Environmental factors controlling temporal and spatial variability in the soil-atmosphere exchange of CO2, CH4 and N2O from an Australian subtropical rainforest

The temporal variations in CO2, CH4 and N2O fluxes were measured over two consecutive years from February 2007 to March 2009 from a subtropical rainforest in south-eastern Queensland, Australia, using an automated sampling system. A concurrent study using an additional 30 manual chambers examined the spatial variability of emissions distributed across three nearby remnant rainforest sites with similar vegetation and climatic conditions. Interannual variation in fluxes of all gases over the 2 years was minimal, despite large discrepancies in rainfall, whereas a pronounced seasonal variation could only be observed for CO2 fluxes. High infiltration, drainage and subsequent high soil aeration under the rainforest limited N2O loss while promoting substantial CH4 uptake. The average annual N2O loss of 0.5 ± 0.1 kg N2O-N ha−1 over the 2-year measurement period was at the lower end of reported fluxes from rainforest soils. The rainforest soil functioned as a sink for atmospheric CH4 throughout the entire 2-year period, despite periods of substantial rainfall. A clear linear correlation between soil moisture and CH4 uptake was found. Rates of uptake ranged from greater than 15 g CH4-C ha−1 day−1 during extended dry periods to less than 2–5 g CH4-C ha−1 day−1 when soil water content was high. The calculated annual CH4 uptake at the site was 3.65 kg CH4-C ha−1 yr−1. This is amongst the highest reported for rainforest systems, reiterating the ability of aerated subtropical rainforests to act as substantial sinks of CH4. The spatial study showed N2O fluxes almost eight times higher, and CH4 uptake reduced by over one-third, as clay content of the rainforest soil increased from 12% to more than 23%. This demonstrates that for some rainforest ecosystems, soil texture and related water infiltration and drainage capacity constraints may play a more important role in controlling fluxes than either vegetation or seasonal variability

Exercise, appetite and weight management: understanding the compensatory responses in eating behaviour and how they contribute to variability in exercise-induced weight loss

Does exercise promote weight loss? One of the key problems with studies assessing the efficacy of exercise as a method of weight management and obesityis that mean data are presented and the individual variability in response is overlooked. Recent data have highlighted the need to demonstrate and characterise the individual variability in response to exercise. Do people who exercise compensate for the increase in energy expenditure via compensatory increases in hunger and food intake? The authors address the physiological, psychological and behavioural factors potentially involved in the relationship between exercise and appetite, and identify the research questions that remain unanswered. A negative consequence of the phenomena of individual variability and compensatory responses has been the focus on those who lose little weight in response to exercise; this has been used unreasonably as evidence to suggest that exercise is a futile method of controlling weight and managing obesity. Most of the evidence suggests that exercise is useful for improving body composition and health. For example, when exercise-induced mean weight loss is <1.0 kg, significant improvements in aerobic capacity (+6.3 ml/kg/min), systolic (−6.00 mm Hg) and diastolic (−3.9 mm Hg) blood pressure, waist circumference (−3.7 cm) and positive mood still occur. However, people will vary in their responses to exercise; understanding and characterising this variability will help tailor weight loss strategies to suit individuals.

Induction of antioxidative Nrf2 gene transcription by coffee in humans : depending on genotype?

The Nrf2/ARE pathway is a major cellular defense mechanism that prevents damage by reactive oxygen species through induction of antioxidative phase II enzymes. However, the activity of the Nrf2/ARE system is not uniform with variability in response presumed to be dependent on the Nrf2 genotype. We recently completed a pilot human coffee intervention trial with healthy humans, where large interindividual differences in the antioxidative response to the study coffee were examined. Here, we address the question whether differences in the modulation of Nrf2 gene transcription, assessed as an induction of Nrf2 gene transcription by Q-PCR, might be correlated with specific Nrf2 genotypes. To date, nine single nucleotide polymorphisms (SNPs) have been identified in the Nrf2 (NFE2L2) gene. Two of these, the -617C/A and -651G/A SNPs are located within the promoter region and have previously been reported to influence the activity of the Nrf2/ARE pathway by reducing Nrf2 transcriptional activity. Sequencing of the critical Nrf2 gene promoter region not only confirmed the existence of these SNPs within the participants of the trial at the expected frequency (33% carrying the -617C/A, 17% the -651G/A and 56% the -653A/G SNP) but also indicated reduced Nrf2 gene transcription associated with a normal diet if the SNPs at position -617, -651 or -653 were present. Of note, the data also indicated the study coffee increased Nrf2 gene transcription even in SNP carriers. This further highlights the relevance of genotype-dependent induction of Nrf2 gene transcription that appears to be largely influenced by dietary factors.

Gene expression analysis of diagnostic biopsies predicts pathological response to neoadjuvant chemoradiotherapy of esophageal cancer

OBJECTIVE: This study explored gene expression differences in predicting response to chemoradiotherapy in esophageal cancer. PURPOSE:: A major pathological response to neoadjuvant chemoradiation is observed in about 40% of esophageal cancer patients and is associated with favorable outcomes. However, patients with tumors of similar histology, differentiation, and stage can have vastly different responses to the same neoadjuvant therapy. This dichotomy may be due to differences in the molecular genetic environment of the tumor cells. BACKGROUND DATA: Diagnostic biopsies were obtained from a training cohort of esophageal cancer patients (13), and extracted RNA was hybridized to genome expression microarrays. The resulting gene expression data was verified by qRT-PCR. In a larger, independent validation cohort (27), we examined differential gene expression by qRT-PCR. The ability of differentially-regulated genes to predict response to therapy was assessed in a multivariate leave-one-out cross-validation model. RESULTS: Although 411 genes were differentially expressed between normal and tumor tissue, only 103 genes were altered between responder and non-responder tumor; and 67 genes differentially expressed >2-fold. These included genes previously reported in esophageal cancer and a number of novel genes. In the validation cohort, 8 of 12 selected genes were significantly different between the response groups. In the predictive model, 5 of 8 genes could predict response to therapy with 95% accuracy in a subset (74%) of patients. CONCLUSIONS: This study has identified a gene microarray pattern and a set of genes associated with response to neoadjuvant chemoradiation in esophageal cancer. The potential of these genes as biomarkers of response to treatment warrants further investigation. Copyright © 2009 by Lippincott Williams & Wilkins.

A metastatic neuroendocrine anaplastic small cell tumor in a patient with multiple endocrine neoplasia type 1 syndrome : assessment of disease status and response to doxorubicin, cyclophosphamide, etoposide chemotherapy through scintigraphic imaging with 111In-pentetreotide

Extrapulmonary small cell and small cell neuroendocrine tumors of unknown primary site are, in general, aggressive neoplasms with a short median survival. Like small cell lung cancer (SCLC), they often are responsive to chemotherapy and radiotherapy. Small cell lung cancer and well differentiated neuroendocrine carcinomas of the gastrointestinal tract and pancreas tend to express somatostatin receptors. These tumors may be localized in patients by scintigraphic imaging using radiolabeled somatostatin analogues. A patient with an anaplastic neuroendocrine small cell tumor arising on a background of multiple endocrine neoplasia type 1 syndrome is reported. The patient had a known large pancreatic gastrinoma and previously treated parathyroid adenopathy. At presentation, there was small cell cancer throughout the liver and skeleton. Imaging with a radiolabeled somatostatin analogue, 111In- pentetreotide (Mallinckrodt Medical B. V., Petten, Holland), revealed all sites of disease detected by routine biochemical and radiologic methods. After six cycles of chemotherapy with doxorubicin, cyclophosphamide, and etoposide, there was almost complete clearance of the metastatic disease. 111In-pentetreotide scintigraphy revealed uptake consistent with small areas of residual disease in the liver, the abdomen (in mesenteric lymph nodes), and posterior thorax (in a rib). The primary gastrinoma present before the onset of the anaplastic small cell cancer showed no evidence of response to the treatment. The patient remained well for 1 year and then relapsed with brain, lung, liver, and skeletal metastases. Despite an initial response to salvage radiotherapy and chemotherapy with carboplatin and dacarbazine, the patient died 6 months later.

Influence of pollutant build-up on variability in wash-off from urban road surfaces

Variability in the pollutant wash-off process is a concept which needs to be understood in-depth in order to better assess the outcomes of stormwater quality models, and thereby strengthen stormwater pollution mitigation strategies. Current knowledge about the wash-off process does not extend to a clear understanding of the influence of the initially available pollutant build-up on the variability of the pollutant wash-off load and composition. Consequently, pollutant wash-off process variability is poorly characterised in stormwater quality models, which can result in inaccurate stormwater quality predictions. Mathematical simulation of particulate wash-off from three urban road surfaces confirmed that the wash-off load of particle size fractions <150µm and >150µm after a storm event vary with the build-up of the respective particle size fractions available at the beginning of the storm event. Furthermore, pollutant load and composition associated with the initially available build-up of <150µm particles predominantly influence the variability in washed-off pollutant load and composition. The influence of the build-up of pollutants associated with >150µm particles on wash-off process variability is significant only for relatively shorter duration storm events.

Population of computational rabbit-specific ventricular action potential models for investigating sources of variability in cellular repolarisation

Variability is observed at all levels of cardiac electrophysiology. Yet, the underlying causes and importance of this variability are generally unknown, and difficult to investigate with current experimental techniques. The aim of the present study was to generate populations of computational ventricular action potential models that reproduce experimentally observed intercellular variability of repolarisation (represented by action potential duration) and to identify its potential causes. A systematic exploration of the effects of simultaneously varying the magnitude of six transmembrane current conductances (transient outward, rapid and slow delayed rectifier K(+), inward rectifying K(+), L-type Ca(2+), and Na(+)/K(+) pump currents) in two rabbit-specific ventricular action potential models (Shannon et al. and Mahajan et al.) at multiple cycle lengths (400, 600, 1,000 ms) was performed. This was accomplished with distributed computing software specialised for multi-dimensional parameter sweeps and grid execution. An initial population of 15,625 parameter sets was generated for both models at each cycle length. Action potential durations of these populations were compared to experimentally derived ranges for rabbit ventricular myocytes. 1,352 parameter sets for the Shannon model and 779 parameter sets for the Mahajan model yielded action potential duration within the experimental range, demonstrating that a wide array of ionic conductance values can be used to simulate a physiological rabbit ventricular action potential. Furthermore, by using clutter-based dimension reordering, a technique that allows visualisation of multi-dimensional spaces in two dimensions, the interaction of current conductances and their relative importance to the ventricular action potential at different cycle lengths were revealed. Overall, this work represents an important step towards a better understanding of the role that variability in current conductances may play in experimentally observed intercellular variability of rabbit ventricular action potential repolarisation.

Sexual selection in a tropical fruit fly : role of a plant derived chemical in mate choice

The specific mechanisms by which selective pressures affect individuals are often difficult to resolve. In tephritid fruit flies, males respond strongly and positively to certain plant derived chemicals. Sexual selection by female choice has been hypothesized as the mechanism driving this behaviour in certain species, as females preferentially mate with males that have fed on these chemicals. This hypothesis is, to date, based on studies of only very few species and its generality is largely untested. We tested the hypothesis on different spatial scales (small cage and seminatural field-cage) using the monophagous fruit fly, Bactrocera cacuminata. This species is known to respond to methyl eugenol (ME), a chemical found in many plant species and one upon which previous studies have focused. Contrary to expectation, no obvious female choice was apparent in selecting ME-fed males over unfed males as measured by the number of matings achieved over time, copulation duration, or time of copulation initiation. However, the number of matings achieved by ME-fed males was significantly greater than unfed males 16 and 32 days after exposure to ME in small cages (but not in a field-cage). This delayed advantage suggests that ME may not influence the pheromone system of B. cacuminata but may have other consequences, acting on some other fitness consequence (e.g., enhancement of physiology or survival) of male exposure to these chemicals. We discuss the ecological and evolutionary implications of our findings to explore alternate hypotheses to explain the patterns of response of dacine fruit flies to specific plant-derived chemicals.

Strategy for the development of investment decision-making framework for road asset management for queensland department of main roads

The aim of this project is to develop a systematic investment decision-making framework for infrastructure asset management by incorporation economic justification, social and environmental consideration in the decision-making process. This project assesses the factors that are expected to provide significant impacts on the variability of expenditures. A procedure for assessing risk and reliability for project investment appraisals will be developed. The project investigates public perception, social and environmental impacts on road infrastructure investment. This research will contribute to the debate about how important social and environmental issues should be incorporated into the investment decision-making process for infrastructure asset management.

Whole of life cycle cost analysis in bridge rehabilitation

The report presents a methodology for whole of life cycle cost analysis of alternative treatment options for bridge structures, which require rehabilitation. The methodology has been developed after a review of current methods and establishing that a life cycle analysis based on a probabilistic risk approach has many advantages including the essential ability to consider variability of input parameters. The input parameters for the analysis are identified as initial cost, maintenance, monitoring and repair cost, user cost and failure cost. The methodology utilizes the advanced simulation technique of Monte Carlo simulation to combine a number of probability distributions to establish the distribution of whole of life cycle cost. In performing the simulation, the need for a powerful software package, which would work with spreadsheet program, has been identified. After exploring several products on the market, @RISK software has been selected for the simulation. In conclusion, the report presents a typical decision making scenario considering two alternative treatment options.

Report : review of the literature : maintenance and rehabilitation costs for roads (Risk-based Analysis)

Realistic estimates of short- and long-term (strategic) budgets for maintenance and rehabilitation of road assessment management should consider the stochastic characteristics of asset conditions of the road networks so that the overall variability of road asset data conditions is taken into account. The probability theory has been used for assessing life-cycle costs for bridge infrastructures by Kong and Frangopol (2003), Zayed et.al. (2002), Kong and Frangopol (2003), Liu and Frangopol (2004), Noortwijk and Frangopol (2004), Novick (1993). Salem 2003 cited the importance of the collection and analysis of existing data on total costs for all life-cycle phases of existing infrastructure, including bridges, road etc., and the use of realistic methods for calculating the probable useful life of these infrastructures (Salem et. al. 2003). Zayed et. al. (2002) reported conflicting results in life-cycle cost analysis using deterministic and stochastic methods. Frangopol et. al. 2001 suggested that additional research was required to develop better life-cycle models and tools to quantify risks, and benefits associated with infrastructures. It is evident from the review of the literature that there is very limited information on the methodology that uses the stochastic characteristics of asset condition data for assessing budgets/costs for road maintenance and rehabilitation (Abaza 2002, Salem et. al. 2003, Zhao, et. al. 2004). Due to this limited information in the research literature, this report will describe and summarise the methodologies presented by each publication and also suggest a methodology for the current research project funded under the Cooperative Research Centre for Construction Innovation CRC CI project no 2003-029-C.

Report : development of a methodology for assessing variation in maintenance and rehabilitation costs

In the previous research CRC CI 2001-010-C “Investment Decision Framework for Infrastructure Asset Management”, a method for assessing variation in cost estimates for road maintenance and rehabilitation was developed. The variability of pavement strength collected from a 92km national highway was used in the analysis to demonstrate the concept. Further analysis was conducted to identify critical input parameters that significantly affect the prediction of road deterioration. In addition to pavement strength, rut depth, annual traffic loading and initial roughness were found to be critical input parameters for road deterioration. This report presents a method developed to incorporate other critical parameters in the analysis, such as unit costs, which are suspected to contribute to a certain degree to cost estimate variation. Thus, the variability of unit costs will be incorporated in this analysis. Bruce Highway located in the tropical east coast of Queensland has been identified to be the network for the analysis. This report presents a step by step methodology for assessing variation in road maintenance and rehabilitation cost estimates.

Report : stochastic analysis of road asset data for maintenance cost prediction

Reliable budget/cost estimates for road maintenance and rehabilitation are subjected to uncertainties and variability in road asset condition and characteristics of road users. The CRC CI research project 2003-029-C ‘Maintenance Cost Prediction for Road’ developed a method for assessing variation and reliability in budget/cost estimates for road maintenance and rehabilitation. The method is based on probability-based reliable theory and statistical method. The next stage of the current project is to apply the developed method to predict maintenance/rehabilitation budgets/costs of large networks for strategic investment. The first task is to assess the variability of road data. This report presents initial results of the analysis in assessing the variability of road data. A case study of the analysis for dry non reactive soil is presented to demonstrate the concept in analysing the variability of road data for large road networks. In assessing the variability of road data, large road networks were categorised into categories with common characteristics according to soil and climatic conditions, pavement conditions, pavement types, surface types and annual average daily traffic. The probability distributions, statistical means, and standard deviation values of asset conditions and annual average daily traffic for each type were quantified. The probability distributions and the statistical information obtained in this analysis will be used to asset the variation and reliability in budget/cost estimates in later stage. Generally, we usually used mean values of asset data of each category as input values for investment analysis. The variability of asset data in each category is not taken into account. This analysis method demonstrated that it can be used for practical application taking into account the variability of road data in analysing large road networks for maintenance/rehabilitation investment analysis.

Identification of critical input variables for risk-based cost estimates for road maintenance and rehabilitation

An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

A numerical method to quantify the axial shortening of vertical elements in concrete buildings

Differential axial shortening, distortion and deformation in high rise buildings is a serious concern. They are caused by three time dependent modes of volume change; “shrinkage”, “creep” and “elastic shortening” that takes place in every concrete element during and after construction. Vertical concrete components in a high rise building are sized and designed based on their strength demand to carry gravity and lateral loads. Therefore, columns and walls are sized, shaped and reinforced differently with varying concrete grades and volume to surface area ratios. These structural components may be subjected to the detrimental effects of differential axial shortening that escalates with increasing the height of buildings. This can have an adverse impact on other structural and non-structural elements. Limited procedures are available to quantify axial shortening, and the results obtained from them differ because each procedure is based on various assumptions and limited to few parameters. All these prompt to a need to develop an accurate numerical procedure to quantify the axial shortening of concrete buildings taking into account the important time varying functions of (i) construction sequence (ii) Young’s Modulus and (iii) creep and shrinkage models associated with reinforced concrete. General assumptions are refined to minimize variability of creep and shrinkage parameters to improve accuracy of the results. Finite element techniques are used in the procedure that employs time history analysis along with compression only elements to simulate staged construction behaviour. This paper presents such a procedure and illustrates it through an example. Keywords: Differential Axial Shortening, Concrete Buildings, Creep and Shrinkage, Construction Sequence, Finite Element Method.