Severity and persistence of asthma and mental health: a birth cohort study

Background. The goal of the current study was to investigate asthma and mental health among youth in the community, and to consider the role of asthma severity and persistence in this link

DNA Aptamers against the Lup an 1 Food Allergen

Using in vitro selection, high affinity DNA aptamers to the food allergen Lup an 1, ß-conglutin, were selected from a pool of DNA, 93 bases in length, containing a randomised sequence of 49 bases. ß-conglutin was purified from lupin flour and chemically crosslinked to carboxylated magnetic beads. Peptide mass fingerprinting was used to confirm the presence of the ß-conglutin. Single stranded DNA was generated from the randomised pool using T7 Gene 6 Exonuclease and was subsequently incubated with the magnetic beads and the captured DNA was released and amplified prior to a further round of Systematic Evolution of Ligands by Exponential Enrichment (SELEX). Evolution was monitored using enzyme linked oligonucleotide assay and surface plasmon resonance. Once a plateau in evolution was reached, the isolated DNA sequences were cloned and sequenced. The consensus motif was identified via alignment of the sequences and the affinities of these sequences for immobilised ß-conglutin were determined using surface plasmon resonance. The selected aptamer was demonstrated to be highly specific, showing no cross-reactivity with other flour ingredients or with other conglutin fractions of lupin. The secondary structures of the selected aptamers were predicted using m-fold. Finally, the functionality of the selected aptamers was demonstrated using a competitive assay for the quantitative detection of ß-conglutin. . Future work will focus on structure elucidation and truncation of the selected sequences to generate a smaller aptamer for application to the analysis of the Lup an 1 allergen in foodstuffs

A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes

dentification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 x 10(-8)) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.Peer reviewe

Wavelet Methods For Curve Estimation

The theory of wavelets is a developing branch of mathematics with a wide range of potential applications. Compactly supported wavelets are particularly interesting because of their natural ability to represent data with intrinsically local properties. They are useful for the detection of edges and singularities in image and sound analysis, and for data compression. However, most of the wavelet based procedures currently available do not explicitly account for the presence of noise in the data. A discussion of how this can be done in the setting of some simple nonparametric curve estimation problems is given. Wavelet analogues of some familiar kernel and orthogonal series estimators are introduced and their finite sample and asymptotic properties are studied. We discover that there is a fundamental instability in the asymptotic variance of wavelet estimators caused by the lack of translation invariance of the wavelet transform. This is related to the properties of certain lacunary seq..

On Goodness-of-Fit Tests for Aalen's Additive Risk Model

In this paper we propose goodness-of-fit tests for Aalen's additive risk model. They are based on test statistics the asymptotic distributions of which are determined under both the null and alternative hypotheses. The results are derived using martingale techniques for counting processes. An important feature of these tests is that they can be adjusted to particular alternatives. One of the alternatives we consider is Cox's multiplicative risk model. It is perhaps remarkable that such a test needs no estimate of the baseline hazard in the Cox model. We present simulation studies which give an impression of the performance of the proposed tests. In addition, the tests are applied to real data sets. Copyright 2005 Board of the Foundation of the Scandinavian Journal of Statistics..

Likelihood Ratio Confidence Bands in Non-parametric Regression with Censored Data

Let (X, Y) be a random vector, where Y denotes the variable of interest possibly subject to random right censoring, and X is a covariate. We construct confidence intervals and bands for the conditional survival and quantile function of Y given X using a non-parametric likelihood ratio approach. This approach was introduced by Thomas & Grunkemeier (1975), who estimated confidence intervals of survival probabilities based on right censored data. The method is appealing for several reasons: it always produces intervals inside [0, 1], it does not involve variance estimation, and can produce asymmetric intervals. Asymptotic results for the confidence intervals and bands are obtained, as well as simulation results, in which the performance of the likelihood ratio intervals and bands is compared with that of the normal approximation method. We also propose a bandwidth selection procedure based on the bootstrap and apply the technique on a real data set