988 resultados para Kevin Reiss


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Cellular response to radiation damage is made by a complex network of pathways and feedback loops whose spatiotemporal organization is still unclear despite its decisive role in determining the fate of the damaged cell. The single-cell approach and the high spatial resolution offered by microbeams provide the perfect tool to study and quantify the dynamic processes associated with the induction and repair of DNA damage. The soft X-ray microbeam has been used to follow the development of radiation induced foci in live cells by monitoring their size and intensity as a function of dose and time using yellow fluorescent protein (YFP) tagging techniques. Preliminary data indicate a delayed and linear rising of the intensity signal indicating a slow kinetic for the accumulation of DNA repair protein 53BP1. A slow and limited foci diffusion has also been observed. Further investigations are required to assess whatever such diffusion is consistent with a random walk pattern or if it is the result of a more structured lesion processing phenomenon. In conclusion, our data indicates that the use of microbeams coupled to live cell microscopy represent a sophisticated approach for visualizing and quantifying the dynamics changes of DNA proteins at the damaged sites.

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Radiotherapy employs ionizing radiation to induce lethal DNA lesions in cancer cells while minimizing damage to healthy tissues. Due to their pattern of energy deposition, better therapeutic outcomes can, in theory, be achieved with ions compared to photons. Antiprotons have been proposed to offer a further enhancement due to their annihilation at the end of the path. The work presented here aimed to establish and validate an experimental procedure for the quantification of plasmid and genomic DNA damage resulting from antiproton exposure. Immunocytochemistry was used to assess DNA damage in directly and indirectly exposed human fibroblasts irradiated in both plateau and Bragg peak regions of a 126 MeV antiproton beam at CERN. Cells were stained post irradiation with an anti-gamma-H2AX antibody. Quantification of the gamma-H2AX foci-dose relationship is consistent with a linear increase in the Bragg peak region. A qualitative analysis of the foci detected in the Bragg peak and plateau region indicates significant differences highlighting the different severity of DNA lesions produced along the particle path. Irradiation of desalted plasmid DNA with 5 Gy antiprotons at the Bragg peak resulted in a significant portion of linear plasmid in the resultant solution.

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Gold nanoparticles (GNPs) are being proposed as contrast agents to enhance X-ray imaging and radiotherapy, seeking to take advantage of the increased X-ray absorption of gold compared to soft tissue. However, there is a great discrepancy between physically predicted increases in X-ray energy deposition and experimentally observed increases in cell killing. In this work, we present the first calculations which take into account the structure of energy deposition in the nanoscale vicinity of GNPs and relate this to biological outcomes, and show for the first time good agreement with experimentally observed cell killing by the combination of X-rays and GNPs. These results are not only relevant to radiotherapy, but also have implications for applications of heavy atom nanoparticles in biological settings or where human exposure is possible because the localised energy deposition high-lighted by these results may cause complex DNA damage, leading to mutation and carcinogenesis.

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In this preliminary case study, we investigate how inconsistency in a network intrusion detection rule set can be measured. To achieve this, we first examine the structure of these rules which incorporate regular expression (Regex) pattern matching. We then identify primitive elements in these rules in order to translate the rules into their (equivalent) logical forms and to establish connections between them. Additional rules from background knowledge are also introduced to make the correlations among rules more explicit. Finally, we measure the degree of inconsistency in formulae of such a rule set (using the Scoring function, Shapley inconsistency values and Blame measure for prioritized knowledge) and compare the informativeness of these measures. We conclude that such measures are useful for the network intrusion domain assuming that incorporating domain knowledge for correlation of rules is feasible.

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A recently published genome-wide association study (GWAS) of late-onset Alzheimer's disease (LOAD) revealed genome-wide significant association of variants in or near MS4A4A, CD2AP, EPHA1 and CD33. Meta-analyses of this and a previously published GWAS revealed significant association at ABCA7 and MS4A, independent evidence for association of CD2AP, CD33 and EPHA1 and an opposing yet significant association of a variant near ARID5B. In this study, we genotyped five variants (in or near CD2AP, EPHA1, ARID5B, and CD33) in a large (2,634 LOAD, 4,201 controls), independent dataset comprising six case-control series from the USA and Europe. We performed meta-analyses of the association of these variants with LOAD and tested for association using logistic regression adjusted by age-at-diagnosis, gender, and APOE e4 dosage.

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We sought to investigate the contribution of extended runs of homozygosity in a genome-wide association dataset of 1,955 Alzheimer's disease cases and 955 elderly screened controls genotyped for 529,205 autosomal single nucleotide polymorphisms. Tracts of homozygosity may mark regions inherited from a common ancestor and could reflect disease loci if observed more frequently in cases than controls. We found no excess of homozygous tracts in Alzheimer's disease cases compared to controls and no individual run of homozygosity showed association to Alzheimer's disease.

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All TAP micro-reactor configurations contain inert particles which are used so that the catalyst zone can be maintained under isothermal conditions. Even on

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In this preliminary study, we investigate how inconsistency in a network intrusion detection rule set can be measured. To achieve this, we first examine the structure of these rules which are based on Snort and incorporate regular expression (Regex) pattern matching. We then identify primitive elements in these rules in order to translate the rules into their (equivalent) logical forms and to establish connections between them. Additional rules from background knowledge are also introduced to make the correlations among rules more explicit. We measure the degree of inconsistency in formulae of such a rule set (using the Scoring function, Shapley inconsistency values and Blame measure for prioritized knowledge) and compare the informativeness of these measures. Finally, we propose a new measure of inconsistency for prioritized knowledge which incorporates the normalized number of atoms in a language involved in inconsistency to provide a deeper inspection of inconsistent formulae. We conclude that such measures are useful for the network intrusion domain assuming that introducing expert knowledge for correlation of rules is feasible.

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Background: The world's oceans are home to a diverse array of microbial life whose metabolic activity helps to drive the earth's biogeochemical cycles. Metagenomic analysis has revolutionized our access to these communities, providing a system-scale perspective of microbial community interactions. However, while metagenome sequencing can provide useful estimates of the relative change in abundance of specific genes and taxa between environments or over time, this does not investigate the relative changes in the production or consumption of different metabolites.
Results: We propose a methodology, Predicted Relative Metabolic Turnover (PRMT) that defines and enables exploration of metabolite-space inferred from the metagenome. Our analysis of metagenomic data from a time-series study in the Western English Channel demonstrated considerable correlations between predicted relative metabolic turnover and seasonal changes in abundance of measured environmental parameters as well as with observed seasonal changes in bacterial population structure.
Conclusions: The PRMT method was successfully applied to metagenomic data to explore the Western English Channel microbial metabalome to generate specific, biologically testable hypotheses. Generated hypotheses linked organic phosphate utilization to Gammaproteobactaria, Plantcomycetes, and Betaproteobacteria, chitin degradation to Actinomycetes, and potential small molecule biosynthesis pathways for Lentisphaerae, Chlamydiae, and Crenarchaeota. The PRMT method can be applied as a general tool for the analysis of additional metagenomic or transcriptomic datasets.

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Stem cells of normal mammalian tissues are defined as nonspecialized cells that have two critical properties: (a) the ability to renew themselves through cell division and (b) the potency to differentiate into other cell types. Therefore, they play a crucial role in development and in tissue homeostasis during adult life. Being long-lived, they can be the targets of environmental carcinogens leading to the accumulation of consecutive genetic changes. Hence, the genome of stem cells must be exceptionally well protected, and several protective mechanisms have evolved to ensure the genetic integrity of the stem cell compartment in any given tissue. Ionizing radiation exposure can disrupt tissue homeostasis both through the induction of cell killing/depletion of radiosensitive stem cells, leading to loss of tissue functionality and by genotoxic damage, increasing overall risk of cancer. We will review the current knowledge about radiation effects in adult stem cells of specific normal tissues, including skin, breast, and brain, examine parallels, as well as differences with cancer stem cells, and discuss the relevance of stem cell effects to radiation risk and radiotherapy. STEM CELLS 2011;29:1315-1321

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Abdominal aortic aneurysm (AAA) is a common cause of morbidity and mortality and has a significant heritability. We carried out a genome-wide association discovery study of 1866 patients with AAA and 5435 controls and replication of promising signals (lead SNP with a p value < 1 × 10 -5) in 2871 additional cases and 32,687 controls and performed further follow-up in 1491 AAA and 11,060 controls. In the discovery study, nine loci demonstrated association with AAA (p < 1 × 10 -5). In the replication sample, the lead SNP at one of these loci, rs1466535, located within intron 1 of low-density-lipoprotein receptor-related protein 1 (LRP1) demonstrated significant association (p = 0.0042). We confirmed the association of rs1466535 and AAA in our follow-up study (p = 0.035). In a combined analysis (6228 AAA and 49182 controls), rs1466535 had a consistent effect size and direction in all sample sets (combined p = 4.52 × 10 -10, odds ratio 1.15 [1.10-1.21]). No associations were seen for either rs1466535 or the 12q13.3 locus in independent association studies of coronary artery disease, blood pressure, diabetes, or hyperlipidaemia, suggesting that this locus is specific to AAA. Gene-expression studies demonstrated a trend toward increased LRP1 expression for the rs1466535 CC genotype in arterial tissues; there was a significant (p = 0.029) 1.19-fold (1.04-1.36) increase in LRP1 expression in CC homozygotes compared to TT homozygotes in aortic adventitia. Functional studies demonstrated that rs1466535 might alter a SREBP-1 binding site and influence enhancer activity at the locus. In conclusion, this study has identified a biologically plausible genetic variant associated specifically with AAA, and we suggest that this variant has a possible functional role in LRP1 expression.