Through a qualitative application of the theory of planned behaviour, the research aimed to increase understanding of elite athletes' reasons behind intentional and actual doping and match fixing. ...Adopting a descriptive phenomenological approach, media interviews, admission statements and testimonies from dopers and match fixers were analysed using deductive content analysis. The final sample comprised 21 elite athlete match fixers from 15 nations and 33 elite athlete dopers from 10 nations. Whilst all three theories of planar behaviour variables were found to influence doping, only attitudinal and subjective normative beliefs influenced match fixing. Despite some similarities between doping and match fixing themes, differences exist between the primary corruption motives and unique doping attitudes emerged. By identifying the reasons behind elite athletes' engagement in corruption the results can be used to better inform the design of preventative doping and match fixing strategies within elite sport.
The telomere structure in the Iberian shrew
Sorex granarius
is characterized by unique, striking features, with short arms of acrocentric chromosomes carrying extremely long telomeres (up to 300 kb) ...with interspersed ribosomal DNA (rDNA) repeat blocks. In this work, we investigated the telomere physiology of
S. granarius
fibroblast cells and found that telomere repeats are transcribed on both strands and that there is no telomere-dependent senescence mechanism. Although telomerase activity is detectable throughout cell culture and appears to act on both short and long telomeres, we also discovered that signatures of a recombinogenic activity are omnipresent, including telomere-sister chromatid exchanges, formation of alternative lengthening of telomeres (ALT)-associated PML-like bodies, production of telomere circles, and a high frequency of telomeres carrying marks of a DNA damage response. Our results suggest that recombination participates in the maintenance of the very long telomeres in normal
S. granarius
fibroblasts. We discuss the possible interplay between the interspersed telomere and rDNA repeats in the stabilization of the very long telomeres in this organism.
This paper presents methods for the parameter identification of a model of subtilin production by Bacillus subtilis. Based on a stochastic hybrid model, identification is split in two subproblems: ...estimation of the genetic network regulating subtilin production from gene expression data, and estimation of population dynamics based on nutrient and population level data. Techniques for identification of switching dynamics from sparse and irregularly sampled observations are developed and applied to simulated data. Numerical results are provided to show the effectiveness of our methods.
We present a method for the structural identification of genetic regulatory networks (GRNs), based on the use of a class of Piecewise-Linear (PL) models. These models consist of a set of decoupled ...linear models describing the different modes of operation of the GRN and discrete switches between the modes accounting for the nonlinear character of gene regulation. They thus form a compromise between the mathematical simplicity of linear models and the biological expressiveness of nonlinear models. The input of the PL identification method consists of time-series measurements of concentrations of gene products. As output it produces estimates of the modes of operation of the GRN, as well as all possible minimal combinations of threshold concentrations of the gene products accounting for switches between the modes of operation. The applicability of the PL identification method has been evaluated using simulated data obtained from a model of the carbon starvation response in the bacterium Escherichia coli. This has allowed us to systematically test the performance of the method under different data characteristics, notably variations in the noise level and the sampling density.
Objectives: To determine the diagnostic accuracy of hysteroscopy in the diagnosis of endometrial hyperplasia in women with abnormal uterine bleeding.
Methods: From 1993 through 1995, 980 women ...referred to our institution for abnormal uterine bleeding underwent diagnostic hysteroscopy with eye direct biopsy of the endometrium in case of macroscopic abnormalities. Hysteroscopic features were compared with pathologic findings in order to detect the reliability of the endoscopic procedure. Statistical analysis was performed with the McNemar test.
Results: Positive predictive value of hysteroscopy in the diagnosis of endometrial hyperplasia accounted for 63%. In fact hysteroscopic diagnosis of endometrial hyperplasia was confirmed at pathologic examination in 81 out of 128 patients. Sensitivity and specificity of the endoscopic procedure accounted for 98% and 95%, respectively. Negative predictive value accounted for 99%, as only two cases of atypical hyperplasia were missed at hysteroscopy. Positive predictive value was higher in postmenopausal patients compared to women in the fertile age (72 vs. 58%).
Conclusions: Overall, results appear encouraging, since no case of endometrial hyperplasia was missed by hysteroscopy. The high diagnostic accuracy, associated with a minimal trauma, renders hysteroscopy the ideal procedure for both diagnosis and follow-up of conservative management of endometrial hyperplasia.
In this paper we introduce a novel method to extract from data and graphically represent the temporal relationships between events, called precedence temporal network. The new approach first derives ...events from time series by exploiting the temporal abstraction technique, then derives temporal precedence between abstractions in terms of association rules and finally expresses the relationships as a labeled graph. The method is applied to the problem of representing the temporal behavior of gene expressions, as they are collected by DNA microarrays. In particular, in this paper we present the results obtained from the analysis of the expression of a subset of the genes involved in cell-cycle regulation.
We consider the problem of learning dynamical models of genetic regulatory networks from time-lapse measurements of gene expression. In our previous work, we described a method for the structural and ...parametric identification of ODE models that makes use of concurrent measurements of concentrations and synthesis rates of the gene products, and requires the knowledge of the noise statistics. In this paper we assume all these pieces of information are not simultaneously available. In particular we propose extensions of that make the method applicable to protein concentration measurements only. We discuss the performance of the method on experimental data from the network IRMA, a benchmark synthetic network engineered in yeast Saccharomices cerevisiae.
We discuss the identification of genetic networks based on a class of boolean gene activation rules known as hierarchically canalizing functions. We introduce a class of kinetic models for the ...concentration of the proteins in the network built on a family of canalizing functions that has been shown to capture the vast majority of the known interaction networks. The simultaneous identification of the structure and of the parameters of the model from experimental data is addressed based on a mixed integer parametrization of the model class. The resulting regression problem is solved numerically via standard branch-and-bound techniques. The performance of the method is tested on simulated data generated by a simple model of Escherichia coli nutrient stress response.
This paper concerns parameter identification for the class of jump Markov linear systems. We present recursive formulae for the computation of the second-order statistics of a jump Markov process and ...discuss their application to the estimation of the model parameters given data from a single or repeated experiments. Simulation results are provided to show the effectiveness of our approach.
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