Ergodic infinite group extensions of geodesic flows on translation surfaces

We show that generic infinite group extensions of geodesic flows on square tiled translation surfaces are ergodic in almost every direction, subject to certain natural constraints. Recently K. Fr\c{a}czek and C. Ulcigrai have shown that certain concrete staircases, covers of square-tiled surfaces, are not ergodic in almost every direction. In contrast we show the almost sure ergodicity of other concrete staircases. An appendix provides a combinatorial approach for the study of square-tiled surfaces

The Particle Physics Reach of High-Energy Neutrino Astronomy

We discuss the prospects for high-energy neutrino astronomy to study particle physics in the energy regime comparable to and beyond that obtainable at the current and planned colliders. We describe the various signatures of high-energy cosmic neutrinos expected in both neutrino telescopes and air shower experiments and discuss these measurements within the context of theoretical models with a quantum gravity or string scale near a TeV, supersymmetry and scenarios with interactions induced by electroweak instantons. We attempt to access the particle physics reach of these experiments.Comment: Mini-review article for New Journal of Physics, "Focus on Neutrinos" issue. 27 pages, 11 figure

Smith-Waterman peak alignment for comprehensive two-dimensional gas chromatography-mass spectrometry

<p>Abstract</p> <p>Background</p> <p>Comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC × GC-MS) is a powerful technique which has gained increasing attention over the last two decades. The GC × GC-MS provides much increased separation capacity, chemical selectivity and sensitivity for complex sample analysis and brings more accurate information about compound retention times and mass spectra. Despite these advantages, the retention times of the resolved peaks on the two-dimensional gas chromatographic columns are always shifted due to experimental variations, introducing difficulty in the data processing for metabolomics analysis. Therefore, the retention time variation must be adjusted in order to compare multiple metabolic profiles obtained from different conditions.</p> <p>Results</p> <p>We developed novel peak alignment algorithms for both homogeneous (acquired under the identical experimental conditions) and heterogeneous (acquired under the different experimental conditions) GC × GC-MS data using modified Smith-Waterman local alignment algorithms along with mass spectral similarity. Compared with literature reported algorithms, the proposed algorithms eliminated the detection of landmark peaks and the usage of retention time transformation. Furthermore, an automated peak alignment software package was established by implementing a likelihood function for optimal peak alignment.</p> <p>Conclusions</p> <p>The proposed Smith-Waterman local alignment-based algorithms are capable of aligning both the homogeneous and heterogeneous data of multiple GC × GC-MS experiments without the transformation of retention times and the selection of landmark peaks. An optimal version of the SW-based algorithms was also established based on the associated likelihood function for the automatic peak alignment. The proposed alignment algorithms outperform the literature reported alignment method by analyzing the experiment data of a mixture of compound standards and a metabolite extract of mouse plasma with spiked-in compound standards.</p

Quantitative metabolomics based on gas chromatography mass spectrometry: status and perspectives

Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites relevant to a specific phenotypic characteristic can be identified. However, the reliability of the analytical data is a prerequisite for correct biological interpretation in metabolomics analysis. In this review the challenges in quantitative metabolomics analysis with regards to analytical as well as data preprocessing steps are discussed. Recommendations are given on how to optimize and validate comprehensive silylation-based methods from sample extraction and derivatization up to data preprocessing and how to perform quality control during metabolomics studies. The current state of method validation and data preprocessing methods used in published literature are discussed and a perspective on the future research necessary to obtain accurate quantitative data from comprehensive GC-MS data is provided

Recent advances of metabolomics in plant biotechnology

Biotechnology, including genetic modification, is a very important approach to regulate the production of particular metabolites in plants to improve their adaptation to environmental stress, to improve food quality, and to increase crop yield. Unfortunately, these approaches do not necessarily lead to the expected results due to the highly complex mechanisms underlying metabolic regulation in plants. In this context, metabolomics plays a key role in plant molecular biotechnology, where plant cells are modified by the expression of engineered genes, because we can obtain information on the metabolic status of cells via a snapshot of their metabolome. Although metabolome analysis could be used to evaluate the effect of foreign genes and understand the metabolic state of cells, there is no single analytical method for metabolomics because of the wide range of chemicals synthesized in plants. Here, we describe the basic analytical advancements in plant metabolomics and bioinformatics and the application of metabolomics to the biological study of plants

Application of a Label-free, Gel-free Quantitative Proteomics Method for Ecotoxicological Studies of Small Fish Species

Although two-dimensional electrophoresis (2D-GE) remains the basis for many ecotoxicoproteomic analyses, newer non-gel-based methods are beginning to be applied to overcome throughput and coverage limitations of 2D-GE. The overall objective of our research was to apply a comprehensive, liquid chromatography–tandem mass spectrometry (LC-MS/MS)-based proteomic approach to identify and quantify differentially expressed hepatic proteins from female fathead minnows exposed to fadrozole, a potent inhibitor of estrogen synthesis. Female fathead minnows were exposed to 0 (control), 0.04, and 1.0 μg of fadrozole/L of water for 4 days, and proteomic analysis was performed. Proteins were extracted and digested, and proteolytic peptides were separated via high-resolution one- or two-dimensional (1-D or 2-D) ultrapressure liquid chromatography (UPLC) and analyzed by tandem mass spectrometry. Mass spectra were searched against the National Center for Biotechnology Information (NCBI) ray-finned fish (Actinopterygii) database, resulting in identification of 782 unique proteins by single-dimension UPLC. When multidimensional LC analysis (2-D) was performed, an average increase of 1.9× in the number of identified proteins was observed. Differentially expressed proteins in fadrozole exposures were consistent with changes in liver function, including a decline in concentrations of vitellogenin as well as other proteins associated with endocrine function and cholesterol synthesis. Overall, these results demonstrate that a gel-free, label-free proteomic analysis method can successfully be utilized to determine differentially expressed proteins in small fish species after toxicant exposure

Genome wide association study identifies seven loci that account for 86% of the population attributable risk of Paget's disease of bone

Bone and mineral researc