Determination of urinary thymidine glycol using affinity chromatography, HPLC and post-column reaction detection : a biomarker of oxidative DNA damage upon kidney transplantation

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.

Collective coverings, communal skin

Collective Coverings, Communal Skin is a large-scale site-specific installation that grows with community contributions created for the 2012 Liverpool Biennial. The work involves transforming objects used in conflict (second hand hunting and camouflage t-shirts) into objects of comfort (hula hoop rag mats) . Many of the shirts were either donated or purchased from thrift stores in Los Angeles and Liverpool. With the massive help of the Liverpool community we transformed individual t-shirts through weaving them into a communal skin that covers the existing internal architecture. There was a workshop space with instruction video, inside the installation where visitors could sit and work on patchwork body-pillows. During structured workshops I talked with the community about meditating while they weave so as to contemplate the spiritual and conceptual dimension of the project. The hula-hoop weavings grew throughout the space for the duration of the 10-week Biennial. The community contributed 770 weavings. This project was funded by the Australia Council for the Arts and FACT.

How small business advisory program delivery methods (collective learning, tailored, and practice-based approaches) affect learning and innovation

Past studies relate small business advisory program effectiveness to advisory characteristics such as advisory intensity and scope. We contribute to existing literature by seeking to identify the impact of different advisory program methods of delivery on learning and subsequent firm innovation behavior. Our research is based on a survey of 257 Australian firms completing small business advisory programs in the three years preceding the research. We explore the range of small business advisory program delivery methods in which our surveyed firms participated and, with reference to the literature on organizational learning and innovation, we analyze predictors of firms' learning ability and innovativeness based on the identified delivery methods. First, we found that business advisory programs that involved high levels of collective learning and tailored approaches enhanced firms' perceptions of their learning of critical skills or capabilities. We also found that small business advisory programs that were delivered by using practice-based approaches enhanced firms' subsequent organizational innovation. We verified this finding by testing whether firms that have participated in small business advisory services subsequently demonstrate improved behavior in terms of organizational innovativeness, when compared with matched firms that have not participated in an advisory program.

Protection by methylproamine of irradiated human keratinocytes correlates with reduction of DNA damage

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.

Pathogenesis of Fallopian tube damage caused by Chlamydia trachomatis infections

Chlamydia trachomatis is the leading cause of bacterial sexually transmitted disease worldwide resulting in 4–5 million new cases of Chlamydia annually and an estimated 100 million cases per annum. Infections of the lower female genital tract (FGT) frequently are asymptomatic so they often remain undiagnosed or untreated. If infections are either not resolved, or are left untreated, chlamydia can ascend to the upper FGT and infect the fallopian tubes (FTs) causing salpingitis that may lead to functional damage of the FTs and tubal factor infertility (TFI). Clinical observations and experimental data have indicated a role for antibodies against C. trachomatis proteins such as the 60 kDa heat-shock protein 60 (cHSP60) in the immunopathogenesis of TFI. When released from infected cells cHSP60 can induce pro-inflammatory immune responses that may functionally impair the FTs leading to fibrosis and luminal occlusion. Chlamydial pathogenesis of irreversible and permanent tubal damage is a consequence of innate and adaptive host immune responses to ongoing or repeated infections. The extracellular matrix (ECM) that is regulated by metalloproteinases (MMPs) may also be modified by chlamydial infections of the FGT. This review will highlight protective and pathogenic immune responses to ongoing and repeated chlamydial infections of the FGT. It will also present two recent hypotheses to explain mechanisms that may contribute to FT damage during a C. trachomatis infection. If Chlamydia immunopathology can be controlled it might yield a method of inducing fibrosis and thus provide a means of non-surgical permanent contraception for women.

Structural damage detection method using frequency response functions

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.

Tornado Damage Assessment in the aftermath of the May 20th 2013 Moore Oklahoma Tornado

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.

"I take care of my own" : a field study on how leadership handles conflict between individual and collective incentives

From the early literature on the role of firm managers (Alchian and Demsetz 1972) to the industrial organisation on contracts and mechanism design (Laont and Martimort 2009), economists have given a lot of attention to find solutions to the imperfect alignment between individuals' incentives and an organisation's collective goals (Prendergast 1999). In that literature a key role of managers is to monitor individuals to reward behaviour aligned with the collective goals and reduce sub- optimal behaviour, such as shirking. How- ever, another strand of literature, since Akerlof (1982), has put forward a vision of reciprocal behaviour between an organisation's leadership and its members: gifts (high wages, recognition) from the organisation are reciprocated by high effort from the members of the organisation. By rewarding individual members (rather than strictly monitoring them), organisations may benefit from greater effort and cohesion. Experimental research in organizational economics has provided mixed results suggesting that agents do react to personal incentives but also that reciprocal behaviour can play a substantial role (Camerer and Weber 2012).

Quantifying uncertainty in parameter estimates for stochastic models of collective cell spreading using approximate Bayesian computation

Wound healing and tumour growth involve collective cell spreading, which is driven by individual motility and proliferation events within a population of cells. Mathematical models are often used to interpret experimental data and to estimate the parameters so that predictions can be made. Existing methods for parameter estimation typically assume that these parameters are constants and often ignore any uncertainty in the estimated values. We use approximate Bayesian computation (ABC) to estimate the cell diffusivity, D, and the cell proliferation rate, λ, from a discrete model of collective cell spreading, and we quantify the uncertainty associated with these estimates using Bayesian inference. We use a detailed experimental data set describing the collective cell spreading of 3T3 fibroblast cells. The ABC analysis is conducted for different combinations of initial cell densities and experimental times in two separate scenarios: (i) where collective cell spreading is driven by cell motility alone, and (ii) where collective cell spreading is driven by combined cell motility and cell proliferation. We find that D can be estimated precisely, with a small coefficient of variation (CV) of 2–6%. Our results indicate that D appears to depend on the experimental time, which is a feature that has been previously overlooked. Assuming that the values of D are the same in both experimental scenarios, we use the information about D from the first experimental scenario to obtain reasonably precise estimates of λ, with a CV between 4 and 12%. Our estimates of D and λ are consistent with previously reported values; however, our method is based on a straightforward measurement of the position of the leading edge whereas previous approaches have involved expensive cell counting techniques. Additional insights gained using a fully Bayesian approach justify the computational cost, especially since it allows us to accommodate information from different experiments in a principled way.

Collective futures: How projections about the future of society are related to actions and attitudes supporting social change

We identified the active ingredients in people’s visions of society’s future (“collective futures”) that could drive political behavior in the present. In eight studies (N = 595), people imagined society in 2050 where climate change was mitigated (Study 1), abortion laws relaxed (Study 2), marijuana legalized (Study 3), or the power of different religious groups had increased (Studies 4-8). Participants rated how this future society would differ from today in terms of societal-level dysfunction and development (e.g., crime, inequality, education, technology), people’s character (warmth, competence, morality), and their values (e.g., conservation, self-transcendence). These measures were related to present-day attitudes/intentions that would promote/prevent this future (e.g., act on climate change, vote for a Muslim politician). A projection about benevolence in society (i.e., warmth/morality of people’s character) was the only dimension consistently and uniquely associated with present-day attitudes and intentions across contexts. Implications for social change theories, political communication, and policy design are discussed.

An improved modal strain energy method for structural damage detection, 2D simulation

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.

Structural damage alarming and localization of cable-supported bridges using multi-novelty indices: A feasibility study

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.