Chronic Arsenic Exposure and Oxidative Stress: OGG1 Expression and Arsenic Exposure, Nail Selenium, and Skin Hyperkeratosis in Inner Mongolia

Arsenic, a human carcinogen, is known to induce oxidative damage to DNA. In this study we investigated oxidative stress and As exposure by determining gene expression of OGG1, which codes for an enzyme, 8-oxoguanine DNA glycosylase, involved in removing 8-oxoguanine in As-exposed individuals. Bayingnormen (Ba Men) residents in Inner Mongolia are chronically exposed to As via drinking water. Water, toenail, and blood samples were collected from 299 Ba Men residents exposed to 0.34–826 μg/L As. RNA was isolated from blood, and mRNA levels of OGG1 were determined using real-time polymerase chain reaction. OGG1 expression levels were linked to As concentrations in drinking water and nails, selenium concentrations in nails, and skin hyperkeratosis. OGG1 expression was strongly associated with water As concentrations (p < 0.0001). Addition of the quadratic term significantly improved the fit compared with the linear model (p = 0.05). The maximal OGG1 response was at the water As concentration of 149 μg/L. OGG1 expression was also significantly associated with toenail As concentrations (p = 0.015) but inversely associated with nail Se concentrations (p = 0.0095). We found no significant differences in the As-induced OGG1 expression due to sex, smoking, or age even though the oldest group showed the strongest OGG1 response (p = 0.0001). OGG1 expression showed a dose-dependent increased risk of skin hyperkeratosis in males (trend analysis, p = 0.02), but the trend was not statistically significant in females. The results from this study provide a linkage between oxidative stress and As exposure in humans. OGG1 expression may be useful as a biomarker for assessing oxidative stress from As exposure

A cross-sectional study of the nutritional status of community-dwelling people with idiopathic Parkinson's disease

<p>Abstract</p> <p>Background</p> <p>Parkinson's disease (PD) patients have an increased risk of under-nutrition, but we are unaware of any population based prevalence studies of under-nutrition in PD. The main objective of this study was to identify the prevalence, and nature, of under-nutrition in a representative population of people with PD.</p> <p>Methods</p> <p>People diagnosed with idiopathic PD from within two PD prevalence study sites in North-East England were asked to participate in this study. Those who participated (n = 136) were assessed using a number of standard rating scales including Hoehn & Yahr stage and Unified Parkinson's Disease Rating Scale (UPDRS). Body mass index (BMI), mid-arm circumference (MAC), triceps skin fold thickness (TSF) and grip strength were recorded together with social and demographic information.</p> <p>Results</p> <p>BMI < 20 identified over 15% of the study group to have under-nutrition. The Malnutritional Universal Screening Tool (MUST) scoring system identified 23.5% of participants at medium or high risk of malnutrition. Low BMI, indicating under-nutrition, was associated with greater age and disease duration, lower MAC, TSF, mid-arm muscle circumference (MAMC), reduced grip strength and a report of unintentional weight loss. Problems increased with increasing age and disease duration and were greater in females.</p> <p>Conclusions</p> <p>Under-nutrition is a problem for around 15% of community dwelling people with PD. All PD patients should be screened for under-nutrition; the MUST score is a useful early screening tool.</p

Structural basis for native agonist and synthetic inhibitor recognition by the Pseudomonas aeruginosa quorum sensing regulator PqsR (MvfR)

Bacterial populations co-ordinate gene expression collectively through quorum sensing (QS), a cell-to-cell communication mechanism employing diffusible signal molecules. The LysR-type transcriptional regulator (LTTR) protein PqsR (MvfR) is a key component of alkyl-quinolone (AQ)-dependent QS in Pseudomonas aeruginosa. PqsR is activated by 2-alkyl-4-quinolones including the Pseudomonas quinolone signal (PQS; 2-heptyl-3-hydroxy-4(1H)-quinolone), its precursor 2-heptyl-4- hydroxyquinoline (HHQ) and their C9 congeners, 2-nonyl-3-hydroxy-4(1H)-quinolone (C9-PQS) and 2-nonyl-4-hydroxyquinoline (NHQ). These drive the autoinduction of AQ biosynthesis and the up-regulation of key virulence determinants as a function of bacterial population density. Consequently, PqsR constitutes a potential target for novel antibacterial agents which attenuate infection through the blockade of virulence. Here we present the crystal structures of the PqsR co-inducer binding domain (CBD) and a complex with the native agonist NHQ. We show that the structure of the PqsR CBD has an unusually large ligand-binding pocket in which a native AQ agonist is stabilized entirely by hydrophobic interactions. Through a ligand-based design strategy we synthesized and evaluated a series of 50 AQ and novel quinazolinone (QZN) analogues and measured the impact on AQ biosynthesis, virulence gene expression and biofilm development. The simple exchange of two isosteres (OH for NH2) switches a QZN agonist to an antagonist with a concomitant impact on the induction of bacterial virulence factor production. We also determined the complex crystal structure of a QZN antagonist bound to PqsR revealing a similar orientation in the ligand binding pocket to the native agonist NHQ. This structure represents the first description of an LTTR-antagonist complex. Overall these studies present novel insights into LTTR ligand binding and ligand-based drug design and provide a chemical scaffold for further anti-P. aeruginosa virulence drug development by targeting the AQ receptor PqsR

Differential expression of 12 histone deacetylase (HDAC) genes in astrocytomas and normal brain tissue: class II and IV are hypoexpressed in glioblastomas

<p>Abstract</p> <p>Background</p> <p>Glioblastoma is the most lethal primary malignant brain tumor. Although considerable progress has been made in the treatment of this aggressive tumor, the clinical outcome for patients remains poor. Histone deacetylases (HDACs) are recognized as promising targets for cancer treatment. In the past several years, HDAC inhibitors (HDACis) have been used as radiosensitizers in glioblastoma treatment. However, no study has demonstrated the status of global <it>HDAC </it>expression in gliomas and its possible correlation to the use of HDACis. The purpose of this study was to evaluate and compare mRNA and protein levels of class I, II and IV of HDACs in low grade and high grade astrocytomas and normal brain tissue and to correlate the findings with the malignancy in astrocytomas.</p> <p>Methods</p> <p>Forty-three microdissected patient tumor samples were evaluated. The histopathologic diagnoses were 20 low-grade gliomas (13 grade I and 7 grade II) and 23 high-grade gliomas (5 grade III and 18 glioblastomas). Eleven normal cerebral tissue samples were also analyzed (54 total samples analyzed). mRNA expression of class I, II, and IV <it>HDACs </it>was studied by quantitative real-time polymerase chain reaction and normalized to the housekeeping gene <it>β-glucuronidase</it>. Protein levels were evaluated by western blotting.</p> <p>Results</p> <p>We found that mRNA levels of class II and IV <it>HDACs </it>were downregulated in glioblastomas compared to low-grade astrocytomas and normal brain tissue (7 in 8 genes, <it>p </it>< 0.05). The protein levels of class II HDAC9 were also lower in high-grade astrocytomas than in low-grade astrocytomas and normal brain tissue. Additionally, we found that histone H3 (but not histone H4) was more acetylated in glioblastomas than normal brain tissue.</p> <p>Conclusion</p> <p>Our study establishes a negative correlation between <it>HDAC </it>gene expression and the glioma grade suggesting that class II and IV <it>HDACs </it>might play an important role in glioma malignancy. Evaluation of histone acetylation levels showed that histone H3 is more acetylated in glioblastomas than normal brain tissue confirming the downregulation of <it>HDAC </it>mRNA in glioblastomas.</p

Mechanochemical modeling of dynamic microtubule growth involving sheet-to-tube transition

Microtubule dynamics is largely influenced by nucleotide hydrolysis and the resultant tubulin configuration changes. The GTP cap model has been proposed to interpret the stabilizing mechanism of microtubule growth from the view of hydrolysis effects. Besides, the microtubule growth involves the closure of a curved sheet at its growing end. The curvature conversion also helps to stabilize the successive growth, and the curved sheet is referred to as the conformational cap. However, there still lacks theoretical investigation on the mechanical-chemical coupling growth process of microtubules. In this paper, we study the growth mechanisms of microtubules by using a coarse-grained molecular method. Firstly, the closure process involving a sheet-to-tube transition is simulated. The results verify the stabilizing effect of the sheet structure, and the minimum conformational cap length that can stabilize the growth is demonstrated to be two dimers. Then, we show that the conformational cap can function independently of the GTP cap, signifying the pivotal role of mechanical factors. Furthermore, based on our theoretical results, we describe a Tetris-like growth style of microtubules: the stochastic tubulin assembly is regulated by energy and harmonized with the seam zipping such that the sheet keeps a practically constant length during growth.Comment: 23 pages, 7 figures. 2 supporting movies have not been uploaded due to the file type restriction

Escherichia coli genome-wide promoter analysis: Identification of additional AtoC binding target elements

<p>Abstract</p> <p>Background</p> <p>Studies on bacterial signal transduction systems have revealed complex networks of functional interactions, where the response regulators play a pivotal role. The AtoSC system of <it>E. coli </it>activates the expression of <it>atoDAEB </it>operon genes, and the subsequent catabolism of short-chain fatty acids, upon acetoacetate induction. Transcriptome and phenotypic analyses suggested that <it>atoSC </it>is also involved in several other cellular activities, although we have recently reported a palindromic repeat within the <it>atoDAEB </it>promoter as the single, <it>cis</it>-regulatory binding site of the AtoC response regulator. In this work, we used a computational approach to explore the presence of yet unidentified AtoC binding sites within other parts of the <it>E. coli </it>genome.</p> <p>Results</p> <p>Through the implementation of a computational <it>de novo </it>motif detection workflow, a set of candidate motifs was generated, representing putative AtoC binding targets within the <it>E. coli </it>genome. In order to assess the biological relevance of the motifs and to select for experimental validation of those sequences related robustly with distinct cellular functions, we implemented a novel approach that applies Gene Ontology Term Analysis to the motif hits and selected those that were qualified through this procedure. The computational results were validated using Chromatin Immunoprecipitation assays to assess the <it>in vivo </it>binding of AtoC to the predicted sites. This process verified twenty-two additional AtoC binding sites, located not only within intergenic regions, but also within gene-encoding sequences.</p> <p>Conclusions</p> <p>This study, by tracing a number of putative AtoC binding sites, has indicated an AtoC-related cross-regulatory function. This highlights the significance of computational genome-wide approaches in elucidating complex patterns of bacterial cell regulation.</p

Evaluating Forecasting Methods

Ideally, forecasting methods should be evaluated in the situations for which they will be used. Underlying the evaluation procedure is the need to test methods against reasonable alternatives. Evaluation consists of four steps: testing assumptions, testing data and methods, replicating outputs, and assessing outputs. Most principles for testing forecasting methods are based on commonly accepted methodological procedures, such as to prespecify criteria or to obtain a large sample of forecast errors. However, forecasters often violate such principles, even in academic studies. Some principles might be surprising, such as do not use R-square, do not use Mean Square Error, and do not use the within-sample fit of the model to select the most accurate time-series model. A checklist of 32 principles is provided to help in systematically evaluating forecasting methods

Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c

Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29–39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance