Further evidence for double-strand breaks originating from a paired radical precursor from studies of oxygen fixation processes

By using a fast reaction technique which employs H2S gas as a fast-reacting chemical repair agent, it is possible to measure the competition kinetics between chemical repair reactions and oxygen fixation reactions in model DNA and cellular systems. In plasmid pBR322 DNA irradiated with electrons, we have compared the oxygen fixation reactions of the free radical precursors that lead to the production of single-strand (SSBs) and double-strand breaks (DSBs). For the oxygen-dependent fixation of radical damage leading to SSBs, a second-order rate constant of 2.3 x 10(8) dm(3) mol(-1) s(-1) was obtained compared to 8.9 x 10(7) dm(3) mol(-1) s(-1) for DSBs. The difference is in general agreement with predictions from a multiple-radical model where the precursor of a DSB originates from two radicals. The fixation of this precursor by oxygen will require both radicals to be fixed for the DSB to be formed, which will have slower kinetics than that of single free-radical precursors of SSBs. (C) 1999 by Radiation Research Society.

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods.

Use of the γ-H2AX Assay to Investigate DNA Repair Dynamics Following Multiple Radiation Exposures

Radiation therapy is one of the most common and effective strategies used to treat cancer. The irradiation is usually performed with a fractionated scheme, where the dose required to kill tumour cells is given in several sessions, spaced by specific time intervals, to allow healthy tissue recovery. In this work, we examined the DNA repair dynamics of cells exposed to radiation delivered in fractions, by assessing the response of histone-2AX (H2AX) phosphorylation (γ-H2AX), a marker of DNA double strand breaks. γ-H2AX foci induction and disappearance were monitored following split dose irradiation experiments in which time interval between exposure and dose were varied. Experimental data have been coupled to an analytical theoretical model, in order to quantify key parameters involved in the foci induction process. Induction of γ-H2AX foci was found to be affected by the initial radiation exposure with a smaller number of foci induced by subsequent exposures. This was compared to chromatin relaxation and cell survival. The time needed for full recovery of γ-H2AX foci induction was quantified (12 hours) and the 1:1 relationship between radiation induced DNA double strand breaks and foci numbers was critically assessed in the multiple irradiation scenarios.

Combining multi-scale geophysical techniques for robust hydro-structural characterisation in catchments underlain by hard rock in post-glacial regions

Accurate conceptual models of groundwater systems are essential for correct interpretation of monitoring data in catchment studies. In surface-water dominated hard rock regions, modern ground and surface water monitoring programmes often have very high resolution chemical, meteorological and hydrological observations but lack an equivalent emphasis on the subsurface environment, the properties of which exert a strong control on flow pathways and interactions with surface waters. The reasons for this disparity are the complexity of the system and the difficulty in accurately characterising the subsurface, except locally at outcrops or in boreholes. This is particularly the case in maritime north-western Europe, where a legacy of glacial activity, combined with large areas underlain by heterogeneous igneous and metamorphic bedrock, make the structure and weathering of bedrock difficult to map or model. Traditional approaches which seek to extrapolate information from borehole to field-scale are of limited application in these environments due to the high degree of spatial heterogeneity. Here we apply an integrative and multi-scale approach, optimising and combining standard geophysical techniques to generate a three-dimensional geological conceptual model of the subsurface in a catchment in NE Ireland. Available airborne LiDAR, electromagnetic and magnetic data sets were analysed for the region. At field-scale surface geophysical methods, including electrical resistivity tomography, seismic refraction, ground penetrating radar and magnetic surveys, were used and combined with field mapping of outcrops and borehole testing. The study demonstrates how combined interpretation of multiple methods at a range of scales produces robust three-dimensional conceptual models and a stronger basis for interpreting groundwater and surface water monitoring data.

Machine Learning for Predictive Maintenance: A Multiple Classifiers Approach

In this paper a multiple classifier machine learning methodology for Predictive Maintenance (PdM) is presented. PdM is a prominent strategy for dealing with maintenance issues given the increasing need to minimize downtime and associated costs. One of the challenges with PdM is generating so called ’health factors’ or quantitative indicators of the status of a system associated with a given maintenance issue, and determining their relationship to operating costs and failure risk. The proposed PdM methodology allows dynamical decision rules to be adopted for maintenance management and can be used with high-dimensional and censored data problems. This is achieved by training multiple classification modules with different prediction horizons to provide different performance trade-offs in terms of frequency of unexpected breaks and unexploited lifetime and then employing this information in an operating cost based maintenance decision system to minimise expected costs. The effectiveness of the methodology is demonstrated using a simulated example and a benchmark semiconductor manufacturing maintenance problem.

Small leucine rich proteoglycan family regulates multiple signalling pathways in neural development and maintenance

The small leucine-rich repeat proteoglycan (SLRPs) family of proteins currently consists of five classes, based on their structural composition and chromosomal location. As biologically active components of the extracellular matrix (ECM), SLRPs were known to bind to various collagens, having a role in regulating fibril assembly, organization and degradation. More recently, as a function of their diverse proteins cores and glycosaminoglycan side chains, SLRPs have been shown to be able to bind various cell surface receptors, growth factors, cytokines and other ECM components resulting in the ability to influence various cellular functions. Their involvement in several signaling pathways such as Wnt, transforming growth factor-β and epidermal growth factor receptor also highlights their role as matricellular proteins. SLRP family members are expressed during neural development and in adult neural tissues, including ocular tissues. This review focuses on describing SLRP family members involvement in neural development with a brief summary of their role in non-neural ocular tissues and in response to neural injury.

AaeAP1 and AaeAP2: Novel Antimicrobial Peptides from the Venom of the Scorpion, Androctonus aeneas: Structural Characterisation, Molecular Cloning of Biosynthetic Precursor-Encoding cDNAs and Engineering of Analogues with Enhanced Antimicrobial and Anticancer Activities

The main functions of the abundant polypeptide toxins present in scorpion venoms are the debilitation of arthropod prey or defence against predators. These effects are achieved mainly through the blocking of an array of ion channel types within the membranes of excitable cells. However, while these ion channel-blocking toxins are tightly-folded by multiple disulphide bridges between cysteine residues, there are additional groups of peptides in the venoms that are devoid of cysteine residues. These non-disulphide bridged peptides are the subject of much research interest, and among these are peptides that exhibit antimicrobial activity. Here, we describe two novel non-disulphide-bridged antimicrobial peptides that are present in the venom of the North African scorpion, Androctonus aeneas. The cDNAs encoding the biosynthetic precursors of both peptides were cloned from a venom-derived cDNA library using 3'- and 5'-RACE strategies. Both translated precursors contained open-reading frames of 74 amino acid residues, each encoding one copy of a putative novel nonadecapeptide, whose primary structures were FLFSLIPSVIAGLVSAIRN and FLFSLIPSAIAGLVSAIRN, respectively. Both peptides were C-terminally amidated. Synthetic versions of each natural peptide displayed broad-spectrum antimicrobial activities, but were devoid of antiproliferative activity against human cancer cell lines. However, synthetic analogues of each peptide, engineered for enhanced cationicity and amphipathicity, exhibited increases in antimicrobial potency and acquired antiproliferative activity against a range of human cancer cell lines. These data clearly illustrate the potential that natural peptide templates provide towards the design of synthetic analogues for therapeutic exploitation.

Oxygen vacancy formation in CeO2 and Ce1-xZrxO2 solid solutions:electron localization, electrostatic potential and structural relaxation

Ceria (CeO2) and ceria-based composite materials, especially Ce1-xZrxO2 solid solutions, possess a wide range of applications in many important catalytic processes, such as three-way catalysts, owing to their excellent oxygen storage capacity (OSC) through the oxygen vacancy formation and refilling. Much of this activity has focused on the understanding of the electronic and structural properties of defective CeO2 with and without doping, and comprehending the determining factor for oxygen vacancy formation and the rule to tune the formation energy by doping has constituted a central issue in material chemistry related to ceria. However, the calculation on electronic structures and the corresponding relaxation patterns in defective CeO2-x oxides remains at present a challenge in the DFT framework. A pragmatic approach based on density functional theory with the inclusion of on-site Coulomb correction, i.e. the so-called DFT + U technique, has been extensively applied in the majority of recent theoretical investigations. Firstly, we review briefly the latest electronic structure calculations of defective CeO2(111), focusing on the phenomenon of multiple configurations of the localized 4f electrons, as well as the discussions of its formation mechanism and the catalytic role in activating the O-2 molecule. Secondly, aiming at shedding light on the doping effect on tuning the oxygen vacancy formation in ceria-based solid solutions, we summarize the recent theoretical results of Ce1-xZrxO2 solid solutions in terms of the effect of dopant concentrations and crystal phases. A general model on O vacancy formation is also discussed; it consists of electrostatic and structural relaxation terms, and the vital role of the later is emphasized. Particularly, we discuss the crucial role of the localized structural relaxation patterns in determining the superb oxygen storage capacity in kappa-phase Ce1-xZr1-xO2. Thirdly, we briefly discuss some interesting findings for the oxygen vacancy formation in pure ceria nanoparticles (NPs) uncovered by DFT calculations and compare those with the bulk or extended surfaces of ceria as well as different particle sizes, emphasizing the role of the electrostatic field in determining the O vacancy formation.

Looking again at troubled families: parents' perspectives on multiple adversities

The 'Troubled Families' policy and intervention agenda is based on a deficit approach that tends to ignore the role of structural disadvantage in the lives of the families it targets. In an effort to support this rhetoric, both quantitative and qualitative data have been used, and misused, to create a representation of these families, which emphasizes risk and individual blame and minimizes societal factors. This current paper presents findings from an in-depth qualitative study using a biographical narrative approach to explore parents' experiences of multiple adversities at different times over the life-course. Key themes relating to the pattern and nature of adversities experienced by participants provide a more nuanced understanding of the lives of families experiencing multiple and complex problems, highlighting how multiple interpretations are often possible within the context of professional intervention. The findings support the increasing call to move away from procedurally driven, risk averse child protection practice towards more relationally based practice, which addresses not only the needs of all family members but recognizes parents as individuals in their own right.

CSI 2264: Simultaneous Optical and Infrared Light Curves of Young Disk-bearing Stars in NGC 2264 with CoRoT and Spitzer—Evidence for Multiple Origins of Variability

We present the Coordinated Synoptic Investigation of NGC 2264, a continuous 30 day multi-wavelength photometric monitoring campaign on more than 1000 young cluster members using 16 telescopes. The unprecedented combination of multi-wavelength, high-precision, high-cadence, and long-duration data opens a new window into the time domain behavior of young stellar objects. Here we provide an overview of the observations, focusing on results from Spitzer and CoRoT. The highlight of this work is detailed analysis of 162 classical T Tauri stars for which we can probe optical and mid-infrared flux variations to 1% amplitudes and sub-hour timescales. We present a morphological variability census and then use metrics of periodicity, stochasticity, and symmetry to statistically separate the light curves into seven distinct classes, which we suggest represent different physical processes and geometric effects. We provide distributions of the characteristic timescales and amplitudes and assess the fractional representation within each class. The largest category (>20%) are optical "dippers" with discrete fading events lasting ~1-5 days. The degree of correlation between the optical and infrared light curves is positive but weak; notably, the independently assigned optical and infrared morphology classes tend to be different for the same object. Assessment of flux variation behavior with respect to (circum)stellar properties reveals correlations of variability parameters with Hα emission and with effective temperature. Overall, our results point to multiple origins of young star variability, including circumstellar obscuration events, hot spots on the star and/or disk, accretion bursts, and rapid structural changes in the inner disk. Based on data from the Spitzer and CoRoT missions. The CoRoT space mission was developed and is operated by the French space agency CNES, with participation of ESA's RSSD and Science Programmes, Austria, Belgium, Brazil, Germany, and Spain.