Kernel Estimation of Rate Function for Recurrent Event Data

Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we study statistical properties of the proposed estimators and propose bootstrap procedures for the bandwidth selection and for the approximation of confidence intervals in the estimation of the occurrence rate function. It is identified that the moment method without resmoothing via a smaller bandwidth will produce curve with nicks occurring at the censoring times, whereas there is no such problem with the least squares method. Furthermore, the asymptotic variance of the least squares estimator is shown to be smaller under regularity conditions. However, in the implementation of the bootstrap procedures, the moment method is computationally more efficient than the least squares method because the former approach uses condensed bootstrap data. The performance of the proposed procedures is studied through Monte Carlo simulations and an epidemiological example on intravenous drug users.

Genetic maps of the proximal half of chromosome arm 2L of Drosophila melanogaster

Drosophila mutants have played an important role in elucidating the physiologic function of genes. Large-scale projects have succeeded in producing mutations in a large proportion of Drosophila genes. Many mutant fly lines have also been produced through the efforts of individual laboratories over the past century. In an effort to make some of these mutants more useful to the research community, we systematically mapped a large number of mutations affecting genes in the proximal half of chromosome arm 2L to more precisely defined regions, defined by deficiency intervals, and, when possible, by individual complementation groups. To further analyze regions 36 and 39-40, we produced 11 new deficiencies with gamma irradiation, and we constructed 6 new deficiencies in region 30-33, using the DrosDel system. trans-heterozygous combinations of deficiencies revealed 5 additional functions, essential for viability or fertility.

Genetic Variation and Population Structure in Native Americans

We examined genetic diversity and population structure in the American landmass using 678 autosomal microsatellite markers genotyped in 422 individuals representing 24 Native American populations sampled from North, Central, and South America. These data were analyzed jointly with similar data available in 54 other indigenous populations worldwide, including an additional five Native American groups. The Native American populations have lower genetic diversity and greater differentiation than populations from other continental regions. We observe gradients both of decreasing genetic diversity as a function of geographic distance from the Bering Strait and of decreasing genetic similarity to Siberians-signals of the southward dispersal of human populations from the northwestern tip of the Americas. We also observe evidence of: (1) a higher level of diversity and lower level of population structure in western South America compared to eastern South America, (2) a relative lack of differentiation between Mesoamerican and Andean populations, (3) a scenario in which coastal routes were easier for migrating peoples to traverse in comparison with inland routes, and (4) a partial agreement on a local scale between genetic similarity and the linguistic classification of populations. These findings offer new insights into the process of population dispersal and differentiation during the peopling of the Americas.

Non-invasive gene-expression-based detection of well-developed collateral function in individuals with and without coronary artery disease

BACKGROUND: In patients with coronary artery disease (CAD), a well grown collateral circulation has been shown to be important. The aim of this prospective study using peripheral blood monocytes was to identify marker genes for an extensively grown coronary collateral circulation. METHODS: Collateral flow index (CFI) was obtained invasively by angioplasty pressure sensor guidewire in 160 individuals (110 patients with CAD, and 50 individuals without CAD). RNA was extracted from monocytes followed by microarray-based gene-expression analysis. 76 selected genes were analysed by real-time polymerase chain reaction (PCR). A receiver operating characteristics analysis based on differential gene expression was then performed to separate individuals with poor (CFI<0.21) and well-developed collaterals (CFI>or=0.21) Thereafter, the influence of the chemokine MCP-1 on the expression of six selected genes was tested by PCR. RESULTS: The expression of 203 genes significantly correlated with CFI (p = 0.000002-0.00267) in patients with CAD and 56 genes in individuals without CAD (p = 00079-0.0430). Biological pathway analysis revealed 76 of those genes belonging to four different pathways: angiogenesis, integrin-, platelet-derived growth factor-, and transforming growth factor beta-signalling. Three genes in each subgroup differentiated with high specificity among individuals with low and high CFI (>or=0.21). Two out of these genes showed pronounced differential expression between the two groups after cell stimulation with MCP-1. CONCLUSIONS: Genetic factors play a role in the formation and the preformation of the coronary collateral circulation. Gene expression analysis in peripheral blood monocytes can be used for non-invasive differentiation between individuals with poorly and with well grown collaterals. MCP-1 can influence the arteriogenic potential of monocytes.

Control design and genetic algorithm optimization for electrostatic MEMS

This dissertation discusses structural-electrostatic modeling techniques, genetic algorithm based optimization and control design for electrostatic micro devices. First, an alternative modeling technique, the interpolated force model, for electrostatic micro devices is discussed. The method provides improved computational efficiency relative to a benchmark model, as well as improved accuracy for irregular electrode configurations relative to a common approximate model, the parallel plate approximation model. For the configuration most similar to two parallel plates, expected to be the best case scenario for the approximate model, both the parallel plate approximation model and the interpolated force model maintained less than 2.2% error in static deflection compared to the benchmark model. For the configuration expected to be the worst case scenario for the parallel plate approximation model, the interpolated force model maintained less than 2.9% error in static deflection while the parallel plate approximation model is incapable of handling the configuration. Second, genetic algorithm based optimization is shown to improve the design of an electrostatic micro sensor. The design space is enlarged from published design spaces to include the configuration of both sensing and actuation electrodes, material distribution, actuation voltage and other geometric dimensions. For a small population, the design was improved by approximately a factor of 6 over 15 generations to a fitness value of 3.2 fF. For a larger population seeded with the best configurations of the previous optimization, the design was improved by another 7% in 5 generations to a fitness value of 3.0 fF. Third, a learning control algorithm is presented that reduces the closing time of a radiofrequency microelectromechanical systems switch by minimizing bounce while maintaining robustness to fabrication variability. Electrostatic actuation of the plate causes pull-in with high impact velocities, which are difficult to control due to parameter variations from part to part. A single degree-of-freedom model was utilized to design a learning control algorithm that shapes the actuation voltage based on the open/closed state of the switch. Experiments on 3 test switches show that after 5-10 iterations, the learning algorithm lands the switch with an impact velocity not exceeding 0.2 m/s, eliminating bounce.

Space trajectories optimization using variable-chromosome-length genetic algorithms

The problem of optimal design of a multi-gravity-assist space trajectories, with free number of deep space maneuvers (MGADSM) poses multi-modal cost functions. In the general form of the problem, the number of design variables is solution dependent. To handle global optimization problems where the number of design variables varies from one solution to another, two novel genetic-based techniques are introduced: hidden genes genetic algorithm (HGGA) and dynamic-size multiple population genetic algorithm (DSMPGA). In HGGA, a fixed length for the design variables is assigned for all solutions. Independent variables of each solution are divided into effective and ineffective (hidden) genes. Hidden genes are excluded in cost function evaluations. Full-length solutions undergo standard genetic operations. In DSMPGA, sub-populations of fixed size design spaces are randomly initialized. Standard genetic operations are carried out for a stage of generations. A new population is then created by reproduction from all members based on their relative fitness. The resulting sub-populations have different sizes from their initial sizes. The process repeats, leading to increasing the size of sub-populations of more fit solutions. Both techniques are applied to several MGADSM problems. They have the capability to determine the number of swing-bys, the planets to swing by, launch and arrival dates, and the number of deep space maneuvers as well as their locations, magnitudes, and directions in an optimal sense. The results show that solutions obtained using the developed tools match known solutions for complex case studies. The HGGA is also used to obtain the asteroids sequence and the mission structure in the global trajectory optimization competition (GTOC) problem. As an application of GA optimization to Earth orbits, the problem of visiting a set of ground sites within a constrained time frame is solved. The J2 perturbation and zonal coverage are considered to design repeated Sun-synchronous orbits. Finally, a new set of orbits, the repeated shadow track orbits (RSTO), is introduced. The orbit parameters are optimized such that the shadow of a spacecraft on the Earth visits the same locations periodically every desired number of days.

Use of concatamers to study GABAA receptor architecture and function: application to delta-subunit-containing receptors and possible pitfalls

Many membrane proteins, including the GABA(A) [GABA (gamma-aminobutyric acid) type A] receptors, are oligomers often built from different subunits. As an example, the major adult isoform of the GABA(A) receptor is a pentamer built from three different subunits. Theoretically, co-expression of three subunits may result in many different receptor pentamers. Subunit concatenation allows us to pre-define the relative arrangement of the subunits. This method may thus be used to study receptor architecture, but also the nature of binding sites. Indeed, it made possible the discovery of a novel benzodiazepine site. We use here subunit concatenation to study delta-subunit-containing GABA(A) receptors. We provide evidence for the formation of different functional subunit arrangements in recombinant alpha(1)beta(3)delta and alpha(6)beta(3)delta receptors. As with all valuable techniques, subunit concatenation has also some pitfalls. Most of these can be avoided by carefully titrating and minimizing the length of the linker sequences joining the two linked subunits and avoiding inclusion of the signal sequence of all but the N-terminal subunit of a multi-subunit construct. Maybe the most common error found in the literature is that low expression can be overcome by simply overloading the expression system with genetic information. As some concatenated constructs result by themselves in a low level of expression, this erroneous assembly leading to receptor function may be promoted by overloading the expression system and leads to wrong conclusions.

In vivo analysis of efavirenz metabolism in individuals with impaired CYP2A6 function

INTRODUCTION: The antiretroviral drug efavirenz (EFV) is extensively metabolized into three primary metabolites: 8-hydroxy-EFV, 7-hydroxy-EFV and N-glucuronide-EFV. There is a wide interindividual variability in EFV plasma exposure, explained to a great extent by cytochrome P450 2B6 (CYP2B6), the main isoenzyme responsible for EFV metabolism and involved in the major metabolic pathway (8-hydroxylation) and to a lesser extent in 7-hydroxylation. When CYP2B6 function is impaired, the relevance of CYP2A6, the main isoenzyme responsible for 7-hydroxylation may increase. We hypothesize that genetic variability in this gene may contribute to the particularly high, unexplained variability in EFV exposure in individuals with limited CYP2B6 function. METHODS: This study characterized CYP2A6 variation (14 alleles) in individuals (N=169) previously characterized for functional variants in CYP2B6 (18 alleles). Plasma concentrations of EFV and its primary metabolites (8-hydroxy-EFV, 7-hydroxy-EFV and N-glucuronide-EFV) were measured in different genetic backgrounds in vivo. RESULTS: The accessory metabolic pathway CYP2A6 has a critical role in limiting drug accumulation in individuals characterized as CYP2B6 slow metabolizers. CONCLUSION: Dual CYP2B6 and CYP2A6 slow metabolism occurs at significant frequency in various human populations, leading to extremely high EFV exposure.

Copy number variation of the Beta-defensin genes in europeans: no supporting evidence for association with lung function, chronic obstructive pulmonary disease or asthma

Lung function measures are heritable, predict mortality and are relevant in diagnosis of chronic obstructive pulmonary disease (COPD). COPD and asthma are diseases of the airways with major public health impacts and each have a heritable component. Genome-wide association studies of SNPs have revealed novel genetic associations with both diseases but only account for a small proportion of the heritability. Complex copy number variation may account for some of the missing heritability. A well-characterised genomic region of complex copy number variation contains beta-defensin genes (DEFB103, DEFB104 and DEFB4), which have a role in the innate immune response. Previous studies have implicated these and related genes as being associated with asthma or COPD. We hypothesised that copy number variation of these genes may play a role in lung function in the general population and in COPD and asthma risk. We undertook copy number typing of this locus in 1149 adult and 689 children using a paralogue ratio test and investigated association with COPD, asthma and lung function. Replication of findings was assessed in a larger independent sample of COPD cases and smoking controls. We found evidence for an association of beta-defensin copy number with COPD in the adult cohort (OR = 1.4, 95%CI:1.02-1.92, P = 0.039) but this finding, and findings from a previous study, were not replicated in a larger follow-up sample(OR = 0.89, 95%CI:0.72-1.07, P = 0.217). No robust evidence of association with asthma in children was observed. We found no evidence for association between beta-defensin copy number and lung function in the general populations. Our findings suggest that previous reports of association of beta-defensin copy number with COPD should be viewed with caution. Suboptimal measurement of copy number can lead to spurious associations. Further beta-defensin copy number measurement in larger sample sizes of COPD cases and children with asthma are needed.

Thermal 2-loop master spectral function at finite momentum

When considering NLO corrections to thermal particle production in the “relativistic” regime, in which the invariant mass squared of the produced particle is K2 ~ (πT)2, then the production rate can be expressed as a sum of a few universal “master” spectral functions. Taking the most complicated 2-loop master as an example, a general strategy for obtaining a convergent 2-dimensional integral representation is suggested. The analysis applies both to bosonic and fermionic statistics, and shows that for this master the non-relativistic approximation is only accurate for K2 ~(8πT)2, whereas the zero-momentum approximation works surprisingly well. Once the simpler masters have been similarly resolved, NLO results for quantities such as the right-handed neutrino production rate from a Standard Model plasma or the dilepton production rate from a QCD plasma can be assembled for K2 ~ (πT)2.

Interaction between effects of genes coding for dopamine and glutamate transmission on striatal and parahippocampal function

The genes for the dopamine transporter (DAT) and the D-Amino acid oxidase activator (DAOA or G72) have been independently implicated in the risk for schizophrenia and in bipolar disorder and/or their related intermediate phenotypes. DAT and G72 respectively modulate central dopamine and glutamate transmission, the two systems most robustly implicated in these disorders. Contemporary studies have demonstrated that elevated dopamine function is associated with glutamatergic dysfunction in psychotic disorders. Using functional magnetic resonance imaging we examined whether there was an interaction between the effects of genes that influence dopamine and glutamate transmission (DAT and G72) on regional brain activation during verbal fluency, which is known to be abnormal in psychosis, in 80 healthy volunteers. Significant interactions between the effects of G72 and DAT polymorphisms on activation were evident in the striatum, parahippocampal gyrus, and supramarginal/angular gyri bilaterally, the right insula, in the right pre-/postcentral and the left posterior cingulate/retrosplenial gyri (P < 0.05, FDR-corrected across the whole brain). This provides evidence that interactions between the dopamine and the glutamate system, thought to be altered in psychosis, have an impact in executive processing which can be modulated by common genetic variation.

Population amalgamation and genetic variation: observations on artificially agglomerated tribal populations of Central and South America.

The interpretation of data on genetic variation with regard to the relative roles of different evolutionary factors that produce and maintain genetic variation depends critically on our assumptions concerning effective population size and the level of migration between neighboring populations. In humans, recent population growth and movements of specific ethnic groups across wide geographic areas mean that any theory based on assumptions of constant population size and absence of substructure is generally untenable. We examine the effects of population subdivision on the pattern of protein genetic variation in a total sample drawn from an artificial agglomerate of 12 tribal populations of Central and South America, analyzing the pooled sample as though it were a single population. Several striking findings emerge. (1) Mean heterozygosity is not sensitive to agglomeration, but the number of different alleles (allele count) is inflated, relative to neutral mutation/drift/equilibrium expectation. (2) The inflation is most serious for rare alleles, especially those which originally occurred as tribally restricted "private" polymorphisms. (3) The degree of inflation is an increasing function of both the number of populations encompassed by the sample and of the genetic divergence among them. (4) Treating an agglomerated population as though it were a panmictic unit of long standing can lead to serious biases in estimates of mutation rates, selection pressures, and effective population sizes. Current DNA studies indicate the presence of numerous genetic variants in human populations. The findings and conclusions of this paper are all fully applicable to the study of genetic variation at the DNA level as well.

A loss-of-function variant of PTPN22 is associated with reduced risk of systemic lupus erythematosus.

A gain-of-function R620W polymorphism in the PTPN22 gene, encoding the lymphoid tyrosine phosphatase LYP, has recently emerged as an important risk factor for human autoimmunity. Here we report that another missense substitution (R263Q) within the catalytic domain of LYP leads to reduced phosphatase activity. High-resolution structural analysis revealed the molecular basis for this loss of function. Furthermore, the Q263 variant conferred protection against human systemic lupus erythematosus, reinforcing the proposal that inhibition of LYP activity could be beneficial in human autoimmunity.