Endothelin axis expression is markedly different in the two main subtypes of renal cell carcinoma

BACKGROUND. The endothelin axis has been implicated in cancer growth, angiogenesis, and metastasis, but to the authors' knowledge the expression of endothelin genes has not been defined in renal cell carcinoma (RCC). METHODS. Tissue specimens were harvested from both normal and tumor-affected regions at the time of radical nephrectomy from 35 patients with RCC (22 with clear cell RCC [ccRCC] and 13 with papillary RCC [PRCC]). Real-time reverse transcriptase-polymerase chain reaction analysis determined the expression profile of the preproendothelins (PPET-1, PPET-2, and PPET-3), the endothelin receptors (ETA and ETB), and the endothelin-converting enzymes (ECE-1 and ECE-2). RESULTS. PPET-1 was found to be up-regulated in ccRCC tumor specimens and down-regulated in PRCC tumor specimens. ETA was significantly down-regulated in PRCC tumor specimens. ECE-1 was expressed in all tissue specimens at comparable levels, with moderate but significant elevation in normal tissue specimens associated with PRCC. Of the other genes, PPET-2 and ETB were expressed in all tissue specimens and no differences were observed between tumor subtypes or tumor-affected and normal tissue specimens, whereas PPET-3 and ECE-2 were present in all tissue specimens but were barely detectable. CONCLUSIONS. The endothelin axis was expressed differently in the two main subtypes of RCC and appeared to match macroscopic features commonly observed in these tumors (i.e., high expression of PPET-I in hypervascular ccRCC contrasted against low PPET-1 and ETA expression in hypovascular PRCC). The presence of ECE-1 mRNA in these tissue specimens suggested that active endothelin ligands were present, indicating endothelin axis activity was elevated in ccRCC compared with normal kidney, but impaired in PRCC. The current study provided further evidence that it is not appropriate to consider ccRCC and PRCC indiscriminately in regard to treatment. (C) 2004 American Cancer Society.

A PCR method for the identification of methicillin-resistant Staphylococcus aureus (MRSA) from screening swabs

Aim: The aim of this study was to assess the discriminatory power and potential turn around time ( TAT) of a PCR-based method for the detection of methicillin-resistant Staphylococcus aureus (MRSA) from screening swabs. Methods: Screening swabs were examined using the current laboratory protocol of direct culture on mannitol salt agar supplemented with oxacillin (MSAO-direct). The PCR method involved pre-incubation in broth for 4 hours followed by a multiplex PCR with primers directed to mecA and nuc genes of MRSA. The reference standard was determined by pre-incubation in broth for 4 hours followed by culture on MSAO (MSAO-broth). Results: A total of 256 swabs was analysed. The rates of detection of MRSA using MSAO-direct, MSAO-broth and PCR were 10.2, 13.3 and 10.2%, respectively. For PCR, the sensitivity, specificity, positive predictive value and negative predictive values were 66.7% (95% CI 51.9 - 83.3%), 98.6% ( 95% CI 97.1 - 100%), 84.6% ( 95% CI 76.2 - 100%) and 95.2% ( 95% CI 92.4 - 98.0%), respectively, and these results were almost identical to those obtained from MSAO-direct. The agreement between MSAO-direct and PCR was 61.5% ( 95% CI 42.8 - 80.2%) for positive results, 95.6% ( 95% CI 93.0 - 98.2%) for negative results and overall was 92.2% ( 95% CI 88.9 - 95.5%). Conclusions: ( 1) The discriminatory power of PCR and MSAO-direct is similar but the level of agreement, especially for true positive results, is low. ( 2) The potential TAT for the PCR method provides a marked advantage over conventional methods. ( 3) Further modifications to the PCR method such as increased broth incubation time, use of selective broth and adaptation to real-time PCR may lead to improvement in sensitivity and TAT.

Phylogeny and biogeography of the freshwater crayfish Euastacus (Decapoda : Parastacidae) based on nuclear and mitochondrial DNA

Euastacus crayfish are endemic to freshwater ecosystems of the eastern coast of Australia. While recent evolutionary studies have focused on a few of these species, here we provide a comprehensive phylogenetic estimate of relationships among the species within the genus. We sequenced three mitochondrial gene regions (COI, 16S, and 12S) and one nuclear region (28S) from 40 species of the genus Euastacus, as well as one undescribed species. Using these data, we estimated the phylogenetic relationships within the genus using maximum-likelihood, parsimony, and Bayesian Markov Chain Monte Carlo analyses. Using Bayes factors to test different model hypotheses, we found that the best phylogeny supports monophyletic groupings of all but two recognized species and suggests a widespread ancestor that diverged by vicariance. We also show that Eitastacus and Astacopsis are most likely monophyletic sister genera. We use the resulting phylogeny as a framework to test biogeographic hypotheses relating to the diversification of the genus. (c) 2005 Elsevier Inc. All rights reserved.

Assessing the impacts of grazing levels on bird density in woodland habitat: a Bayesian approach using expert opinion

Many studies on birds focus on the collection of data through an experimental design, suitable for investigation in a classical analysis of variance (ANOVA) framework. Although many findings are confirmed by one or more experts, expert information is rarely used in conjunction with the survey data to enhance the explanatory and predictive power of the model. We explore this neglected aspect of ecological modelling through a study on Australian woodland birds, focusing on the potential impact of different intensities of commercial cattle grazing on bird density in woodland habitat. We examine a number of Bayesian hierarchical random effects models, which cater for overdispersion and a high frequency of zeros in the data using WinBUGS and explore the variation between and within different grazing regimes and species. The impact and value of expert information is investigated through the inclusion of priors that reflect the experience of 20 experts in the field of bird responses to disturbance. Results indicate that expert information moderates the survey data, especially in situations where there are little or no data. When experts agreed, credible intervals for predictions were tightened considerably. When experts failed to agree, results were similar to those evaluated in the absence of expert information. Overall, we found that without expert opinion our knowledge was quite weak. The fact that the survey data is quite consistent, in general, with expert opinion shows that we do know something about birds and grazing and we could learn a lot faster if we used this approach more in ecology, where data are scarce. Copyright (c) 2005 John Wiley & Sons, Ltd.

On the estimation and comparison of short-rate models using the generalised method of moments

Subsequent to the influential paper of [Chan, K.C., Karolyi, G.A., Longstaff, F.A., Sanders, A.B., 1992. An empirical comparison of alternative models of the short-term interest rate. Journal of Finance 47, 1209-1227], the generalised method of moments (GMM) has been a popular technique for estimation and inference relating to continuous-time models of the short-term interest rate. GMM has been widely employed to estimate model parameters and to assess the goodness-of-fit of competing short-rate specifications. The current paper conducts a series of simulation experiments to document the bias and precision of GMM estimates of short-rate parameters, as well as the size and power of [Hansen, L.P., 1982. Large sample properties of generalised method of moments estimators. Econometrica 50, 1029-1054], J-test of over-identifying restrictions. While the J-test appears to have appropriate size and good power in sample sizes commonly encountered in the short-rate literature, GMM estimates of the speed of mean reversion are shown to be severely biased. Consequently, it is dangerous to draw strong conclusions about the strength of mean reversion using GMM. In contrast, the parameter capturing the levels effect, which is important in differentiating between competing short-rate specifications, is estimated with little bias. (c) 2006 Elsevier B.V. All rights reserved.

On the existence of uni-instantaneous Q-processes with a given finite mu-invariant measure

Let S be a countable set and let Q = (q(ij), i, j is an element of S) be a conservative q-matrix over S with a single instantaneous state b. Suppose that we are given a real number mu >= 0 and a strictly positive probability measure m = (m(j), j is an element of S) such that Sigma(i is an element of S) m(i)q(ij) = -mu m(j), j 0 b. We prove that there exists a Q-process P(t) = (p(ij) (t), i, j E S) for which m is a mu-invariant measure, that is Sigma(i is an element of s) m(i)p(ij)(t) = e(-mu t)m(j), j is an element of S. We illustrate our results with reference to the Kolmogorov 'K 1' chain and a birth-death process with catastrophes and instantaneous resurrection.

A polymorphism in the agouti signalling protein (ASIP) is associated with decreased levels of mRNA

To date, a role for agouti signalling protein (ASIP) in human pigmentation has not been well characterized. It is known that agouti plays a pivotal role in the pigment switch from the dark eumelanin to the light pheomelanin in the mouse. However, because humans do not have an agouti banded hair pattern, its role in human pigmentation has been questioned. We previously identified a single polymorphism in the 3'-untranslated region (UTR) of ASIP that was found at a higher frequency in African-Americans compared with other population groups. To compare allele frequencies between European-Australians and indigenous Australians, the g.8818A -> G polymorphism was genotyped. Significant differences were seen in allele frequencies between these groups (P < 0.0001) with carriage of the G allele highest in Australian Aborigines. In the Caucasian sample set a strong association was observed between the G allele and dark hair colour (P = 0.004) (odds ratio 4.6; 95% CI 1.4-15.27). The functional consequences of this polymorphism are not known but it was postulated that it might result in message instability and premature degradation of the transcript. To test this hypothesis, ASIP mRNA levels were quantified in melanocytes carrying the variant and non-variant alleles. Using quantitative real-time polymerase chain reaction the mean ASIP mRNA ratio of the AA genotype to the AG genotype was 12 (P < 0.05). This study suggests that the 3'-UTR polymorphism results in decreased levels of ASIP and therefore less pheomelanin production.

Chronic smoking and alcoholism change expression of selective genes in the human prefrontal cortex

Background: Alcoholism is commonly associated with chronic smoking. A number of gene expression profiles of regions within the human mesocorticolimbic system have identified potential alcohol-sensitive genes; however, the influence of smoking on these changes was not taken into account. This study addressed the impact of alcohol and smoking on the expression of 4 genes, previously identified as alcoholism-sensitive. in the human prefrontal cortex (PFC). Methods: mRNA expression of apolipoprotein D, tissue inhibitor of the metalloproteinase 3, high-affinity glial glutamate transporter and midkine, was measured in the PFC of alcoholic Subjects and controls with and without smoking comorbidity using real-time polymerase chain reaction. Results: The results show that alcohol affects transcription of some of these genes. Additionally, smoking has a marked influence on gene expression. Conclusion: This study emphasizes the need for careful case selection in future gene expression studies to delineate the adaptive molecular process associated with smoking and alcohol.

Segmenting eukaryotic genomes with the generalized Gibbs sampler

Eukaryotic genomes display segmental patterns of variation in various properties, including GC content and degree of evolutionary conservation. DNA segmentation algorithms are aimed at identifying statistically significant boundaries between such segments. Such algorithms may provide a means of discovering new classes of functional elements in eukaryotic genomes. This paper presents a model and an algorithm for Bayesian DNA segmentation and considers the feasibility of using it to segment whole eukaryotic genomes. The algorithm is tested on a range of simulated and real DNA sequences, and the following conclusions are drawn. Firstly, the algorithm correctly identifies non-segmented sequence, and can thus be used to reject the null hypothesis of uniformity in the property of interest. Secondly, estimates of the number and locations of change-points produced by the algorithm are robust to variations in algorithm parameters and initial starting conditions and correspond to real features in the data. Thirdly, the algorithm is successfully used to segment human chromosome 1 according to GC content, thus demonstrating the feasibility of Bayesian segmentation of eukaryotic genomes. The software described in this paper is available from the author's website (www.uq.edu.au/similar to uqjkeith/) or upon request to the author.

Non-response to antiviral therapy is associated with obesity and increased hepatic expression of suppressor of cytokine signalling 3 (SOCS-3) in patients with chronic hepatitis C, viral genotype 1

Background: Interferon alpha (IFN-alpha) activated cellular signalling is negatively regulated by inhibitory factors, including the suppressor of cytokine signalling (SOCS) family. The effects of host factors such as obesity on hepatic expression of these inhibitory factors in subjects with chronic hepatitis C virus (HCV) are unknown. Objectives: To assess the independent effects of obesity, insulin resistance, and steatosis on response to IFN-alpha therapy and to determine hepatic expression of factors inhibiting IFN-alpha signalling in obese and nonobese subjects with chronic HCV. Methods: A total of 145 subjects were analysed to determine host factors associated with non-response to antiviral therapy. Treatment comprised IFN-alpha or peginterferon alpha, either alone or in combination with ribavirin. In a separate cohort of 73 patients, real time-polymerase chain reaction was performed to analyse hepatic mRNA expression. Immunohistochemistry for SOCS-3 was performed on liver biopsy samples from 38 patients with viral genotype 1 who had received antiviral treatment. Results: Non-response (NR) to treatment occurred in 55% of patients with HCV genotypes 1 or 4 and 22% with genotypes 2 or 3. Factors independently associated with NR were viral genotype 1/4 (p < 0.001), cirrhosis on pretreatment biopsy (p = 0.025), and body mass index >= 30 kg/m(2) (p = 0.010). Obese subjects with viral genotype 1 had increased hepatic mRNA expression of phosphoenolpyruvate carboxy kinase (p = 0.01) and SOCS-3 (p = 0.047), in comparison with lean subjects. Following multivariate analysis, SOCS-3 mRNA expression remained independently associated with obesity (p = 0.023). SOCS-3 immunoreactivity was significantly increased in obesity (p = 0.013) and in non-responders compared with responders (p = 0.014). Conclusions: In patients with chronic HCV viral genotype 1, increased expression of factors that inhibit interferon signalling may be one mechanism by which obesity reduces the biological response to IFN-alpha.

Motor unit number estimation - A Bayesian approach

All muscle contractions are dependent on the functioning of motor units. In diseases such as amyotrophic lateral sclerosis (ALS), progressive loss of motor units leads to gradual paralysis. A major difficulty in the search for a treatment for these diseases has been the lack of a reliable measure of disease progression. One possible measure would be an estimate of the number of surviving motor units. Despite over 30 years of motor unit number estimation (MUNE), all proposed methods have been met with practical and theoretical objections. Our aim is to develop a method of MUNE that overcomes these objections. We record the compound muscle action potential (CMAP) from a selected muscle in response to a graded electrical stimulation applied to the nerve. As the stimulus increases, the threshold of each motor unit is exceeded, and the size of the CMAP increases until a maximum response is obtained. However, the threshold potential required to excite an axon is not a precise value but fluctuates over a small range leading to probabilistic activation of motor units in response to a given stimulus. When the threshold ranges of motor units overlap, there may be alternation where the number of motor units that fire in response to the stimulus is variable. This means that increments in the value of the CMAP correspond to the firing of different combinations of motor units. At a fixed stimulus, variability in the CMAP, measured as variance, can be used to conduct MUNE using the "statistical" or the "Poisson" method. However, this method relies on the assumptions that the numbers of motor units that are firing probabilistically have the Poisson distribution and that all single motor unit action potentials (MUAP) have a fixed and identical size. These assumptions are not necessarily correct. We propose to develop a Bayesian statistical methodology to analyze electrophysiological data to provide an estimate of motor unit numbers. Our method of MUNE incorporates the variability of the threshold, the variability between and within single MUAPs, and baseline variability. Our model not only gives the most probable number of motor units but also provides information about both the population of units and individual units. We use Markov chain Monte Carlo to obtain information about the characteristics of individual motor units and about the population of motor units and the Bayesian information criterion for MUNE. We test our method of MUNE on three subjects. Our method provides a reproducible estimate for a patient with stable but severe ALS. In a serial study, we demonstrate a decline in the number of motor unit numbers with a patient with rapidly advancing disease. Finally, with our last patient, we show that our method has the capacity to estimate a larger number of motor units.

Simulation of air traffic controllers' behaviour using the operator choice model

The Operator Choice Model (OCM) was developed to model the behaviour of operators attending to complex tasks involving interdependent concurrent activities, such as in Air Traffic Control (ATC). The purpose of the OCM is to provide a flexible framework for modelling and simulation that can be used for quantitative analyses in human reliability assessment, comparison between human computer interaction (HCI) designs, and analysis of operator workload. The OCM virtual operator is essentially a cycle of four processes: Scan Classify Decide Action Perform Action. Once a cycle is complete, the operator will return to the Scan process. It is also possible to truncate a cycle and return to Scan after each of the processes. These processes are described using Continuous Time Probabilistic Automata (CTPA). The details of the probability and timing models are specific to the domain of application, and need to be specified using domain experts. We are building an application of the OCM for use in ATC. In order to develop a realistic model we are calibrating the probability and timing models that comprise each process using experimental data from a series of experiments conducted with student subjects. These experiments have identified the factors that influence perception and decision making in simplified conflict detection and resolution tasks. This paper presents an application of the OCM approach to a simple ATC conflict detection experiment. The aim is to calibrate the OCM so that its behaviour resembles that of the experimental subjects when it is challenged with the same task. Its behaviour should also interpolate when challenged with scenarios similar to those used to calibrate it. The approach illustrated here uses logistic regression to model the classifications made by the subjects. This model is fitted to the calibration data, and provides an extrapolation to classifications in scenarios outside of the calibration data. A simple strategy is used to calibrate the timing component of the model, and the results for reaction times are compared between the OCM and the student subjects. While this approach to timing does not capture the full complexity of the reaction time distribution seen in the data from the student subjects, the mean and the tail of the distributions are similar.

Regression with input-dependent noise: A Gaussian process treatment

Gaussian processes provide natural non-parametric prior distributions over regression functions. In this paper we consider regression problems where there is noise on the output, and the variance of the noise depends on the inputs. If we assume that the noise is a smooth function of the inputs, then it is natural to model the noise variance using a second Gaussian process, in addition to the Gaussian process governing the noise-free output value. We show that prior uncertainty about the parameters controlling both processes can be handled and that the posterior distribution of the noise rate can be sampled from using Markov chain Monte Carlo methods. Our results on a synthetic data set give a posterior noise variance that well-approximates the true variance.