The Quantized Hall Insulator: A New Insulator in Two-Dimensions

Quite generally, an insulator is theoretically defined by a vanishing conductivity tensor at the absolute zero of temperature. In classical insulators, such as band insulators, vanishing conductivities lead to diverging resistivities. In other insulators, in particular when a high magnetic field (B) is added, it is possible that while the magneto-resistance diverges, the Hall resistance remains finite, which is known as a Hall insulator. In this letter we demonstrate experimentally the existence of another, more exotic, insulator. This insulator, which terminates the quantum Hall effect series in a two-dimensional electron system, is characterized by a Hall resistance which is approximately quantized in the quantum unit of resistance h/e^2. This insulator is termed a quantized Hall insulator. In addition we show that for the same sample, the insulating state preceding the QHE series, at low-B, is of the HI kind.Comment: 4 page

Kinetic frustration and the nature of the magnetic and paramagnetic states in iron pnictides and iron chalcogenides

The iron pnictide and chalcogenide compounds are a subject of intensive investigations due to their high temperature superconductivity.\cite{a-LaFeAsO} They all share the same structure, but there is significant variation in their physical properties, such as magnetic ordered moments, effective masses, superconducting gaps and T$_c$. Many theoretical techniques have been applied to individual compounds but no consistent description of the trends is available \cite{np-review}. We carry out a comparative theoretical study of a large number of iron-based compounds in both their magnetic and paramagnetic states. We show that the nature of both states is well described by our method and the trends in all the calculated physical properties such as the ordered moments, effective masses and Fermi surfaces are in good agreement with experiments across the compounds. The variation of these properties can be traced to variations in the key structural parameters, rather than changes in the screening of the Coulomb interactions. Our results provide a natural explanation of the strongly Fermi surface dependent superconducting gaps observed in experiments\cite{Ding}. We propose a specific optimization of the crystal structure to look for higher T$_c$ superconductors.Comment: 5 pages, 3 figures with a 5-page supplementary materia

Identification of physicochemical selective pressure on protein encoding nucleotide sequences

BACKGROUND: Statistical methods for identifying positively selected sites in protein coding regions are one of the most commonly used tools in evolutionary bioinformatics. However, they have been limited by not taking the physiochemical properties of amino acids into account. RESULTS: We develop a new codon-based likelihood model for detecting site-specific selection pressures acting on specific physicochemical properties. Nonsynonymous substitutions are divided into substitutions that differ with respect to the physicochemical properties of interest, and those that do not. The substitution rates of these two types of changes, relative to the synonymous substitution rate, are then described by two parameters, γ and ω respectively. The new model allows us to perform likelihood ratio tests for positive selection acting on specific physicochemical properties of interest. The new method is first used to analyze simulated data and is shown to have good power and accuracy in detecting physicochemical selective pressure. We then re-analyze data from the class-I alleles of the human Major Histocompatibility Complex (MHC) and from the abalone sperm lysine. CONCLUSION: Our new method allows a more flexible framework to identify selection pressure on particular physicochemical properties

Selective Constraints on Amino Acids Estimated by a Mechanistic Codon Substitution Model with Multiple Nucleotide Changes

Empirical substitution matrices represent the average tendencies of substitutions over various protein families by sacrificing gene-level resolution. We develop a codon-based model, in which mutational tendencies of codon, a genetic code, and the strength of selective constraints against amino acid replacements can be tailored to a given gene. First, selective constraints averaged over proteins are estimated by maximizing the likelihood of each 1-PAM matrix of empirical amino acid (JTT, WAG, and LG) and codon (KHG) substitution matrices. Then, selective constraints specific to given proteins are approximated as a linear function of those estimated from the empirical substitution matrices. Akaike information criterion (AIC) values indicate that a model allowing multiple nucleotide changes fits the empirical substitution matrices significantly better. Also, the ML estimates of transition-transversion bias obtained from these empirical matrices are not so large as previously estimated. The selective constraints are characteristic of proteins rather than species. However, their relative strengths among amino acid pairs can be approximated not to depend very much on protein families but amino acid pairs, because the present model, in which selective constraints are approximated to be a linear function of those estimated from the JTT/WAG/LG/KHG matrices, can provide a good fit to other empirical substitution matrices including cpREV for chloroplast proteins and mtREV for vertebrate mitochondrial proteins. The present codon-based model with the ML estimates of selective constraints and with adjustable mutation rates of nucleotide would be useful as a simple substitution model in ML and Bayesian inferences of molecular phylogenetic trees, and enables us to obtain biologically meaningful information at both nucleotide and amino acid levels from codon and protein sequences.Comment: Table 9 in this article includes corrections for errata in the Table 9 published in 10.1371/journal.pone.0017244. Supporting information is attached at the end of the article, and a computer-readable dataset of the ML estimates of selective constraints is available from 10.1371/journal.pone.001724

Correcting the Bias of Empirical Frequency Parameter Estimators in Codon Models

Markov models of codon substitution are powerful inferential tools for studying biological processes such as natural selection and preferences in amino acid substitution. The equilibrium character distributions of these models are almost always estimated using nucleotide frequencies observed in a sequence alignment, primarily as a matter of historical convention. In this note, we demonstrate that a popular class of such estimators are biased, and that this bias has an adverse effect on goodness of fit and estimates of substitution rates. We propose a “corrected” empirical estimator that begins with observed nucleotide counts, but accounts for the nucleotide composition of stop codons. We show via simulation that the corrected estimates outperform the de facto standard estimates not just by providing better estimates of the frequencies themselves, but also by leading to improved estimation of other parameters in the evolutionary models. On a curated collection of sequence alignments, our estimators show a significant improvement in goodness of fit compared to the approach. Maximum likelihood estimation of the frequency parameters appears to be warranted in many cases, albeit at a greater computational cost. Our results demonstrate that there is little justification, either statistical or computational, for continued use of the -style estimators

Nonlinear Sigma Model for Disordered Media: Replica Trick for Non-Perturbative Results and Interactions

In these lectures, given at the NATO ASI at Windsor (2001), applications of the replicas nonlinear sigma model to disordered systems are reviewed. A particular attention is given to two sets of issues. First, obtaining non-perturbative results in the replica limit is discussed, using as examples (i) an oscillatory behaviour of the two-level correlation function and (ii) long-tail asymptotes of different mesoscopic distributions. Second, a new variant of the sigma model for interacting electrons in disordered normal and superconducting systems is presented, with demonstrating how to reduce it, under certain controlled approximations, to known ``phase-only'' actions, including that of the ``dirty bosons'' model.Comment: 25 pages, Proceedings of the NATO ASI "Field Theory of Strongly Correlated Fermions and Bosons in Low - Dimensional Disordered Systems", Windsor, August, 2001; to be published by Kluwe

Surface and Temporal Biosignatures

Recent discoveries of potentially habitable exoplanets have ignited the prospect of spectroscopic investigations of exoplanet surfaces and atmospheres for signs of life. This chapter provides an overview of potential surface and temporal exoplanet biosignatures, reviewing Earth analogues and proposed applications based on observations and models. The vegetation red-edge (VRE) remains the most well-studied surface biosignature. Extensions of the VRE, spectral "edges" produced in part by photosynthetic or nonphotosynthetic pigments, may likewise present potential evidence of life. Polarization signatures have the capacity to discriminate between biotic and abiotic "edge" features in the face of false positives from band-gap generating material. Temporal biosignatures -- modulations in measurable quantities such as gas abundances (e.g., CO2), surface features, or emission of light (e.g., fluorescence, bioluminescence) that can be directly linked to the actions of a biosphere -- are in general less well studied than surface or gaseous biosignatures. However, remote observations of Earth's biosphere nonetheless provide proofs of concept for these techniques and are reviewed here. Surface and temporal biosignatures provide complementary information to gaseous biosignatures, and while likely more challenging to observe, would contribute information inaccessible from study of the time-averaged atmospheric composition alone.Comment: 26 pages, 9 figures, review to appear in Handbook of Exoplanets. Fixed figure conversion error

Episodic Evolution and Adaptation of Chloroplast Genomes in Ancestral Grasses

It has been suggested that the chloroplast genomes of the grass family, Poaceae, have undergone an elevated evolutionary rate compared to most other angiosperms, yet the details of this phenomenon have remained obscure. To know how the rate change occurred during evolution, estimation of the time-scale with reliable calibrations is needed. The recent finding of 65 Ma grass phytoliths in Cretaceous dinosaur coprolites places the diversification of the grasses to the Cretaceous period, and provides a reliable calibration in studying the tempo and mode of grass chloroplast evolution.By using chloroplast genome data from angiosperms and by taking account of new paleontological evidence, we now show that episodic rate acceleration both in terms of non-synonymous and synonymous substitutions occurred in the common ancestral branch of the core Poaceae (a group formed by rice, wheat, maize, and their allies) accompanied by adaptive evolution in several chloroplast proteins, while the rate reverted to the slow rate typical of most monocot species in the terminal branches.Our finding of episodic rate acceleration in the ancestral grasses accompanied by adaptive molecular evolution has a profound bearing on the evolution of grasses, which form a highly successful group of plants. The widely used model for estimating divergence times was based on the assumption of correlated rates between ancestral and descendant lineages. However, the assumption is proved to be inadequate in approximating the episodic rate acceleration in the ancestral grasses, and the assumption of independent rates is more appropriate. This finding has implications for studies of molecular evolutionary rates and time-scale of evolution in other groups of organisms

Cellular Radiosensitivity: How much better do we understand it?

Purpose: Ionizing radiation exposure gives rise to a variety of lesions in DNA that result in genetic instability and potentially tumorigenesis or cell death. Radiation extends its effects on DNA by direct interaction or by radiolysis of H2O that generates free radicals or aqueous electrons capable of interacting with and causing indirect damage to DNA. While the various lesions arising in DNA after radiation exposure can contribute to the mutagenising effects of this agent, the potentially most damaging lesion is the DNA double strand break (DSB) that contributes to genome instability and/or cell death. Thus in many cases failure to recognise and/or repair this lesion determines the radiosensitivity status of the cell. DNA repair mechanisms including homologous recombination (HR) and non-homologous end-joining (NHEJ) have evolved to protect cells against DNA DSB. Mutations in proteins that constitute these repair pathways are characterised by radiosensitivity and genome instability. Defects in a number of these proteins also give rise to genetic disorders that feature not only genetic instability but also immunodeficiency, cancer predisposition, neurodegeneration and other pathologies. Conclusions: In the past fifty years our understanding of the cellular response to radiation damage has advanced enormously with insight being gained from a wide range of approaches extending from more basic early studies to the sophisticated approaches used today. In this review we discuss our current understanding of the impact of radiation on the cell and the organism gained from the array of past and present studies and attempt to provide an explanation for what it is that determines the response to radiation

Leukocytes Are Recruited through the Bronchial Circulation to the Lung in a Spontaneously Hypertensive Rat Model of COPD

Chronic obstructive pulmonary disease (COPD) kills approximately 2.8 million people each year, and more than 80% of COPD cases can be attributed to smoking. Leukocytes recruited to the lung contribute to COPD pathology by releasing reactive oxygen metabolites and proteolytic enzymes. In this work, we investigated where leukocytes enter the lung in the early stages of COPD in order to better understand their effect as a contributor to the development of COPD. We simultaneously evaluated the parenchyma and airways for neutrophil accumulation, as well as increases in the adhesion molecules and chemokines that cause leukocyte recruitment in the early stages of tobacco smoke induced lung disease. We found neutrophil accumulation and increased expression of adhesion molecules and chemokines in the bronchial blood vessels that correlated with the accumulation of leukocytes recovered from the lung. The expression of adhesion molecules and chemokines in other vascular beds did not correlate with leukocytes recovered in bronchoalveolar lavage fluid (BALF). These data strongly suggest leukocytes are recruited in large measure through the bronchial circulation in response to tobacco smoke. Our findings have important implications for understanding the etiology of COPD and suggest that pharmaceuticals designed to reduce leukocyte recruitment through the bronchial circulation may be a potential therapy to treat COPD