both elevated fasting glucose and A1C suggests a dual role for fasting glucose and A1C for prediction of diabetes. Although A1C is now recommended for the diagnosis of diabetes (1,2), its precise test performance is uncertain. The lack of a single, clear “gold standard” poses a challenge for determining the performance of A1C. Previous diagnostic studies of A1C have relied exclusively on a single elevated fasting or 2-h glucose values as gold standards (3–5). However, because glucose determinations are inherently more variable than A1C (6), these convenient gold standards are likely to reduce the apparent accuracy of A1C as a diagnostic test. A stronger gold standard would rely on repeated glucose determinations on different days (2), i.e., the recommended approach to diagnosis of diabetes in clinical practice. Alternatively, A1C and fasting glucose can be compared head-to-head against the subsequent development of clinically diagnosed diabetes as the gold standard. We hypothesized that 1) A1C would perform well as a diagnostic and prognostic test for diabetes across its full range and at the American Diabetes Association–recommended threshold of 6.5% and 2) that its performance would be best when judged against stronger, most clinically relevant gold standards