EFFICIENT PATTERNS OF CONSERVATION ACTIVITIES IN A WATERSHED: THE CASE OF THE GRANDE RONDE RIVER, OREGON

This research examines a spatially explicit allocation of habitat restoration activities in an Oregon watershed to meet water temperature targets for the benefit of endangered salmonid fish species. Integrating hydrological, biological and economic models, a series of optimization problems are investigated for different policy targets including temperature reductions and enhanced fish populations. Results indicated that the heterogeneous nature of riparian conditions and stream morphology needs to be considered if restoration activities are to be allocated efficiently in a watershed. We also found that it is less costly to implement restoration activities in tributaries if the objective is to maximize stream length where water temperatures decrease by a certain degree. Although temperature reductions are primarily achieved by shading in nearby reaches, if a desired level of temperature reductions increases, then it is necessary to apply restoration efforts in remote reaches.Resource /Energy Economics and Policy,

Inherited destiny? Genetics and gestational diabetes mellitus

Despite years of investigation, very little is known about the genetic predisposition for gestational diabetes mellitus (GDM). However, the advent of genome-wide association and identification of loci contributing to susceptibility to type 2 diabetes mellitus has opened a small window into the genetics of GDM. More importantly, the study of the genetics of GDM has not only illuminated potential new biology underlying diabetes in pregnancy, but has also provided insights into fetal outcomes. Here, I review some of the insights into GDM and fetal outcomes gained through the study of both rare and common genetic variation. I also discuss whether recent testing of type 2 diabetes mellitus susceptibility loci in GDM case-control samples changes views of whether GDM is a distinct form of diabetes. Finally, I examine how the study of susceptibility loci can be used to influence clinical care, one of the great promises of the new era of human genome analysis

OGTT-Derived Measures of Insulin Sensitivity Are Confounded by Factors Other Than Insulin Sensitivity Itself

Insulin resistance is an important risk factor for diabetes and other diseases. It has been important to estimate insulin resistance in epidemiological and genetic studies involving significant number of individuals. Complex and invasive protocols are impractical. Therefore, insulin sensitivity indices based on the oral glucose-tolerance test (OGTT) have been introduced. The aim of the present study was to assess the accuracy with which OGTT-derived indices would reflect changes in insulin sensitivity in the face of changes in other factors, such as rate of glucose absorption and/or B-cell function. A computer model was employed to predict excursions of plasma glucose and insulin after a 75-g oral glucose load. The model was then used to predict changes in these excursions, which would be observed with altered insulin resistance, with alterations in β-cell sensitivity to glucose and/or alterations in glucose absorption rates. Published indices of insulin sensitivity could then be calculated from the predicted curves, to ask whether changes in β-cell function or glucose absorptions rates might be misinterpreted (using the indices) as changes in insulin sensitivity. The model accurately represented OGTT data for a normal glucose tolerant subject, closely matching published data. Imposed 50% reductions or increases in insulin sensitivity alone in the model were reflected in only small changes in OGTT-derived insulin sensitivity values. More important, imposed alterations in β-cell sensitivity and glucose absorption without simulated changes in insulin sensitivity did change insulin sensitivity indices. These results indicate that caution is required for the interpretation of differences in OGTT-derived values of insulin sensitivity, because variation in factors other than insulin sensitivity per se appear to have the greatest effects on indices calculated from the OGTT alone

The effect of phenotype variation on detection of linkage in the COGA data

Error in phenotypic measurement can significantly compromise ability to detect linkage. We assessed the impact of introducing phenotypic measurement error on our ability to detect a quantitative trait locus in the Collaborative Study on the Genetics of Alcoholism (COGA) data. The impact of introducing three different types of errors was evaluated: 1) errors generated by sampling from a normal distribution; 2) errors generated by permuting phenotype values between subjects; and 3) errors generated by sampling from a uniform error distribution.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/101827/1/1370170711_ftp.pd

MINMOD Millennium: A Computer Program to Calculate Glucose Effectiveness and Insulin Sensitivity From the Frequently Sampled Intravenous Glucose Tolerance Test

The Bergman Minimal Model enables estimation of two key indices of glucose/insulin dynamics: glucose effectiveness and insulin sensitivity. In this paper we describe MINMOD Millennium, the latest Windows-based version of minimal model software. Extensive beta testing of MINMOD Millennium has shown that it is user-friendly, fully automatic, fast, accurate, reproducible, repeatable, and highly concordant with past versions of MINMOD. It has a simple interface, a comprehensive help system, an input file editor, a file converter, an intelligent processing kernel, and a file exporter. It provides publication-quality charts of glucose and insulin and a table of all minimal model parameters and their error estimates. In contrast to earlier versions of MINMOD and some other minimal model programs, Millennium provides identified estimates of insulin sensitivity and glucose effectiveness for almost every subject

Our Sun. IV. The Standard Model and Helioseismology: Consequences of Uncertainties in Input Physics and in Observed Solar Parameters

Helioseismology provides a powerful tool to explore the deep interior of the Sun: for example, the adiabatic sound speed can be inferred with an accuracy of a few parts in 10,000. This has become a serious challenge to theoretical models of the Sun. Therefore, we have undertaken a self-consistent, systematic study of sources of uncertainties in the standard solar model, which must be understood before the helioseismic observations can be used as constraints on theory. We find that the largest uncertainty in the sound speed in the solar interior, namely, 3 parts in 1000, arises from uncertainties in the observed photospheric abundances of the elements; uncertainties of 1 part in 1000 arise from (1) the 4% uncertainty in the OPAL opacities, (2) the 5% uncertainty in the basic pp nuclear reaction rate, (3) the 15% uncertainty in the diffusion constants for the gravitational settling of helium, and (4) the 50% uncertainties in diffusion constants for the heavier elements. (Other investigators have shown that similar uncertainties arise from uncertainties in the interior equation of state and in rotation-induced turbulent mixing.) The predicted pre-main-sequence solar lithium depletion is a factor of order 20 (an order of magnitude larger than that predicted by earlier models that neglected gravitational settling and used older opacities), and is uncertain by a factor of 2. The predicted neutrino capture rate is uncertain by 30% for the Cl-37 experiment and by 3% for the Ga-71 experiments (not including uncertainties in the capture cross sections), while the B-8 neutrino flux is uncertain by 30%.Comment: LaTeX, 38 pages (including 8 figures); ApJ, in press. Added figures/color figurea available at http://www.cita.utoronto.ca/~boothroy/sun4.htm

Identifying influential individuals in linkage analysis: Application to a quantitative trait locus detected in the COGA data

Once linkage is detected to a quantitative trait locus (QTL), the next step towards localizing the gene involved may be to identify those families, or individuals, in whom the putative mutations are segregating. In this paper, we describe a jackknife procedure for identifying individuals (and families) who contribute disproportionately to the linkage. Following initial detection of linkage to a QTL, the strategy involves sequentially removing each individual (or each family) from the analysis and recomputing the lod score associated with the linked region using data from all remaining subjects (or families). This procedure can be used to determine if particular observations have substantial impact on evidence for linkage. Identification of such observations may provide insights for further efforts to localize the QTL.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/101831/1/1370170744_ftp.pd

A Better Index of Body Adiposity

Obesity is a growing problem in the United States and throughout the world. It is a risk factor for many chronic diseases. The BMI has been used to assess body fat for almost 200 years. BMI is known to be of limited accuracy, and is different for males and females with similar %body adiposity. Here, we define an alternative parameter, the body adiposity index (BAI = ((hip circumference)/((height)1.5)–18)). The BAI can be used to reflect %body fat for adult men and women of differing ethnicities without numerical correction. We used a population study, the “BetaGene” study, to develop the new index of body adiposity. %Body fat, as measured by the dual-energy X-ray absorptiometry (DXA), was used as a “gold standard” for validation. Hip circumference (R = 0.602) and height (R = −0.524) are strongly correlated with %body fat and therefore chosen as principal anthropometric measures on which we base BAI. The BAI measure was validated in the “Triglyceride and Cardiovascular Risk in African-Americans (TARA)” study of African Americans. Correlation between DXA-derived %adiposity and the BAI was R = 0.85 for TARA with a concordance of C_b = 0.95. BAI can be measured without weighing, which may render it useful in settings where measuring accurate body weight is problematic. In summary, we have defined a new parameter, the BAI, which can be calculated from hip circumference and height only. It can be used in the clinical setting even in remote locations with very limited access to reliable scales. The BAI estimates %adiposity directly