Effect of family relatedness on characteristics of estimated IBD probabilities in relation to precision of QTL estimates

Background: A random QTL effects model uses a function of probabilities that two alleles in the same or in different animals at a particular genomic position are identical by descent (IBD). Estimates of such IBD probabilities and therefore, modeling and estimating QTL variances, depend on marker polymorphism, strength of linkage and linkage disequilibrium of markers and QTL, and the relatedness of animals in the pedigree. The effect of relatedness of animals in a pedigree on IBD probabilities and their characteristics was examined in a simulation study. Results: The study based on nine multi-generational family structures, similar to a pedigree structure of a real dairy population, distinguished by an increased level of inbreeding from zero to 28 % across the studied population. Highest inbreeding level in the pedigree, connected with highest relatedness, was accompanied by highest IBD probabilities of two alleles at the same locus, and by lower relative variation coefficients. Profiles of correlation coefficients of IBD probabilities along the marked chromosomal segment with those at the true QTL position were steepest when the inbreeding coefficient in the pedigree was highest. Precision of estimated QTL location increased with increasing inbreeding and pedigree relatedness. A method to assess the optimum level of inbreeding for QTL detection is proposed, depending on population parameters. Conclusions: An increased overall relationship in a QTL mapping design has positive effects on precision of QTL position estimates. But the relationship of inbreeding level and the capacity for QTL detection depending on the recombination rate of QTL and adjacent informative marker is not linear. © 2010 Freyer et al., licensee BioMed Central Ltd.

The development of a new method for the determination of concentrations of carbonaceous gases using a non-dispersive infrared sensor

An analytical method for the detection of carbonaceous gases by a non-dispersive infrared sensor (NDIR) has been developed. The calibration plots of six carbonaceous gases including CO2, CH4, CO, C2H2, C2H4 and C2H6 were obtained and the reproducibility determined to verify the feasibility of this gas monitoring method. The results prove that squared correlation coefficients for the six gas measurements are greater than 0.999. The reproducibility is excellent, thus indicating that this analytical method is useful to determinate the concentrations of carbonaceous gases.

Factors affecting the accuracy of engineers' estimates

Emerging sciences, such as conceptual cost estimating, seem to have to go through two phases. The first phase involves reducing the field of study down to its basic ingredients - from systems development to technological development (techniques) to theoretical development. The second phase operates in the direction in building up techniques from theories, and systems from techniques. Cost estimating is clearly and distinctly still in the first phase. A great deal of effort has been put into the development of both manual and computer based cost estimating systems during this first phase and, to a lesser extent, the development of a range of techniques that can be used (see, for instance, Ashworth & Skitmore, 1986). Theoretical developments have not, as yet, been forthcoming. All theories need the support of some observational data and cost estimating is not likely to be an exception. These data do not need to be complete in order to build theories. As it is possible to construct an image of a prehistoric animal such as the brontosaurus from only a few key bones and relics, so a theory of cost estimating may possibly be found on a few factual details. The eternal argument of empiricists and deductionists is that, as theories need factual support, so do we need theories in order to know what facts to collect. In cost estimating, the basic facts of interest concern accuracy, the cost of achieving this accuracy, and the trade off between the two. When cost estimating theories do begin to emerge, it is highly likely that these relationships will be central features. This paper presents some of the facts we have been able to acquire regarding one part of this relationship - accuracy, and its influencing factors. Although some of these factors, such as the amount of information used in preparing the estimate, will have cost consequences, we have not yet reached the stage of quantifying these costs. Indeed, as will be seen, many of the factors do not involve any substantial cost considerations. The absence of any theory is reflected in the arbitrary manner in which the factors are presented. Rather, the emphasis here is on the consideration of purely empirical data concerning estimating accuracy. The essence of good empirical research is to .minimize the role of the researcher in interpreting the results of the study. Whilst space does not allow a full treatment of the material in this manner, the principle has been adopted as closely as possible to present results in an uncleaned and unbiased way. In most cases the evidence speaks for itself. The first part of the paper reviews most of the empirical evidence that we have located to date. Knowledge of any work done, but omitted here would be most welcome. The second part of the paper presents an analysis of some recently acquired data pertaining to this growing subject.

Improved estimates of percolation and anisotropic permeability from 3-D X-ray microtomography using stochastic analyses and visualization

X-ray microtomography (micro-CT) with micron resolution enables new ways of characterizing microstructures and opens pathways for forward calculations of multiscale rock properties. A quantitative characterization of the microstructure is the first step in this challenge. We developed a new approach to extract scale-dependent characteristics of porosity, percolation, and anisotropic permeability from 3-D microstructural models of rocks. The Hoshen-Kopelman algorithm of percolation theory is employed for a standard percolation analysis. The anisotropy of permeability is calculated by means of the star volume distribution approach. The local porosity distribution and local percolation probability are obtained by using the local porosity theory. Additionally, the local anisotropy distribution is defined and analyzed through two empirical probability density functions, the isotropy index and the elongation index. For such a high-resolution data set, the typical data sizes of the CT images are on the order of gigabytes to tens of gigabytes; thus an extremely large number of calculations are required. To resolve this large memory problem parallelization in OpenMP was used to optimally harness the shared memory infrastructure on cache coherent Non-Uniform Memory Access architecture machines such as the iVEC SGI Altix 3700Bx2 Supercomputer. We see adequate visualization of the results as an important element in this first pioneering study.

Footprint-based estimates of arch structure are confounded by body composition in adults

Previous research employing indirect measures of arch structure, such as those derived from footprints, have indicated that obesity results in a “flatter” foot type. In the absence of radiographic measures, however, definitive conclusions regarding the osseous alignment of the foot cannot be made. We determined the effect of body mass index (BMI) on radiographic and footprint‐based measures of arch structure. The research was a cross‐sectional study in which radiographic and footprint‐based measures of foot structure were made in 30 subjects (10 males, 20 female) in addition to standard anthropometric measures of height, weight, and BMI. Multiple (univariate) regression analysis demonstrated that both BMI ( β  = 0.39, t 26  = 2.12, p  = 0.04) and radiographic arch alignment ( β  = 0.51, t 26  = 3.32, p  < 0.01) were significant predictors of footprint‐based measures of arch height after controlling for all variables in the model ( R 2  = 0.59, F 3,26  = 12.3, p  < 0.01). In contrast, radiographic arch alignment was not significantly associated with BMI ( β  = −0.03, t 26  = −0.13, p  = 0.89) when Arch Index and age were held constant ( R 2  = 0.52, F 3,26  = 9.3, p  < 0.01). Adult obesity does not influence osseous alignment of the medial longitudinal arch, but selectively distorts footprint‐based measures of arch structure. Footprint‐based measures of arch structure should be interpreted with caution when comparing groups of varying body composition.

Quantitative genetic parameter estimates for body and carcass traits in a cultured stock of giant freshwater prawn (Macrobrachium rosenbergii) selected for harvest weight in Vietnam

We estimated the heritability and correlations between body and carcass weight traits in a cultured stock of giant freshwater prawn (GFP) (Macrobrachium rosenbergii) selected for harvest body weight in Vietnam. The data set consisted of 18,387 body and 1,730 carcass records, as well as full pedigree information collected over four generations. Variance and covariance components were estimated by restricted maximum likelihood fitting a multi-trait animal model. Across generations, estimates of heritability for body and carcass weight traits were moderate and ranged from 0.14 to 0.19 and 0.17 to 0.21, respectively. Body trait heritabilities estimated for females were significantly higher than for males whereas carcass weight trait heritabilities estimated for females and males were not significantly different (P>. 0.05). Maternal effects for body traits accounted for 4 to 5% of the total variance and were greater in females than in males. Genetic correlations among body traits were generally high in the mixed sexes. Genetic correlations between body and carcass weight traits were also high. Although some issues remain regarding the best statistical model to be fitted to GFP data, our results suggest that selection for high harvest body weight based on breeding values estimated by fitting an animal model to the data can significantly improve mean body and carcass weight in GFP.

The health effects of temperature : current estimates, future projections, and adaptation strategies

Climate change is expected to be one of the biggest global health threats in the 21st century. In response to changes in climate and associated extreme events, public health adaptation has become imperative. This thesis examined several key issues in this emerging research field. The thesis aimed to identify the climate-health (particularly temperature-health) relationships, then develop quantitative models that can be used to project future health impacts of climate change, and therefore help formulate adaptation strategies for dealing with climate-related health risks and reducing vulnerability. The research questions addressed by this thesis were: (1) What are the barriers to public health adaptation to climate change? What are the research priorities in this emerging field? (2) What models and frameworks can be used to project future temperature-related mortality under different climate change scenarios? (3) What is the actual burden of temperature-related mortality? What are the impacts of climate change on future burden of disease? and (4) Can we develop public health adaptation strategies to manage the health effects of temperature in response to climate change? Using a literature review, I discussed how public health organisations should implement and manage the process of planned adaptation. This review showed that public health adaptation can operate at two levels: building adaptive capacity and implementing adaptation actions. However, there are constraints and barriers to adaptation arising from uncertainty, cost, technologic limits, institutional arrangements, deficits of social capital, and individual perception of risks. The opportunities for planning and implementing public health adaptation are reliant on effective strategies to overcome likely barriers. I proposed that high priorities should be given to multidisciplinary research on the assessment of potential health effects of climate change, projections of future health impacts under different climate and socio-economic scenarios, identification of health cobenefits of climate change policies, and evaluation of cost-effective public health adaptation options. Heat-related mortality is the most direct and highly-significant potential climate change impact on human health. I thus conducted a systematic review of research and methods for projecting future heat-related mortality under different climate change scenarios. The review showed that climate change is likely to result in a substantial increase in heatrelated mortality. Projecting heat-related mortality requires understanding of historical temperature-mortality relationships, and consideration of future changes in climate, population and acclimatisation. Further research is needed to provide a stronger theoretical framework for mortality projections, including a better understanding of socioeconomic development, adaptation strategies, land-use patterns, air pollution and mortality displacement. Most previous studies were designed to examine temperature-related excess deaths or mortality risks. However, if most temperature-related deaths occur in the very elderly who had only a short life expectancy, then the burden of temperature on mortality would have less public health importance. To guide policy decisions and resource allocation, it is desirable to know the actual burden of temperature-related mortality. To achieve this, I used years of life lost to provide a new measure of health effects of temperature. I conducted a time-series analysis to estimate years of life lost associated with changes in season and temperature in Brisbane, Australia. I also projected the future temperaturerelated years of life lost attributable to climate change. This study showed that the association between temperature and years of life lost was U-shaped, with increased years of life lost on cold and hot days. The temperature-related years of life lost will worsen greatly if future climate change goes beyond a 2 °C increase and without any adaptation to higher temperatures. The excess mortality during prolonged extreme temperatures is often greater than the predicted using smoothed temperature-mortality association. This is because sustained period of extreme temperatures produce an extra effect beyond that predicted by daily temperatures. To better estimate the burden of extreme temperatures, I estimated their effects on years of life lost due to cardiovascular disease using data from Brisbane, Australia. The results showed that the association between daily mean temperature and years of life lost due to cardiovascular disease was U-shaped, with the lowest years of life lost at 24 °C (the 75th percentile of daily mean temperature in Brisbane), rising progressively as temperatures become hotter or colder. There were significant added effects of heat waves, but no added effects of cold spells. Finally, public health adaptation to hot weather is necessary and pressing. I discussed how to manage the health effects of temperature, especially with the context of climate change. Strategies to minimise the health effects of high temperatures and climate change can fall into two categories: reducing the heat exposure and managing the health effects of high temperatures. However, policy decisions need information on specific adaptations, together with their expected costs and benefits. Therefore, more research is needed to evaluate cost-effective adaptation options. In summary, this thesis adds to the large body of literature on the impacts of temperature and climate change on human health. It improves our understanding of the temperaturehealth relationship, and how this relationship will change as temperatures increase. Although the research is limited to one city, which restricts the generalisability of the findings, the methods and approaches developed in this thesis will be useful to other researchers studying temperature-health relationships and climate change impacts. The results may be helpful for decision-makers who develop public health adaptation strategies to minimise the health effects of extreme temperatures and climate change.

Approximate Bayesian computation using auxiliary model based estimates

We present a novel approach for developing summary statistics for use in approximate Bayesian computation (ABC) algorithms using indirect infer- ence. We embed this approach within a sequential Monte Carlo algorithm that is completely adaptive. This methodological development was motivated by an application involving data on macroparasite population evolution modelled with a trivariate Markov process. The main objective of the analysis is to compare inferences on the Markov process when considering two di®erent indirect mod- els. The two indirect models are based on a Beta-Binomial model and a three component mixture of Binomials, with the former providing a better ¯t to the observed data.

Are in vitro estimates of cell diffusivity and cell proliferation rate sensitive to assay geometry?

Cells respond to various biochemical and physical cues during wound–healing and tumour progression. In vitro assays used to study these processes are typically conducted in one particular geometry and it is unclear how the assay geometry affects the capacity of cell populations to spread, or whether the relevant mechanisms, such as cell motility and cell proliferation, are somehow sensitive to the geometry of the assay. In this work we use a circular barrier assay to characterise the spreading of cell populations in two different geometries. Assay 1 describes a tumour–like geometry where a cell population spreads outwards into an open space. Assay 2 describes a wound–like geometry where a cell population spreads inwards to close a void. We use a combination of discrete and continuum mathematical models and automated image processing methods to obtain independent estimates of the effective cell diffusivity, D, and the effective cell proliferation rate, λ. Using our parameterised mathematical model we confirm that our estimates of D and λ accurately predict the time–evolution of the location of the leading edge and the cell density profiles for both assay 1 and assay 2. Our work suggests that the effective cell diffusivity is up to 50% lower for assay 2 compared to assay 1, whereas the effective cell proliferation rate is up to 30% lower for assay 2 compared to assay 1.

Semiparametric estimates of the supply and demand effects of disability on labor force participation

This paper modifies and uses the semiparametric methods of Ichimura and Lee (1991) on standard cross-section data to decompose the effect of disability on labor force participation into a demand and a supply effect. It shows that straightforward use of Ichimura and Lee leads to meaningless results while imposing monotonicity on the unknown function leads to substantial results. The paper finds that supply effects dominate the demand effects of disability.

New estimates for CRNA vacancies

A national survey to estimate vacancy rates of Certified Registered Nurse Anesthetists (CRNAs) in hospitals and ambulatory surgical centers was conducted in 2007. Poisson regression methods were used to improve the precision of the estimates. A significant increase in the estimated vacancy rate was reported for hospitals relative to an earlier study from 2002, although it is important to note that there were some methodological differences between the 2 surveys explaining part of the increase. Results from this study found the vacancy rate was higher in rural hospitals than in nonrural hospitals, and it was lower in ambulatory surgical centers. A number of simulations were run to predict the effects of relevant changes in the market for surgeries and number of CRNAs, which were compared to the predictions from the previous survey. The remarkable factor since the last survey was the unusually large rate of new CRNAs entering the market, yet the vacancy rates remain relatively high.

A Raman spectroscopic study of the arsenate mineral chenevixite Cu2Fe23+(AsO4)2(OH)4⋅H2O

We have studied the mineral chenevixite from Manto Cuba Mine, San Pedro de Cachiyuyo District, Inca de Oro, Chañaral Province, Atacama Region, Chile, using a combination of scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDX) and vibrational spectroscopy. Qualitative chemical analysis shows a homogeneous composition, with predominance of As, Fe, Al, Cu, Fe and Cu. Minor amounts of Si were also observed. Raman spectroscopy complimented with infrared spectroscopy has been used to assess the molecular structure of the arsenate minerals chenevixite. Characteristic Raman and infrared bands of the (AsO4)3− stretching and bending vibrations are identified and described. The observation of multiple bands in the (AsO4)3− bending region offers support for the loss of symmetry of the arsenate anion in the structure of chenevixite. Raman bands attributable to the OH stretching vibrations of water and hydroxyl units were analysed. Estimates of the hydrogen bond distances were made based upon the OH stretching wavenumbers.

Can estimates of antimalarial efficacy from field studies be improved?

Monitoring therapeutic efficacy of antimalarial drugs is important because treatment failure rates are the primary basis for changing antimalarial treatment policy. An important aspect of efficacy studies is the use of PCR genotyping to distinguish recrudescent from new infections. The conclusions reached using this technique might be misleading if there is insufficient parasite diversity or a non-uniform haplotype frequency distribution in the study area. Statistical techniques can be used to overcome this problem, but only when data describing the haplotype frequency distribution are available. Therefore, assessing haplotype frequency and distribution should form an integral part of all studies investigating the therapeutic efficacy of antimalarial treatment regimes.