Successful nesting by a Bald Eagle pair in prairie grasslands of the Texas Panhandle

We observed a breeding Bald Eagle ( Haliaeetus leucocephalus ) pair nesting in a short-grass prairie and agricultural community on the southern Great Plains of the Texas Panhandle in 2004 and 2005. The nesting eagles produced 1 fledgling in 2004 and 2 fledglings in 2005. Our assessment of landcover types within a 5-km radius of the nest indicated that grasslands accounted for most of the area (90%), followed by agricultural lands (8%). Black-tailed prairie dog ( Cynomys ludovicianus ) colonies occupied 2.5% of the area, and single human residences with associated structures (i.e., barns) occupied 2.5 ha in surface area was 51 km from the nest. An analysis of regurgitated castings collected near the nest revealed a mammalian-dominated, breeding-season diet with black-tailed prairie dogs occurring in 80.9% of the castings. Other identified prey included cottontails ( Sylvilagus spp., 15.9%), black-tailed jackrabbits ( Lepus californicus , 3.2%), pronghorn ( Antilocapra americana , 3.2%), and plains pocket gopher ( Geomys bursarius , 1.6%). Bird remains were also present in 34.9% of the castings. This is the first reported successful nesting of Bald Eagles in the panhandle region of Texas since 1916; the nest is particularly unique because of its distance from any substantial body of water.     

Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits

We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.     

Protein intrinsic disorder as a flexible armor and a weapon of HIV-1

Many proteins and protein regions are disordered in their native, biologically active states. These proteins/regions are abundant in different organisms and carry out important biological functions that complement the functional repertoire of ordered proteins. Viruses, with their highly compact genomes, small proteomes, and high adaptability for fast change in their biological and physical environment utilize many of the advantages of intrinsic disorder. In fact, viral proteins are generally rich in intrinsic disorder, and intrinsically disordered regions are commonly used by viruses to invade the host organisms, to hijack various host systems, and to help viruses in accommodation to their hostile habitats and to manage their economic usage of genetic material. In this review, we focus on the structural peculiarities of HIV-1 proteins, on the abundance of intrinsic disorder in viral proteins, and on the role of intrinsic disorder in their functions.     

Genetic variation in the gene encoding calpain-10 is associated with type 2 diabetes mellitus

Type 2 or non-insulin-dependent diabetes mellitus (NIDDM) is the most common form of diabetes worldwide, affecting approximately 4% of the world's adult population. It is multifactorial in origin with both genetic and environmental factors contributing to its development. A genome-wide screen for type 2 diabetes genes carried out in Mexican Americans localized a susceptibility gene, designated NIDDM1, to chromosome 2. Here we describe the positional cloning of a gene located in the NIDDM1 region that shows association with type 2 diabetes in Mexican Americans and a Northern European population from the Botnia region of Finland. This putative diabetes-susceptibility gene encodes a ubiquitously expressed member of the calpain-like cysteine protease family, calpain-10 (CAPN10). This finding suggests a novel pathway that may contribute to the development of type 2 diabetes.     

Forecasting Interest Rates and Yield Spreads: The Informational Content of Implied Futures Yields and Best-fitting Forward Rate Models

Forecasts of interest rates for different maturities are essential for forecasts of asset prices. The growth of derivatives markets coupled with the development of complex theories of the term structure of interest rates have provided forecasters with a rich array of variables for predicting interest rates and yield spreads. This paper extends previous work on forecasting future interest rates and yield spreads using market data for T-bills, T-Notes, and Treasury Bond spot and futures contracts. The information conveyed in technical models that use market data is also assessed, using a recent innovation in interest rate modelling, the maximum smoothness approach. Forecasts from this model are compared with predicted yields and yield spreads derived from futures prices as well as with those of the random walk model. The results show some evidence of market segmentation, with more arbitrage evident for nearby maturities. Market participants appear to show a greater degree of consensus on short-term interest rates than on longer-term interest rates. There is some indication that forecasts from the futures markets are marginally better than those provided by those of the maximum-smoothness approach, consistent with the informational advantages of futures markets. Finally, futures and maximum-smoothness market forecasts are shown to outperform those of the random walk model.© 1997 John Wiley & Sons, Ltd.     

Dense genotyping identifies and localizes multiple common and rare variant association signals in celiac disease

Using variants from the 1000 Genomes Project pilot European CEU dataset and data from additional resequencing studies, we densely genotyped 183 non-HLA risk loci previously associated with immune-mediated diseases in 12,041 individuals with celiac disease (cases) and 12,228 controls. We identified 13 new celiac disease risk loci reaching genome-wide significance, bringing the number of known loci (including the HLA locus) to 40. We found multiple independent association signals at over one-third of these loci, a finding that is attributable to a combination of common, low-frequency and rare genetic variants. Compared to previously available data such as those from HapMap3, our dense genotyping in a large sample collection provided a higher resolution of the pattern of linkage disequilibrium and suggested localization of many signals to finer scale regions. In particular, 29 of the 54 fine-mapped signals seemed to be localized to single genes and, in some instances, to gene regulatory elements. Altogether, we define the complex genetic architecture of the risk regions of and refine the risk signals for celiac disease, providing the next step toward uncovering the causal mechanisms of the disease.     

Neural model identification,variable selection and model adequacy

In recent years an impressive array of publications has appeared claiming considerable successes of neural networks in modelling financial data but sceptical practitioners and statisticians are still raising the question of whether neural networks really are ‘a major breakthrough or just a passing fad’. A major reason for this is the lack of procedures for performing tests for misspecified models, and tests of statistical significance for the various parameters that have been estimated, which makes it difficult to assess the model's significance and the possibility that any short‐term successes that are reported might be due to ‘data mining’. In this paper we describe a methodology for neural model identification which facilitates hypothesis testing at two levels: model adequacy and variable significance. The methodology includes a model selection procedure to produce consistent estimators, a variable selection procedure based on statistical significance and a model adequacy procedure based on residuals analysis. We propose a novel, computationally efficient scheme for estimating sampling variability of arbitrarily complex statistics for neural models and apply it to variable selection. The approach is based on sampling from the asymptotic distribution of the neural model's parameters (‘parametric sampling’). Controlled simulations are used for the analysis and evaluation of our model identification methodology. A case study in tactical asset allocation is used to demonstrate how the methodology can be applied to real‐life problems in a way analogous to stepwise forward regression analysis. Neural models are contrasted to multiple linear regression. The results indicate the presence of non‐linear relationships in modelling the equity premium. Copyright © 1999 John Wiley & Sons, Ltd.     

Systemic Thinking and Practice Toward Facilitating Inclusive Education: Reflections on a Case of Co-Generated Knowledge and Action in South Africa

This article offers our reflections around a case of facilitating systemic thinking and practice in which the first author of the article (Tlale) interacted with research participants/participant researchers with the intention of strengthening systemic thought and action toward fostering inclusive education in the setting (a rural school in the Eastern Cape in South Africa). We reflect upon the process and also how our engagement was perceived by participants, as expressed in feedback received from them. We point to how Tlale introduced the idea of systemic thinking (to teachers, school management team, school governing body, and a district officer for the district) as tied to the possibility of acting to generate transformation toward a more inclusive educational context for the benefit of the learners at the school in question, thus acting as a systemic mediator on their behalf.