996 resultados para damage-released pheromone
Resumo:
Reactive oxygen species are generated during ischaemia-reperfusion of tissue. Oxidation of thymidine by hydroxyl radicals (HO) leads to the formation of 5,6-dihydroxy-5,6-dihydrothymidine (thymidine glycol). Thymidine glycol is excreted in urine and can be used as biomarker of oxidative DNA damage. Time dependent changes in urinary excretion rates of thymidine glycol were determined in six patients after kidney transplantation and in six healthy controls. A new analytical method was developed involving affinity chromatography and subsequent reverse-phase high-performance liquid chromatography (RP-HPLC) with a post-column chemical reaction detector and endpoint fluorescence detection. The detection limit of this fluorimetric assay was 1.6 ng thymidine glycol per ml urine, which corresponds to about half of the physiological excretion level in healthy control persons. After kidney transplantation the urinary excretion rate of thymidine glycol increased gradually reaching a maximum around 48 h. The excretion rate remained elevated until the end of the observation period of 10 days. Severe proteinuria with an excretion rate of up to 7.2 g of total protein per mmol creatinine was also observed immediately after transplantation and declined within the first 24 h of allograft function (0.35 + 0.26 g/mmol creatinine). The protein excretion pattern, based on separation of urinary proteins on sodium dodecyl sulphate-polyacrylamide gel electrophorosis (SDS-PAGE), as well as excretion of individual biomarker proteins, indicated nonselective glomerular and tubular damage. The increased excretion of thymidine glycol after kidney transplantation may be explained by ischaemia-reperfusion induced oxidative DNA damage of the transplanted kidney.
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Purpose: The therapeutic ratio for ionising radiation treatment of tumour is a trade-off between normal tissue side-effects and tumour control. Application of a radioprotector to normal tissue can reduce side-effects. Here we study the effects of a new radioprotector on the cellular response to radiation. Methylproamine is a DNA-binding radioprotector which, on the basis of published pulse radiolysis studies, acts by repair of transient radiation-induced oxidative species on DNA. To substantiate this hypothesis, we studied protection by methylproamine at both clonogenic survival and radiation-induced DNA damage, assessed by γH2AX (histone 2AX phosphorylation at serine 139) focus formation endpoints. Materials and methods: The human keratinocyte cell line FEP1811 was used to study clonogenic survival and yield of γH2AX foci following irradiation (137Cs γ-rays) of cells exposed to various concentrations of methylproamine. Uptake of methylproamine into cell nuclei was measured in parallel. Results: The extent of radioprotection at the clonogenic survival endpoint increased with methylproamine concentration up to a maximum dose modification factor (DMF) of 2.0 at 10 μM. At least 0.1 fmole/nucleus of methylproamine is required to achieve a substantial level of radioprotection (DMF of 1.3) with maximum protection (DMF of 2.0) achieved at 0.23 fmole/nucleus. The γH2AX focus yield per cell nucleus 45 min after irradiation decreased with drug concentration with a DMF of 2.5 at 10 μM. Conclusions: These results are consistent with the hypothesis that radioprotection by methylproamine is mediated by attenuation of the extent of initial DNA damage.
Resumo:
Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.
Resumo:
This report presents observations, findings, and recommendations from an engineering reconnaissance trip following the May 20th, 2013 tornado that struck Moore, Oklahoma. A team of faculty, research scientists, professional engineers, and civil engineering students were tasked with investigating and documenting the performance of critical facility buildings and residences, (IBC Occupancy Category II, III, and IV), in Moore, OK. The Enhanced Fujita (EF) 5 tornado created a 17-mile long damage swath destroying over 12,000 buildings and killing 24 people. The total economic loss from this single event was estimated at $3 billion. The May 20th tornado was the third major tornado to hit Moore in the previous 15 years.
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We performed a contingent valuation survey to elicit the opportunity cost of bed-days consumed by healthcare-associated infections in 11 European hospitals. The opportunity cost of a bed-day was significantly lower than the accounting cost; median values were i72 and i929, respectively (P ! .001). Accounting methods overestimate the opportunity cost of bed-days...
Resumo:
Structural damage detection using modal strain energy (MSE) is one of the most efficient and reliable structural health monitoring techniques. However, some of the existing MSE methods have been validated for special types of structures such as beams or steel truss bridges which demands improving the available methods. The purpose of this study is to improve an efficient modal strain energy method to detect and quantify the damage in complex structures at early stage of formation. In this paper, a modal strain energy method was mathematically developed and then numerically applied to a fixed-end beam and a three-story frame including single and multiple damage scenarios in absence and presence of up to five per cent noise. For each damage scenario, all mode shapes and natural frequencies of intact structures and the first five mode shapes of assumed damaged structures were obtained using STRAND7. The derived mode shapes of each intact and damaged structure at any damage scenario were then separately used in the improved formulation using MATLAB to detect the location and quantify the severity of damage as compared to those obtained from previous method. It was found that the improved method is more accurate, efficient and convergent than its predecessors. The outcomes of this study can be safely and inexpensively used for structural health monitoring to minimize the loss of lives and property by identifying the unforeseen structural damages.
Resumo:
This paper presents a feasibility study on structural damage alarming and localization of long-span cable-supported bridges using multi-novelty indices formulated by monitoring-derived modal parameters. The proposed method which requires neither structural model nor damage model is applicable to structures of arbitrary complexity. With the intention to enhance the tolerance to measurement noise/uncertainty and the sensitivity to structural damage, an improved novelty index is formulated in terms of auto-associative neural networks (ANNs) where the output vector is designated to differ from the input vector while the training of the ANNs needs only the measured modal properties of the intact structure under in-service conditions. After validating the enhanced capability of the improved novelty index for structural damage alarming over the commonly configured novelty index, the performance of the improved novelty index for damage occurrence detection of large-scale bridges is examined through numerical simulation studies of the suspension Tsing Ma Bridge (TMB) and the cable-stayed Ting Kau Bridge (TKB) incurred with different types of structural damage. Then the improved novelty index is extended to formulate multi-novelty indices in terms of the measured modal frequencies and incomplete modeshape components for damage region identification. The capability of the formulated multi-novelty indices for damage region identification is also examined through numerical simulations of the TMB and TKB.
Resumo:
Germline mutations in BRCA1 predispose carriers to a high incidence of breast and ovarian cancers. BRCA1 functions to maintain genomic stability through critical roles in DNA repair, cell cycle arrest and transcriptional control. A major question has been why BRCA1 loss or mutation leads to tumors mainly in estrogen-regulated tissues, given that BRCA1 has essential functions in all cell types. Here we report that estrogen and estrogen metabolites can cause DNA double strand breaks (DSB) in estrogen receptor-α negative breast cells and that BRCA1 is required to repair these DSBs to prevent metabolite-induced genomic instability. We found that BRCA1 also regulates estrogen metabolism and metabolite-mediated DNA damage by repressing the transcription of estrogen-metabolising enzymes, such as CYP1A1, in breast cells. Lastly, we used a knock-in human cell model with a heterozygous BRCA1 pathogenic mutation to show how BRCA1 haploinsufficiency affects these processes. Our findings provide pivotal new insights into why BRCA1 mutation drives the formation of tumours in estrogen-regulated tissues, despite the general role of BRCA1 in DNA repair in all cell types.
Resumo:
Scope: Coffee is among the most frequently consumed beverages. Its consumption is inversely associated to the incidence of diseases related to reactive oxygen species; the phenomenon may be due to its antioxidant properties. Our primary objective was to investigate the impact of consumption of a coffee containing high levels of chlorogenic acids on the oxidation of proteins, DNA and membrane lipids; additionally, other redox biomarkers were monitored in an intervention trial. Methods and results: The treatment group (n=36) consumed instant coffee co-extracted from green and roasted beans, whereas the control consumed water (800 mL/P/day, 5 days). A global statistical analysis of four main biomarkers selected as primary outcomes showed that the overall changes are significant. 8-Isoprostaglandin F2α in urine declined by 15.3%, 3-nitrotyrosine was decreased by 16.1%, DNA migration due to oxidized purines and pyrimidines was (not significantly) reduced in lymphocytes by 12.5 and 14.1%. Other markers such as the total antioxidant capacity were moderately increased; e.g. LDL and malondialdehyde were shifted towards a non-significant reduction. Conclusion: The oxidation of DNA, lipids and proteins associated with the incidence of various diseases and the protection against their oxidative damage may be indicative for beneficial health effects of coffee.