Evidence for a hypoxic fixation reaction leading to the induction of ssb and dsb in irradiated DNA

Purpose: To measure hypoxic chemical fixation processes of radiation damage in both isolated plasmid DNA and in GSH-depleted E. coli cells.

A comparison of the radiosensitivity of relaxed and supercoiled plasmid DNA

Purpose: The aim of the work was to compare critically the radiosensitivity of the supercoiled and relaxed forms of a plasmid DNA system commonly used in DNA damage assays.

Critical energies for ssb and dsb induction in plasmid DNA by vacuum-UV photons: an arrangement for irradiating dry or hydrated DNA with monochromatic photons

Purpose: Theoretical modelling techniques are often used to simulate the action of ionizing radiations on cells at the nanometre level, Using monoenergetic vacuum-UV (VUV) radiation to irradiate DNA either dry or humidified, the action spectra for the induction of DNA damage by low energy photons and the role of water and can be studied. These data provide inputs for the theoretical models.

Critical energies for SSB and DSB induction in plasmid DNA by low-energy photons: action spectra for strand-break induction in plasmid DNA irradiated in vacuum

Purpose: To measure action spectra for the induction of single- strand breaks (SSB) and double-strand breaks (DSB) in plasmid DNA by low-energy photons and provide estimates for the energy dependence of strand-break formation important for track-structure simulations of DNA damage.

The relationship between the RBE of alpha particles and the radiosensitivity of different mutations of Chinese hamster cells

The RBE of alpha -particles in different mutations of Chinese hamster cells was determined with the aim of identifying differences in the sensitivity to x-ray and alpha -particle-induced DNA damage. Two parental lines of Chinese hamster cells and four radiosensitive mutants were irradiated with different single doses of x-rays and alpha -particles and clonogenic cell survival was determined. Radiosensitivity to x-rays varied by a factor of 5 between the cell strains whereas sensitivity to alpha -particle irradiation was almost identical among all strains. The RBE is only determined by the sensitivity of the cells towards x-rays. Since cells with different defects of repair or cell cycle control have different radiosensitivities, we conclude that the effects of x-ray irradiation and the RBE are mostly determined by the activity of repair processes.

A model for radiation-induced bystander effects, with allowance for spatial position and the effects of cell turnover

Bystander effects, whereby cells that are not directly exposed to ionizing radiation exhibit adverse biological effects, have been observed in a number of experimental systems. A novel stochastic model of the radiation-induced bystander effect is developed that takes account of spatial location, cell killing and repopulation. The ionizing radiation dose- and time-responses of this model are explored, and it is shown to exhibit pronounced downward curvature in the high dose-rate region, similar to that observed in many experimental systems, reviewed in the paper. It is also shown to predict the augmentation of effect after fractionated delivery of dose that has been observed in certain experimental systems. It is shown that the generally intractable solution of the full stochastic system can be considerably simplified by assumption of pairwise conditional dependence that varies exponentially over time. (C) 2004 Elsevier Ltd. All rights reserved.

A Monte Carlo model of DNA double-strand break clustering and rejoining kinetics for the analysis of pulsed-field gel electrophoresis data

In studies of radiation-induced DNA fragmentation and repair, analytical models may provide rapid and easy-to-use methods to test simple hypotheses regarding the breakage and rejoining mechanisms involved. The random breakage model, according to which lesions are distributed uniformly and independently of each other along the DNA, has been the model most used to describe spatial distribution of radiation-induced DNA damage. Recently several mechanistic approaches have been proposed that model clustered damage to DNA. In general, such approaches focus on the study of initial radiation-induced DNA damage and repair, without considering the effects of additional (unwanted and unavoidable) fragmentation that may take place during the experimental procedures. While most approaches, including measurement of total DNA mass below a specified value, allow for the occurrence of background experimental damage by means of simple subtractive procedures, a more detailed analysis of DNA fragmentation necessitates a more accurate treatment. We have developed a new, relatively simple model of DNA breakage and the resulting rejoining kinetics of broken fragments. Initial radiation-induced DNA damage is simulated using a clustered breakage approach, with three free parameters: the number of independently located clusters, each containing several DNA double-strand breaks (DSBs), the average number of DSBs within a cluster (multiplicity of the cluster), and the maximum allowed radius within which DSBs belonging to the same cluster are distributed. Random breakage is simulated as a special case of the DSB clustering procedure. When the model is applied to the analysis of DNA fragmentation as measured with pulsed-field gel electrophoresis (PFGE), the hypothesis that DSBs in proximity rejoin at a different rate from that of sparse isolated breaks can be tested, since the kinetics of rejoining of fragments of varying size may be followed by means of computer simulations. The problem of how to account for background damage from experimental handling is also carefully considered. We have shown that the conventional procedure of subtracting the background damage from the experimental data may lead to erroneous conclusions during the analysis of both initial fragmentation and DSB rejoining. Despite its relative simplicity, the method presented allows both the quantitative and qualitative description of radiation-induced DNA fragmentation and subsequent rejoining of double-stranded DNA fragments. (C) 2004 by Radiation Research Society.

Calcium fluxes modulate the radiation-induced bystander responses in targeted glioma and fibroblast cells

Bystander responses have been reported to be a major determinant of the response of cells to radiation exposure at low doses, including those of relevance to therapy. This study investigated the role of changes in calcium levels in bystander responses leading to chromosomal damage in nonirradiated T98G glioma cells and AG01522 fibroblasts that had been either exposed to conditioned medium from irradiated cells or co-cultured with a population where a fraction of cells were individually targeted through the nucleus or cytoplasm with a precise number of microbeam helium-3 particles. After the recipient cells were treated with conditioned medium from T98G or AG01522 cells that had been irradiated through either nucleus or cytoplasm, rapid calcium fluxes were monitored in the nonirradiated recipient cells. Their characteristics were dependent on the source of the conditioned medium but had no dependence on radiation dose. When recipient cells were co-cultured with an irradiated population of either T98G or AG01522 cells, micronuclei were induced in the nonirradiated cells, but this response was eliminated by treating the cells with calcicludine (CaC), a potent blocker of Ca2+ channels. Moreover, both the calcium fluxes and the bystander effect were inhibited when the irradiated T98G cells were treated with aminoguanidine, an inhibitor of nitric oxide synthase (NOS), and when the irradiated AG01522 cells were treated with DMSO, a scavenger of reactive oxygen species (ROS), which indicates that NO and ROS were involved in the bystander responses generated from irradiated T98G and AG01522 cells, respectively. Our findings indicate that calcium signaling may be an early response in radiation-induced bystander effects leading to chromosome damage. (c) 2006 by Radiation Research Society.

Weak interactions, omnivory and emergent food-web properties

Empirical studies have shown that, in real ecosystems, species-interaction strengths are generally skewed in their distribution towards weak interactions. Some theoretical work also suggests that weak interactions, especially in omnivorous links, are important for the local stability of a community at equilibrium. However, the majority of theoretical studies use uniform distributions of interaction strengths to generate artificial communities for study. We investigate the effects of the underlying interaction-strength distribution upon the return time, permanence and feasibility of simple Lotka-Volterra equilibrium communities. We show that a skew towards weak interactions promotes local and global stability only when omnivory is present. It is found that skewed interaction strengths are an emergent property of stable omnivorous communities, and that this skew towards weak interactions creates a dynamic constraint maintaining omnivory. Omnivory is more likely to occur when omnivorous interactions are skewed towards weak interactions. However, a skew towards weak interactions increases the return time to equilibrium, delays the recovery of ecosystems and hence decreases the stability of a community. When no skew is imposed, the set of stable omnivorous communities shows an emergent distribution of skewed interaction strengths. Our results apply to both local and global concepts of stability and are robust to the definition of a feasible community. These results are discussed in the light of empirical data and other theoretical studies, in conjunction with their broader implications for community assembly.

A Common KIF6 Polymorphism Increases Vulnerability to Low-Density Lipoprotein Cholesterol: Two Meta-Analyses and a Meta-Regression Analysis

Background: We sought to determine if a common polymorphism can influence vulnerability to LDL cholesterol, and thereby influence the clinical benefit derived from therapies that reduce LDL cholesterol.

Job Strain and Alcohol Intake:A Collaborative Meta-Analysis of Individual-Participant Data from 140 000 Men and Women

BACKGROUND: The relationship between work-related stress and alcohol intake is uncertain. In order to add to the thus far inconsistent evidence from relatively small studies, we conducted individual-participant meta-analyses of the association between work-related stress (operationalised as self-reported job strain) and alcohol intake. METHODOLOGY AND PRINCIPAL FINDINGS: We analysed cross-sectional data from 12 European studies (n?=?142 140) and longitudinal data from four studies (n?=?48 646). Job strain and alcohol intake were self-reported. Job strain was analysed as a binary variable (strain vs. no strain). Alcohol intake was harmonised into the following categories: none, moderate (women: 1-14, men: 1-21 drinks/week), intermediate (women: 15-20, men: 22-27 drinks/week) and heavy (women: >20, men: >27 drinks/week). Cross-sectional associations were modelled using logistic regression and the results pooled in random effects meta-analyses. Longitudinal associations were examined using mixed effects logistic and modified Poisson regression. Compared to moderate drinkers, non-drinkers and (random effects odds ratio (OR): 1.10, 95% CI: 1.05, 1.14) and heavy drinkers (OR: 1.12, 95% CI: 1.00, 1.26) had higher odds of job strain. Intermediate drinkers, on the other hand, had lower odds of job strain (OR: 0.92, 95% CI: 0.86, 0.99). We found no clear evidence for longitudinal associations between job strain and alcohol intake. CONCLUSIONS: Our findings suggest that compared to moderate drinkers, non-drinkers and heavy drinkers are more likely and intermediate drinkers less likely to report work-related stress.

Job Strain and Tobacco Smoking:An Individual-Participant Data Meta-Analysis of 166 130 Adults in 15 European Studies

BACKGROUND: Tobacco smoking is a major contributor to the public health burden and healthcare costs worldwide, but the determinants of smoking behaviours are poorly understood. We conducted a large individual-participant meta-analysis to examine the extent to which work-related stress, operationalised as job strain, is associated with tobacco smoking in working adults. METHODOLOGY AND PRINCIPAL FINDINGS: We analysed cross-sectional data from 15 European studies comprising 166 130 participants. Longitudinal data from six studies were used. Job strain and smoking were self-reported. Smoking was harmonised into three categories never, ex- and current. We modelled the cross-sectional associations using logistic regression and the results pooled in random effects meta-analyses. Mixed effects logistic regression was used to examine longitudinal associations. Of the 166 130 participants, 17% reported job strain, 42% were never smokers, 33% ex-smokers and 25% current smokers. In the analyses of the cross-sectional data, current smokers had higher odds of job strain than never-smokers (age, sex and socioeconomic position-adjusted odds ratio: 1.11, 95% confidence interval: 1.03, 1.18). Current smokers with job strain smoked, on average, three cigarettes per week more than current smokers without job strain. In the analyses of longitudinal data (1 to 9 years of follow-up), there was no clear evidence for longitudinal associations between job strain and taking up or quitting smoking. CONCLUSIONS: Our findings show that smokers are slightly more likely than non-smokers to report work-related stress. In addition, smokers who reported work stress smoked, on average, slightly more cigarettes than stress-free smokers.

Animal group forces resulting from predator avoidance and competition minimization

A new model to explain animal spacing, based on a trade-off between foraging efficiency and predation risk, is derived from biological principles. The model is able to explain not only the general tendency for animal groups to form, but some of the attributes of real groups. These include the independence of mean animal spacing from group population, the observed variation of animal spacing with resource availability and also with the probability of predation, and the decline in group stability with group size. The appearance of "neutral zones" within which animals are not motivated to adjust their relative positions is also explained. The model assumes that animals try to minimize a cost potential combining the loss of intake rate due to foraging interference and the risk from exposure to predators. The cost potential describes a hypothetical field giving rise to apparent attractive and repulsive forces between animals. Biologically based functions are given for the decline in interference cost and increase in the cost of predation risk with increasing animal separation. Predation risk is calculated from the probabilities of predator attack and predator detection as they vary with distance. Using example functions for these probabilities and foraging interference, we calculate the minimum cost potential for regular lattice arrangements of animals before generalizing to finite-sized groups and random arrangements of animals, showing optimal geometries in each case and describing how potentials vary with animal spacing. (C) 1999 Academic Press.</p>

Exploring statistical and population aspects of network complexity

The characterization and the definition of the complexity of objects is an important but very difficult problem that attracted much interest in many different fields. In this paper we introduce a new measure, called network diversity score (NDS), which allows us to quantify structural properties of networks. We demonstrate numerically that our diversity score is capable of distinguishing ordered, random and complex networks from each other and, hence, allowing us to categorize networks with respect to their structural complexity. We study 16 additional network complexity measures and find that none of these measures has similar good categorization capabilities. In contrast to many other measures suggested so far aiming for a characterization of the structural complexity of networks, our score is different for a variety of reasons. First, our score is multiplicatively composed of four individual scores, each assessing different structural properties of a network. That means our composite score reflects the structural diversity of a network. Second, our score is defined for a population of networks instead of individual networks. We will show that this removes an unwanted ambiguity, inherently present in measures that are based on single networks. In order to apply our measure practically, we provide a statistical estimator for the diversity score, which is based on a finite number of samples.