195 research outputs found
Modeling association between DNA copy number and gene expression with constrained piecewise linear regression splines
DNA copy number and mRNA expression are widely used data types in cancer
studies, which combined provide more insight than separately. Whereas in
existing literature the form of the relationship between these two types of
markers is fixed a priori, in this paper we model their association. We employ
piecewise linear regression splines (PLRS), which combine good interpretation
with sufficient flexibility to identify any plausible type of relationship. The
specification of the model leads to estimation and model selection in a
constrained, nonstandard setting. We provide methodology for testing the effect
of DNA on mRNA and choosing the appropriate model. Furthermore, we present a
novel approach to obtain reliable confidence bands for constrained PLRS, which
incorporates model uncertainty. The procedures are applied to colorectal and
breast cancer data. Common assumptions are found to be potentially misleading
for biologically relevant genes. More flexible models may bring more insight in
the interaction between the two markers.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS605 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Better prediction by use of co-data: Adaptive group-regularized ridge regression
For many high-dimensional studies, additional information on the variables,
like (genomic) annotation or external p-values, is available. In the context of
binary and continuous prediction, we develop a method for adaptive
group-regularized (logistic) ridge regression, which makes structural use of
such 'co-data'. Here, 'groups' refer to a partition of the variables according
to the co-data. We derive empirical Bayes estimates of group-specific
penalties, which possess several nice properties: i) they are analytical; ii)
they adapt to the informativeness of the co-data for the data at hand; iii)
only one global penalty parameter requires tuning by cross-validation. In
addition, the method allows use of multiple types of co-data at little extra
computational effort.
We show that the group-specific penalties may lead to a larger distinction
between `near-zero' and relatively large regression parameters, which
facilitates post-hoc variable selection. The method, termed GRridge, is
implemented in an easy-to-use R-package. It is demonstrated on two cancer
genomics studies, which both concern the discrimination of precancerous
cervical lesions from normal cervix tissues using methylation microarray data.
For both examples, GRridge clearly improves the predictive performances of
ordinary logistic ridge regression and the group lasso. In addition, we show
that for the second study the relatively good predictive performance is
maintained when selecting only 42 variables.Comment: 15 pages, 2 figures. Supplementary Information available on first
author's web sit
Diffusion of hydrogen in crystalline silicon
The coefficient of diffusion of hydrogen in crystalline silicon is calculated
using tight-binding molecular dynamics. Our results are in good quantitative
agreement with an earlier study by Panzarini and Colombo [Phys. Rev. Lett. 73,
1636 (1994)]. However, while our calculations indicate that long jumps dominate
over single hops at high temperatures, no abrupt change in the diffusion
coefficient can be observed with decreasing temperature. The (classical)
Arrhenius diffusion parameters, as a consequence, should extrapolate to low
temperatures.Comment: 4 pages, including 5 postscript figures; submitted to Phys. Rev. B
Brief Repor
Magnetic properties of Sm-Co thin films grown on MgO(100) deposited from a single alloy target
Quantum Matter and Optic
Agonist signalling properties of radiotracers used for imaging of dopamine D-2/3 receptors
Background: Dopamine D-2/3 receptor (D2/3R) agonist radiopharmaceuticals are considered superior to antagonists to detect dopamine release, e.g. induced by amphetamines. Agonists bind preferentially to the high-affinity state of the dopamine D2R, which has been proposed as the reason why agonists are more sensitive to detect dopamine release than antagonist radiopharmaceuticals, but this theory has been challenged. Interestingly, not all agonists similarly activate the classic cyclic adenosine mono phosphate (cAMP) and the beta-arrestin-2 pathway, some stimulate preferentially one of these pathways; a phenomenon called biased agonism. Because these pathways can be affected separately by pathologies or drugs (including dopamine releasers), it is important to know how agonist radiotracers act on these pathways. Therefore, we characterized the intracellular signalling of the well-known D2/3R agonist radiopharmaceuticals NPA and PHNO and of several novel D2/3R agonists. Methods: cAMP accumulation and beta-arrestin-2 recruitment were measured on cells expressing human D2R. Results: All tested agonists showed (almost) full agonism in both pathways. Conclusions: The tested D2/3R agonist radiopharmaceuticals did not exhibit biased agonism in vitro. Consequently, it is likely that drugs (including psychostimulants like amphetamines) and/or pathologies that influence the cAMP and/or the beta-arrestin-2 pathway may influence the binding of these radiopharmaceuticals
4H Leukodystrophy: A Brain Magnetic Resonance Imaging Scoring System
4H (hypomyelination, hypodontia and hypogonadotropic hypogonadism) leukodystrophy (4H) is an autosomal recessive hypomyelinating white matter (WM) disorder with neurologic, dental, and endocrine abnormalities. The aim of this study was to develop and validate a magnetic resonance imaging (MRI) scoring system for 4H. A scoring system (0-54) was developed to quantify hypomyelination and atrophy of different brain regions. Pons diameter and bicaudate ratio were included as measures of cerebral and brainstem atrophy, and reference values were determined using controls. Five independent raters completed the scoring system in 40 brain MRI scans collected from 36 patients with genetically proven 4H. Interrater reliability (IRR) and correlations between MRI scores, age, gross motor function, gender, and mutated gene were assessed. IRR for total MRI severity was found to be excellent (intraclass correlation coefficient: 0.87; 95% confidence interval: 0.80-0.92) but varied between different items with some (e.g., myelination of the cerebellar WM) showing poor IRR. Atrophy increased with age in contrast to hypomyelination scores. MRI scores (global, hypomyelination, and atrophy scores) significantly correlated with clinical handicap (p < 0.01 for all three items) and differed between the different genotypes. Our 4H MRI scoring system reliably quantifies hypomyelination and atrophy in patients with 4H, and MRI scores reflect clinical disease severity
On dynamic network entropy in cancer
The cellular phenotype is described by a complex network of molecular
interactions. Elucidating network properties that distinguish disease from the
healthy cellular state is therefore of critical importance for gaining
systems-level insights into disease mechanisms and ultimately for developing
improved therapies. By integrating gene expression data with a protein
interaction network to induce a stochastic dynamics on the network, we here
demonstrate that cancer cells are characterised by an increase in the dynamic
network entropy, compared to cells of normal physiology. Using a fundamental
relation between the macroscopic resilience of a dynamical system and the
uncertainty (entropy) in the underlying microscopic processes, we argue that
cancer cells will be more robust to random gene perturbations. In addition, we
formally demonstrate that gene expression differences between normal and cancer
tissue are anticorrelated with local dynamic entropy changes, thus providing a
systemic link between gene expression changes at the nodes and their local
network dynamics. In particular, we also find that genes which drive
cell-proliferation in cancer cells and which often encode oncogenes are
associated with reductions in the dynamic network entropy. In summary, our
results support the view that the observed increased robustness of cancer cells
to perturbation and therapy may be due to an increase in the dynamic network
entropy that allows cells to adapt to the new cellular stresses. Conversely,
genes that exhibit local flux entropy decreases in cancer may render cancer
cells more susceptible to targeted intervention and may therefore represent
promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte
PIN71 QUALITY OF LIFE (QOL) AND OTHER ENDPOINTS COMPARISON IN THE TREATMENT OF FACIAL LIPOATROPHY WITH INJECTION OF POLY-L-LACTIC ACID
Context: Longitudinal data on bone mineral density(BMD) in children and adolescents with Prader-Willi Syndrome (PWS) during long-term GH treatment are not available. Objective: This study aimed to determine effects of long-term GH treatment and puberty on BMD of total body (BMDTB), lumbar spine (BMDLS), and bone mineral apparent density of the lumbar spine (BMAD(LS)) in children with PWS. Design and Setting: This was a prospective longitudinal study of a Dutch PWS cohort. Participants: Seventy-seven children with PWS who remained prepubertal during GH treatment for 4 years and 64 children with PWS who received GH treatment for 9 years participated in the study. Intervention: The children received GH treatment, 1 mg/m(2)/day (congruent to 0.035 mg/kg/d). Main Outcome Measures: BMDTB, BMDLS, and BMAD(LS) was measured by using the same dual-energy x-ray absorptiometry machine for all annual measurements. Results: In the prepubertal group, BMDTB standard deviation score (SDS) and BMDLSSDS significantly increased during 4 years of GH treatment whereas BMAD(LS)SDS remained stable. During adolescence, BMDTBSDS and BMAD(LS)SDS decreased significantly, in girls from the age of 11 years and in boys from the ages of 14 and 16 years, respectively, but all BMD parameters remained within the normal range. Higher Tanner stages tended to be associated with lower BMDTBSDS (P = .083) and a significantly lowerBMAD(LS)SDS (P = .016). After 9 years of GH treatment, lean body mass SDS was the most powerful predictor of BMDTBSDS and BMDLSSDS in adolescents with PWS. Conclusions: This long-term GH study demonstrates that BMDTB, BMDLS, and BMAD(LS) remain stable in prepubertal children with PWS but decreases during adolescence, parallel to incomplete pubertal development. Based on our findings, clinicians should start sex hormone therapy from the age of 11 years in girls and 14 years in boys unless there is a normal progression of puberty
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