PROFILE OF PARTICIPANTS IN FISH AND WILDLIFE RELATED OUTDOOR RECREATIONAL ACTIVITIES IN THE UNITED STATES

Resource /Energy Economics and Policy,

OUTDOOR RECREATION TRENDS AND MARKET OPPORTUNITIES IN THE UNITED STATES

In 1994 and 1995, the National Survey of Recreation and Environment (NSRE) was accomplished by interviewing approximately 17,000 Americans over age 15 in random-digit-dialing telephone samplings. The primary purpose was to learn about the outdoor recreation activities of people over age 15 in the United States. They were asked about their participation in 62 specific recreation activities.Resource /Energy Economics and Policy,

Multivisceral intestinal transplantation: Surgical pathology

We report the diagnostic surgical pathology of two children who underwent multivisceral abdominal transplantation and survived for 1 month and 6 months. There is little relevant literature, and diagnostic criteria for the various clinical possibilities are not established; this is made more complicated by the simultaneous occurrence of more than one process. We based our interpretations on conventional histology, augmented with immunohistology, including HLA staining that distinguished graft from host cells in situ. In some instances functional analysis of T cells propagated from the same biopsies was available and was used to corroborate morphological interpretations. A wide spectrum of changes was encountered. Graft-versus-host disease, a prime concern before surgery, was not seen. Rejection was severe in 1 patient, not present in the other, and both had evidence of lymphoproliferative disease, which was related to Epstein-Barr virus. Bacterial translocation through the gut wall was also a feature in both children. This paper documents and illustrates the various diagnostic possibilities.. © 1989 Informa UK Ltd All rights reserved: reproduction in whole or part not permitted

Residue management in double-crop systems: Impact on soybean growth and yield

Double-crop soybeans [Glycine max(L.) Merr.] have the potential to be a productive and profitable system. However, due to delayed planting, double-crop soybeans frequently experience lower yields and higher stress. Because planting is a major production constraint, a critical practice is the management of previous wheat residue. Trials were established in 2012, 2013, and 2014 in Saint Joseph, LA, and in 2013 and 2014 in Winnsboro, LA. The four residue management treatments investigated included conventionally tilled, planted into burned residue, planted into mowed residue, and planted into standing wheat residue. Vegetative and reproductive growth parameters, as well as yield, were used to evaluate the influence of residue management on productivity. Overall, residue management did not have a significant impact on early season growth parameters, except for plant height in 2012 at St. Joseph; however, it did significantly influence yield at both locations. In Saint Joseph in 2012, yields from planting into wheat residue were significantly lower than burned and mowed plots (1.2 compared with 2.8 and 2.7 Mg ha-1, respectively), and tilled treatments yielded significantly less than all three nontilled treatments in 2013 and 2014. In Winnsboro, planting into residue left on the soil surface resulted in significantly higher yields than when residue was removed. Overall, leaving residue on the soil surface provided stable yields across years and locations; however, not managing the residue can result in diminished yields. Therefore, practices such as mowing of wheat residue prior to planting provide an alternative to traditional no-till planting.Peer reviewedPlant and Soil Science

A genome-wide scan for common alleles affecting risk for autism

Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C

Haplotype association analyses in resources of mixed structure using Monte Carlo testing

<p>Abstract</p> <p>Background</p> <p>Genomewide association studies have resulted in a great many genomic regions that are likely to harbor disease genes. Thorough interrogation of these specific regions is the logical next step, including regional haplotype studies to identify risk haplotypes upon which the underlying critical variants lie. Pedigrees ascertained for disease can be powerful for genetic analysis due to the cases being enriched for genetic disease. Here we present a Monte Carlo based method to perform haplotype association analysis. Our method, hapMC, allows for the analysis of full-length and sub-haplotypes, including imputation of missing data, in resources of nuclear families, general pedigrees, case-control data or mixtures thereof. Both traditional association statistics and transmission/disequilibrium statistics can be performed. The method includes a phasing algorithm that can be used in large pedigrees and optional use of pseudocontrols.</p> <p>Results</p> <p>Our new phasing algorithm substantially outperformed the standard expectation-maximization algorithm that is ignorant of pedigree structure, and hence is preferable for resources that include pedigree structure. Through simulation we show that our Monte Carlo procedure maintains the correct type 1 error rates for all resource types. Power comparisons suggest that transmission-disequilibrium statistics are superior for performing association in resources of only nuclear families. For mixed structure resources, however, the newly implemented pseudocontrol approach appears to be the best choice. Results also indicated the value of large high-risk pedigrees for association analysis, which, in the simulations considered, were comparable in power to case-control resources of the same sample size.</p> <p>Conclusions</p> <p>We propose hapMC as a valuable new tool to perform haplotype association analyses, particularly for resources of mixed structure. The availability of meta-association and haplotype-mining modules in our suite of Monte Carlo haplotype procedures adds further value to the approach.</p

A genetic ensemble approach for gene-gene interaction identification

<p>Abstract</p> <p>Background</p> <p>It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging.</p> <p>Methods</p> <p>In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA) and an ensemble of classifiers (called genetic ensemble). Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP) subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise <it>double fault </it>is designed to quantify the degree of complementarity.</p> <p>Conclusions</p> <p>Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR) and is slightly better than Polymorphism Interaction Analysis (PIA), which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of combining identification results from different algorithms.</p

Bayesian Classification and Regression Trees for Predicting Incidence of Cryptosporidiosis

Background Classification and regression tree (CART) models are tree-based exploratory data analysis methods which have been shown to be very useful in identifying and estimating complex hierarchical relationships in ecological and medical contexts. In this paper, a Bayesian CART model is described and applied to the problem of modelling the cryptosporidiosis infection in Queensland, Australia. Methodology/Principal Findings We compared the results of a Bayesian CART model with those obtained using a Bayesian spatial conditional autoregressive (CAR) model. Overall, the analyses indicated that the nature and magnitude of the effect estimates were similar for the two methods in this study, but the CART model more easily accommodated higher order interaction effects. Conclusions/Significance A Bayesian CART model for identification and estimation of the spatial distribution of disease risk is useful in monitoring and assessment of infectious diseases prevention and control