Preventing Deer Damage to Your Trees and Shrubs

Deer/human conflicts have increased due to growing deer populations, limited resources and suburban development in deer habitat. In winter, deer often browse in residential landscapes. This can be reduced by selecting unpalatable plants, protecting woody plants with burlap or trunk protectors, and using deer repellent. In extreme cases, deer can be completely excluded with a fence

Empirical Bayes analysis of single nucleotide polymorphisms

<p>Abstract</p> <p>Background</p> <p>An important goal of whole-genome studies concerned with single nucleotide polymorphisms (SNPs) is the identification of SNPs associated with a covariate of interest such as the case-control status or the type of cancer. Since these studies often comprise the genotypes of hundreds of thousands of SNPs, methods are required that can cope with the corresponding multiple testing problem. For the analysis of gene expression data, approaches such as the empirical Bayes analysis of microarrays have been developed particularly for the detection of genes associated with the response. However, the empirical Bayes analysis of microarrays has only been suggested for binary responses when considering expression values, i.e. continuous predictors.</p> <p>Results</p> <p>In this paper, we propose a modification of this empirical Bayes analysis that can be used to analyze high-dimensional categorical SNP data. This approach along with a generalized version of the original empirical Bayes method are available in the R package siggenes version 1.10.0 and later that can be downloaded from <url>http://www.bioconductor.org</url>.</p> <p>Conclusion</p> <p>As applications to two subsets of the HapMap data show, the empirical Bayes analysis of microarrays cannot only be used to analyze continuous gene expression data, but also be applied to categorical SNP data, where the response is not restricted to be binary. In association studies in which typically several ten to a few hundred SNPs are considered, our approach can furthermore be employed to test interactions of SNPs. Moreover, the posterior probabilities resulting from the empirical Bayes analysis of (prespecified) interactions/genotypes can also be used to quantify the importance of these interactions.</p

Predictors and outcome impact of perioperative serum sodium changes in a high-risk population.

BACKGROUND: The perioperative period may be associated with a marked neurohumoral stress response, significant fluid losses, and varied fluid replacement regimes. Acute changes in serum sodium concentration are therefore common, but predictors and outcomes of these changes have not been investigated in a large surgical population. METHODS: We carried out a retrospective cohort analysis of 27 068 in-patient non-cardiac surgical procedures in a tertiary teaching hospital setting. Data on preoperative conditions, perioperative events, hospital length of stay, and mortality were collected, along with preoperative and postoperative serum sodium measurements up to 7 days after surgery. Logistic regression was used to investigate the association between sodium changes and mortality, and to identify clinical characteristics associated with a deviation from baseline sodium >5 mmol litre(-1). RESULTS: Changes in sodium concentration >5 mmol litre(-1) were associated with increased mortality risk (adjusted odds ratio 1.49 for a decrease, 3.02 for an increase). Factors independently associated with a perioperative decrease in serum sodium concentration >5 mmol litre(-1) included age >60, diabetes mellitus, and the use of patient-controlled opioid analgesia. Factors associated with a similar increase were preoperative oxygen dependency, mechanical ventilation, central nervous system depression, non-elective surgery, and major operative haemorrhage. CONCLUSIONS: Maximum deviation from preoperative serum sodium value is associated with increased hospital mortality in patients undergoing in-patient non-cardiac surgery. Specific preoperative and perioperative factors are associated with significant serum sodium changes.This work was supported by the Cambridge University Division of Anaesthesia.This is the author accepted manuscript. The final version is available from Oxford University Press via http://dx.doi.org/10.1093/bja/aeu40

Anti-Allergic Cromones Inhibit Histamine and Eicosanoid Release from Activated Human and Murine Mast Cells by Releasing Annexin A1

PMCID: PMC3601088This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

A Connectivity-Based Psychometric Prediction Framework for Brain-Behavior Relationship Studies.

peer reviewedThe recent availability of population-based studies with neuroimaging and behavioral measurements opens promising perspectives to investigate the relationships between interindividual variability in brain regions' connectivity and behavioral phenotypes. However, the multivariate nature of connectivity-based prediction model severely limits the insight into brain-behavior patterns for neuroscience. To address this issue, we propose a connectivity-based psychometric prediction framework based on individual regions' connectivity profiles. We first illustrate two main applications: 1) single brain region's predictive power for a range of psychometric variables and 2) single psychometric variable's predictive power variation across brain region. We compare the patterns of brain-behavior provided by these approaches to the brain-behavior relationships from activation approaches. Then, capitalizing on the increased transparency of our approach, we demonstrate how the influence of various data processing and analyses can directly influence the patterns of brain-behavior relationships, as well as the unique insight into brain-behavior relationships offered by this approach

Deep EST profiling of developing fenugreek endosperm to investigate galactomannan biosynthesis and its regulation

Galactomannans are hemicellulosic polysaccharides composed of a (1 → 4)-linked β-D-mannan backbone substituted with single-unit (1 → 6)-α-linked D-galactosyl residues. Developing fenugreek (Trigonella foenum-graecum) seeds are known to accumulate large quantities of galactomannans in the endosperm, and were thus used here as a model system to better understand galactomannan biosynthesis and its regulation. We first verified the specific deposition of galactomannans in developing endosperms and determined that active accumulation occurred from 25 to 38 days post anthesis (DPA) under our growth conditions. We then examined the expression levels during seed development of ManS and GMGT, two genes encoding backbone and side chain synthetic enzymes. Based on transcript accumulation dynamics for ManS and GMGT, cDNA libraries were constructed using RNA isolated from endosperms at four ages corresponding to before, at the beginning of, and during active galactomannan deposition. DNA from these libraries was sequenced using the 454 sequencing technology to yield a total of 1.5 million expressed sequence tags (ESTs). Through analysis of the EST profiling data, we identified genes known to be involved in galactomannan biosynthesis, as well as new genes that may be involved in this process, and proposed a model for the flow of carbon from sucrose to galactomannans. Measurement of in vitro ManS and GMGT activities and analysis of sugar phosphate and nucleotide sugar levels in the endosperms of developing fenugreek seeds provided data consistent with this model. In vitro enzymatic assays also revealed that the ManS enzyme from fenugreek endosperm preferentially used GDP-mannose as the substrate for the backbone synthesis