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Journal articleMingot JM, Tilburn J, Diez E, et al., 1999,
Specificity determinants of proteolytic processing of <i>Aspergillus</i> PacC transcription factor are remote from the processing site, and processing occurs in yeast if pH signalling is bypassed
, MOLECULAR AND CELLULAR BIOLOGY, Vol: 19, Pages: 1390-1400, ISSN: 0270-7306- Cite
- Citations: 64
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Journal articleDizier MH, Sandford A, Walley A, et al., 1999,
Indication of linkage of serum IgE levels to the interleukin-4 gene and exclusion of the contribution of the (-590 C to T) interleukin-4 promoter polymorphism to IgE variation
, Genetic Epidemiology, Vol: 16, Pages: 84-94, ISSN: 0741-0395Previous segregation analysis of a sample of 234 randomly selected Australian families showed evidence for a recessive major gene controlling serum immunoglobulin E (IgE) levels independently of the specific response to allergens (SRA). Since linkage has been recently reported between serum IgE levels and the 5q candidate region spanning the interleukin-4 (IL-4) gene, we investigated whether the recessive major gene detected by segregation analysis was linked to the IL-4 region and whether polymorphisms within the IL-4 gene were associated with IgE levels. Both sib-pair method and combined segregation and linkage analysis using the regressive models were applied to our data. Whereas there was no evidence of linkage of total IgE levels to the IL-4 region, an indication of linkage (P values ranging between 0.01 and 0.03) was found between IgE levels adjusted for SRA and two IL-4 polymorphisms: one dinucleotide repeat in intron 2 of the IL-4 gene and a single nucleotide (-590 C to T) polymorphism in the IL-4 promoter. However, the putative IL-4 linked gene did not appear to be in linkage disequilibrium with either of these two polymorphisms. A contribution of the IL-4 promoter polymorphism, presumed to be a potential functional variant influencing IgE variation, was also excluded.
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Conference paperNg CS, Desai SR, Rubens MB, et al., 1999,
Visual quantitation and observer variation of signs of small airways disease at inspiratory and expiratory CT
, Pages: 279-285, ISSN: 0883-5993Areas of decreased pulmonary attenuation representing small airways disease can be identified on computed tomography (CT). The objective was to quantify differences between inspiratory and expiratory CT for the detection of signs of small airways disease by four observers. Observer variation and the superiority of a fine versus a coarse grading system were also evaluated. Inspiratory and expiratory CT scans of 106 patients with conditions characterized by small airways disease and 19 healthy individuals were assessed by four observers. The extent of decreased attenuation was scored on a fine scale to the nearest 5% and also semiquantitatively on a coarser 5-point scale. Decreased attenuation was more extensive on expiratory CT (median, 6.7%; 0-76.7%) than on inspiratory CT (median, 3.8%; 0-81.7%). The fine scoring system had unacceptable interobserver variation (coefficient of variation, 80% for inspiratory CT, 70% for expiratory CT). The semiquantitative system had acceptable interobserver agreement (inspiratory CT k<inf>w</inf> = 0.64; expiratory CT, k<inf>w</inf> = 0.69) and good intra-observer agreement (inspiratory CT, k<inf>w</inf> = 0.80; expiratory CT, k<inf>w</inf> = 0.64). The major CT sign of small airways disease is more confidently quantified on expiratory CT. A fine scoring system is associated with unacceptable observer variation, and a coarse semiquantitative system is more suitable for quantitative studies of small airways disease. © 1999 Lippincott Williams and Wilkins, Inc.
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Journal articleDesai SR, 1999,
Mini-symposium: Cryptogenic fibrosing alveolitis
, Imaging, Vol: 11, ISSN: 0965-6812 -
Journal articleDesai SR, Wells AU, 1999,
Functional-morphological relationships in cryptogenic fibrosing alveolitis
, Imaging, Vol: 11, Pages: 31-38, ISSN: 0965-6812· The relationships between the abnormal morphology of CFA and physiology are ideally investigated using CT; the extent and severity of different CT patterns may be quantified. · The methods used for the quantification of CT patterns and the statistical tests employed in analysis are crucial. · In patients with CFA, the extent of lung involvement on CT is an important determinant of prognosis. · The percent predicted DLco is the best single lung function parameter which reflects global disease extent. However, whether a combination of physiological indices would be better has not been established. · The relationship between DLco and disease extent is perturbed by coexistent emphysema.
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Journal articleDesai SR, Wells AU, Rubens MB, et al., 1999,
Acute respiratory distress syndrome: CT abnormalities at long-term follow-up
, RADIOLOGY, Vol: 210, Pages: 29-35, ISSN: 0033-8419- Author Web Link
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- Citations: 159
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Journal articleCookson WO, 1999,
Disease taxonomy--polygenic.
, Br Med Bull, Vol: 55, Pages: 358-365, ISSN: 0007-1420The practice of medicine depends on the recognition and classification of disease. Correct diagnosis is the cornerstone of correct treatment. The past century has seen the classification of disease move from a reliance on symptoms and signs to the use of more and more sophisticated measurements of human structure and function. However, although most diseases have now have names and schemes of classification, these names still may hide a fundamental lack of understanding of the causes of the disease. The extraordinary progress in molecular genetics in the last 20 years now means that a complete understanding of the constitutional predisposition to disease is possible. All disease results from the interaction between adverse environmental events and constitutional (genetic) resistance or susceptibility. Genetic resistance is modified by ageing. The study of genetics is the process of linking polymorphism in the genetic material to polymorphism or variation in the function or appearance of an organism. The extent to which this becomes clinically useful will be determined by the strength of the genetic effects influencing the disease. Oligogenic disorders, in which just a few genes are impacting on the disease, are more likely to be classifiable by genetic polymorphism than true polygenic disorders, in which a multiplicity of small effects give incremental risks of developing disease. Nevertheless, an improved understanding of the aetiology of disease will in all probability identify previously unrecognised yet distinct subsets of disease.
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Journal articleTaylor JW, Jacobson DJ, Fisher MC, 1999,
The evolution of asexual fungi: Reproduction, speciation and classification
, ANNUAL REVIEW OF PHYTOPATHOLOGY, Vol: 37, Pages: 197-246, ISSN: 0066-4286- Cite
- Citations: 423
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Journal articleBurton PR, Tiller KJ, Gurrin LC, et al., 1999,
Genetic variance components analysis for binary phenotypes using generalized linear mixed models (GLMMs) and Gibbs sampling.
, Genet Epidemiol, Vol: 17, Pages: 118-140, ISSN: 0741-0395The common complex diseases such as asthma are an important focus of genetic research, and studies based on large numbers of simple pedigrees ascertained from population-based sampling frames are becoming commonplace. Many of the genetic and environmental factors causing these diseases are unknown and there is often a strong residual covariance between relatives even after all known determinants are taken into account. This must be modelled correctly whether scientific interest is focused on fixed effects, as in an association analysis, or on the covariances themselves. Analysis is straightforward for multivariate Normal phenotypes, but difficulties arise with other types of trait. Generalized linear mixed models (GLMMs) offer a potentially unifying approach to analysis for many classes of phenotype including multivariate Normal traits, binary traits, and censored survival times. Markov Chain Monte Carlo methods, including Gibbs sampling, provide a convenient framework within which such models may be fitted. In this paper, Bayesian inference Using Gibbs Sampling (a generic Gibbs sampler; BUGS) is used to fit GLMMs for multivariate Normal and binary phenotypes in nuclear families. BUGS is easy to use and readily available. We motivate a suitable model structure for Normal phenotypes and show how the model extends to binary traits. We discuss parameter interpretation and statistical inference and show how to circumvent a number of important theoretical and practical problems that we encountered. Using simulated data we show that model parameters seem consistent and appear unbiased in smaller data sets. We illustrate our methods using data from an ongoing cohort study.
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Journal articleBismarck A, Wuertz C, Springer J, 1999,
Basic Surface Oxides on Carbon Fibers
, Carbon, Vol: 37, Pages: 1019-1027
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