1,152 research outputs found

    The Certified Chaplain in the Modern Hospital

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    Reconstructing (super)trees from data sets with missing distances: Not all is lost

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    The wealth of phylogenetic information accumulated over many decades of biological research, coupled with recent technological advances in molecular sequence generation, present significant opportunities for researchers to investigate relationships across and within the kingdoms of life. However, to make best use of this data wealth, several problems must first be overcome. One key problem is finding effective strategies to deal with missing data. Here, we introduce Lasso, a novel heuristic approach for reconstructing rooted phylogenetic trees from distance matrices with missing values, for datasets where a molecular clock may be assumed. Contrary to other phylogenetic methods on partial datasets, Lasso possesses desirable properties such as its reconstructed trees being both unique and edge-weighted. These properties are achieved by Lasso restricting its leaf set to a large subset of all possible taxa, which in many practical situations is the entire taxa set. Furthermore, the Lasso approach is distance-based, rendering it very fast to run and suitable for datasets of all sizes, including large datasets such as those generated by modern Next Generation Sequencing technologies. To better understand the performance of Lasso, we assessed it by means of artificial and real biological datasets, showing its effectiveness in the presence of missing data. Furthermore, by formulating the supermatrix problem as a particular case of the missing data problem, we assessed Lasso's ability to reconstruct supertrees. We demonstrate that, although not specifically designed for such a purpose, Lasso performs better than or comparably with five leading supertree algorithms on a challenging biological data set. Finally, we make freely available a software implementation of Lasso so that researchers may, for the first time, perform both rooted tree and supertree reconstruction with branch lengths on their own partial datasets

    Changes in the Spatial Allocation of Cropland in the Ft. Cobb Watershed as a Result of Environmental Restrictions

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    Pollution runoff estimates from SWAT are used in a mathematical programming model to optimally model site-specific crop and conservation practices for pollution abatement in the Ft. Cobb watershed in Southwestern Oklahoma. Results indicate the tradeoffs between producer income, sediment and nutrient runoff and the spatial allocation of crops in the watershed.Environmental Economics and Policy,

    Impact of United States Corn-Based Ethanol Production on Land Use

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    This study measures the impact of corn-based ethanol production in the United States on land use in other countries, or indirect land use. Indirect land use is a change from non-cropland to cropland (e.g. deforestation) that may occur in response to increasing scarcity of cropland. As farmers worldwide respond to higher crop prices in order to maintain the global food supply and demand balance, pristine lands are cleared and converted to new cropland to replace the crops for feed and food that were diverted elsewhere to biofuel production. The results show that increasing ethanol production in the US has a positive and significant relation to U.S corn price. However, U.S. corn price does not have a significant impact on changes in corn acreage in Brazil and other countries such as Canada, Japan and China. Although many authors have hypothesized that increased ethanol production in the U.S. will increase corn prices, which will result in increased change in land use in other countries, these results suggest that the effect is minimal at best. This is important because although production of ethanol for fuel is often criticized for negatively impacting the environment because of indirect land use, this study was unable to prove the existence of indirect land use.ethanol, indirect land use, Agricultural and Food Policy, Demand and Price Analysis, Land Economics/Use, Marketing,

    Thermophilin 13: In Silico Analysis Provides New Insight in Genes Involved in Bacteriocin Production

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    Bacteriocins are a large family of ribosomally synthesised proteinaceous toxins that are produced by bacteria and archaea and have antimicrobial activity against closely related species to the producer strain. Antimicrobial proteinaceous compounds are associated with a wide range of applications, including as a pathogen inhibitor in food and medical use. Among the several lactic acid bacteria (LAB) commonly used in fresh and fermented food preservation, Streptococcus thermophilus is well known for its importance as a starter culture for yoghurt and cheese. Previous studies described the bacteriocin thermophilin 13 exclusively in S. thermophilus SFi13 and the genes encoding its production as an operon consisting of two genes (thmA and thmB). However, the majority of bacteriocins possess a complex production system, which involves several genes encoding dedicated proteins with relatively specific functions. Up to now, far too little attention has been paid to the genes involved in the synthesis, regulation and expression of thermophilin 13. The aim of the present study, using in silico gene mining, was to investigate the presence of a regulation system involved in thermophilin 13 production. Results revealed the dedicated putative bacteriocin gene cluster (PBGC), which shows high similarity with the class IIb bacteriocins genes. This newly revealed PBGC, which was also found within various strains of Streptococcus thermophilus, provides a new perspective and insights into understanding the mechanisms implicated in the production of thermophilin 13

    Nanofibers Offer Alternative Ways to the Treatment of Skin Infections

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    Injury to the skin causes a breach in the protective layer surrounding the body. Many pathogens are resistant to antibiotics, rendering conventional treatment less effective. This led to the use of alternative antimicrobial compounds, such as silver ions, in skin treatment. In this review nanofibers, and the incorporation of natural antimicrobial compounds in these scaffolds, are discussed as an alternative way to control skin infections. Electrospinning as a technique to prepare nanofibers is discussed. The possibility of using these structures as drug delivery systems is investigated

    Land Use Implications of Expanding Biofuel Demand

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    The Renewable Fuel Standard mandates in the Energy Independence and Security Act of 2007 will require 36 billion gallons of ethanol to be produced in 2022. The mandates require that 16 of the 36 billion gallons must be produced from cellulosic feedstocks. The potential land use implications resulting from these mandates were examined using two methods, the POLYSYS model and a general equilibrium model. Results of the POLYSYS analysis indicated that 72.1 million tons of corn stover, 23.5 million tons of wheat straw, and 24.7 million acres would be used to produce 109 million tons of switchgrass in 2025 to meet the mandate. Results of the CGE analysis indicated that 10.9 billion bushels of corn grain, 71 million tons of corn stover, and 56,200 tons of switchgrass is needed to meet the mandate.cellulosic ethanol, corn stover, grain ethanol, renewable fuel standard, switchgrass, Crop Production/Industries, Demand and Price Analysis, Environmental Economics and Policy, Land Economics/Use, Resource /Energy Economics and Policy, Q15, Q42,
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