Genotoxic mixtures and dissimilar action: Concepts for prediction and assessment

This article has been made available through the Brunel Open Access Publishing Fund. This article is distributed under the terms of the creative commons Attribution license which permits any use, distribution, and reproduction in any medium, provided the original author(s)and the source are credited.Combinations of genotoxic agents have frequently been assessed without clear assumptions regarding their expected (additive) mixture effects, often leading to claims of synergisms that might in fact be compatible with additivity. We have shown earlier that the combined effects of chemicals, which induce micronuclei (MN) in the cytokinesis-block micronucleus assay in Chinese hamster ovary-K1 cells by a similar mechanism, were additive according to the concept of concentration addition (CA). Here, we extended these studies and investigated for the first time whether valid additivity expectations can be formulated for MN-inducing chemicals that operate through a variety of mechanisms, including aneugens and clastogens (DNA cross-linkers, topoisomerase II inhibitors, minor groove binders). We expected that their effects should follow the additivity principles of independent action (IA). With two mixtures, one composed of various aneugens (colchicine, flubendazole, vinblastine sulphate, griseofulvin, paclitaxel), and another composed of aneugens and clastogens (flubendazole, doxorubicin, etoposide, melphalan and mitomycin C), we observed mixture effects that fell between the additivity predictions derived from CA and IA. We achieved better agreement between observation and prediction by grouping the chemicals into common assessment groups and using hybrid CA/IA prediction models. The combined effects of four dissimilarly acting compounds (flubendazole, paclitaxel, doxorubicin and melphalan) also fell within CA and IA. Two binary mixtures (flubendazole/paclitaxel and flubendazole/doxorubicin) showed effects in reasonable agreement with IA additivity. Our studies provide a systematic basis for the investigation of mixtures that affect endpoints of relevance to genotoxicity and show that their effects are largely additive.UK Food Standards Agenc

Differential expression analysis for sequence count data

*Motivation:* High-throughput nucleotide sequencing provides quantitative readouts in assays for RNA expression (RNA-Seq), protein-DNA binding (ChIP-Seq) or cell counting (barcode sequencing). Statistical inference of differential signal in such data requires estimation of their variability throughout the dynamic range. When the number of replicates is small, error modelling is needed to achieve statistical power.

*Results:* We propose an error model that uses the negative binomial distribution, with variance and mean linked by local regression, to model the null distribution of the count data. The method controls type-I error and provides good detection power. 

*Availability:* A free open-source R software package, _DESeq_, is available from the Bioconductor project and from "http://www-huber.embl.de/users/anders/DESeq":http://www-huber.embl.de/users/anders/DESeq

Human Immunity and the Design of Multi-Component, Single Target Vaccines

BACKGROUND: Inclusion of multiple immunogens to target a single organism is a strategy being pursued for many experimental vaccines, especially where it is difficult to generate a strongly protective response from a single immunogen. Although there are many human vaccines that contain multiple defined immunogens, in almost every case each component targets a different pathogen. As a consequence, there is little practical experience for deciding where the increased complexity of vaccines with multiple defined immunogens vaccines targeting single pathogens will be justifiable. METHODOLOGY/PRINCIPAL FINDINGS: A mathematical model, with immunogenicity parameters derived from a database of human responses to established vaccines, was used to predict the increase in the efficacy and the proportion of the population protected resulting from addition of further immunogens. The gains depended on the relative protection and the range of responses in the population to each immunogen and also to the correlation of the responses between immunogens. In most scenarios modeled, the gain in overall efficacy obtained by adding more immunogens was comparable to gains obtained from a single immunogen through the use of better formulations or adjuvants. Multi-component single target vaccines were more effective at decreasing the proportion of poor responders than increasing the overall efficacy of the vaccine in a population. CONCLUSIONS/SIGNIFICANCE: Inclusion of limited number of antigens in a vaccine aimed at targeting a single organism will increase efficacy, but the gains are relatively modest and for a practical vaccine there are constraints that are likely to limit multi-component single target vaccines to a small number of key antigens. The model predicts that this type of vaccine will be most useful where the critical issue is the reduction in proportion of poor responders

Maximum Likelihood Estimation of the Negative Binomial Dispersion Parameter for Highly Overdispersed Data, with Applications to Infectious Diseases

BACKGROUND: The negative binomial distribution is used commonly throughout biology as a model for overdispersed count data, with attention focused on the negative binomial dispersion parameter, k. A substantial literature exists on the estimation of k, but most attention has focused on datasets that are not highly overdispersed (i.e., those with k≥1), and the accuracy of confidence intervals estimated for k is typically not explored. METHODOLOGY: This article presents a simulation study exploring the bias, precision, and confidence interval coverage of maximum-likelihood estimates of k from highly overdispersed distributions. In addition to exploring small-sample bias on negative binomial estimates, the study addresses estimation from datasets influenced by two types of event under-counting, and from disease transmission data subject to selection bias for successful outbreaks. CONCLUSIONS: Results show that maximum likelihood estimates of k can be biased upward by small sample size or under-reporting of zero-class events, but are not biased downward by any of the factors considered. Confidence intervals estimated from the asymptotic sampling variance tend to exhibit coverage below the nominal level, with overestimates of k comprising the great majority of coverage errors. Estimation from outbreak datasets does not increase the bias of k estimates, but can add significant upward bias to estimates of the mean. Because k varies inversely with the degree of overdispersion, these findings show that overestimation of the degree of overdispersion is very rare for these datasets

Dispelling urban myths about default uncertainty factors in chemical risk assessment - Sufficient protection against mixture effects?

© 2013 Martin et al.; licensee BioMed Central LtdThis article has been made available through the Brunel Open Access Publishing Fund.Assessing the detrimental health effects of chemicals requires the extrapolation of experimental data in animals to human populations. This is achieved by applying a default uncertainty factor of 100 to doses not found to be associated with observable effects in laboratory animals. It is commonly assumed that the toxicokinetic and toxicodynamic sub-components of this default uncertainty factor represent worst-case scenarios and that the multiplication of those components yields conservative estimates of safe levels for humans. It is sometimes claimed that this conservatism also offers adequate protection from mixture effects. By analysing the evolution of uncertainty factors from a historical perspective, we expose that the default factor and its sub-components are intended to represent adequate rather than worst-case scenarios. The intention of using assessment factors for mixture effects was abandoned thirty years ago. It is also often ignored that the conservatism (or otherwise) of uncertainty factors can only be considered in relation to a defined level of protection. A protection equivalent to an effect magnitude of 0.001-0.0001% over background incidence is generally considered acceptable. However, it is impossible to say whether this level of protection is in fact realised with the tolerable doses that are derived by employing uncertainty factors. Accordingly, it is difficult to assess whether uncertainty factors overestimate or underestimate the sensitivity differences in human populations. It is also often not appreciated that the outcome of probabilistic approaches to the multiplication of sub-factors is dependent on the choice of probability distributions. Therefore, the idea that default uncertainty factors are overly conservative worst-case scenarios which can account both for the lack of statistical power in animal experiments and protect against potential mixture effects is ill-founded. We contend that precautionary regulation should provide an incentive to generate better data and recommend adopting a pragmatic, but scientifically better founded approach to mixture risk assessment. © 2013 Martin et al.; licensee BioMed Central Ltd.Oak Foundatio

Smashing WEP in A Passive Attack

In this paper, we report extremely fast and optimised active and passive attacks against the old IEEE 802.11 wireless communication protocol WEP. This was achieved through a huge amount of theoretical and experimental analysis (capturing WiFi packets), refinement and optimisation of all the former known attacks and methodologies against RC4 stream cipher in WEP mode. We support all our claims by providing an implementation of this attack as a publicly available patch on Aircrack-ng. Our new attacks improve its success probability drastically. We adapt our theoretical analysis in Eurocrypt 2011 to real-world scenarios and we perform a slight adjustment to match the empirical observations. Our active attack, based on ARP injection, requires 22 500 packets to gain success probability of 50% against a 104-bit WEP key, using Aircrack-ng in non-interactive mode. It runs in less than 5 seconds on an off-the-shelf PC. Using the same number of packets, Aicrack-ng yields around 3% success rate. Furthermore, we describe very fast passive only attacks by just eavesdropping TCP/IPv4 packets in a WiFi communication. Our passive attack requires 27 500 packets. This is much less than the number of packets Aircrack-ng requires in active mode (around 37 500), which is a huge improvement.We believe that our analysis brings on further insight to the security of RC4

Optimized low-dose combinatorial drug treatment boosts selectivity and efficacy of colorectal carcinoma treatment.

The current standard of care for colorectal cancer (CRC) is a combination of chemotherapeutics, often supplemented with targeted biological drugs. An urgent need exists for improved drug efficacy and minimized side effects, especially at late-stage disease. We employed the phenotypically driven therapeutically guided multidrug optimization (TGMO) technology to identify optimized drug combinations (ODCs) in CRC. We identified low-dose synergistic and selective ODCs for a panel of six human CRC cell lines also active in heterotypic 3D co-culture models. Transcriptome sequencing and phosphoproteome analyses showed that the mechanisms of action of these ODCs converged toward MAP kinase signaling and cell cycle inhibition. Two cell-specific ODCs were translated to in vivo mouse models. The ODCs reduced tumor growth by ~80%, outperforming standard chemotherapy (FOLFOX). No toxicity was observed for the ODCs, while significant side effects were induced in the group treated with FOLFOX therapy. Identified ODCs demonstrated significantly enhanced bioavailability of the individual components. Finally, ODCs were also active in primary cells from CRC patient tumor tissues. Taken together, we show that the TGMO technology efficiently identifies selective and potent low-dose drug combinations, optimized regardless of tumor mutation status, outperforming conventional chemotherapy

Nationwide Investigation of the Pyrethroid Susceptibility of Mosquito Larvae Collected from Used Tires in Vietnam

Pyrethroid resistance is envisioned to be a major problem for the vector control program since, at present, there are no suitable chemical substitutes for pyrethroids. Cross-resistance to knockdown agents, which are mainly used in mosquito coils and related products as spatial repellents, is the most serious concern. Since cross-resistance is a global phenomenon, we have started to monitor the distribution of mosquito resistance to pyrethroids. The first pilot study was carried out in Vietnam. We periodically drove along the national road from the north end to the Mekong Delta in Vietnam and collected mosquito larvae from used tires. Simplified susceptibility tests were performed using the fourth instar larvae of Aedes aegypti, Aedes albopictus, and Culex quinquefasciatus. Compared with the other species, Ae. aegypti demonstrated the most prominent reduction in susceptibility. For Ae. aegypti, significant increases in the susceptibility indices with a decrease in the latitude of collection points were observed, indicating that the susceptibility of Ae. aegypti against d-allethrin was lower in the southern part, including mountainous areas, as compared to that in the northern part of Vietnam. There was a significant correlation between the susceptibility indices in Ae. aegypti and the sum of annual pyrethroid use for malaria control (1998–2002). This might explain that the use of pyrethroids as residual treatment inside houses and pyrethroid-impregnated bed nets for malaria control is attributable to low pyrethroid susceptibility in Ae. aegypti. Such insecticide treatment appeared to have been intensively administered in the interior and along the periphery of human habitation areas where, incidentally, the breeding and resting sites of Ae. aegypti are located. This might account for the strong selection pressure toward Ae. aegypti and not Ae. albopictus

Inhibition of Ion Channels and Heart Beat in Drosophila by Selective COX-2 Inhibitor SC-791

Recent findings suggest that modulation of ion channels might be implicated in some of the clinical effects of coxibs, selective inhibitors of cyclooxygenase-2 (COX-2). Celecoxib and its inactive analog 2,5-dimethyl-celecoxib, but not rofecoxib, can suppress or augment ionic currents and alter functioning of neurons and myocytes. To better understand these unexpected effects, we have recently investigated the mechanism of inhibition of human Kv2.1 channels by a highly selective COX-2 inhibitor SC-791. In this study we have further explored the SC-791 action on ion channels and heartbeat in Drosophila, which lacks cyclooxygenases and thus can serve as a convenient model to study COX-2-independent mechanisms of coxibs. Using intracellular recordings in combination with a pharmacological approach and utilizing available Drosophila mutants, we found that SC-791 inhibited voltage-activated K+ and L-type Ca2+ channels in larval body-wall muscles and reduced heart rate in a concentration-dependent manner. Unlike celecoxib and several other K+ channel blockers, SC-791 did not induce arrhythmia. Instead, application of SC-791 resulted in a dramatic slowing of contractions and, at higher concentrations, in progressively weaker contractions with gradual cessation of heartbeat. Isradipine, a selective blocker of L-type Ca2+ channels, showed a similar pattern of heart arrest, though no prolongation of contractions was observed. Ryanodine was the only channel modulating compound of those tested additionally that was capable of slowing contractions. Like SC-791, ryanodine reduced heart rate without arrhythmia. However, it could not stop heartbeat completely even at 500 µM, the highest concentration used. The magnitude of heart rate reduction, when SC-791 and ryanodine were applied together, was smaller than expected for independent mechanisms, raising the possibility that SC-791 might be interfering with excitation-contraction coupling in Drosophila heart