We consider the problem of estimating the proportion of true null hypotheses, "π" 0, in a multiple-hypothesis set-up. The tests are based on observed "p"-values. We first review published estimators based on the estimator that was suggested by Schweder and Spjøtvoll. Then we derive new estimators based on nonparametric maximum likelihood estimation of the "p"-value density, restricting to decreasing and convex decreasing densities. The estimators of "π" 0 are all derived under the assumption of independent test statistics. Their performance under dependence is investigated in a simulation study. We find that the estimators are relatively robust with respect to the assumption of independence and work well also for test statistics with moderate dependence. Copyright 2005 Royal Statistical Society.

This study evaluates the role of postterm age at assessment and the use of one or two video recordings for the detection of fidgety movements (FMs) and prediction of cerebral palsy (CP) using computer vision software. Recordings between 9 and 17 weeks postterm age from 52 preterm and term infants (24 boys, 28 girls; 26 born preterm) were used. Recordings were analyzed using computer vision software. Movement variables, derived from differences between subsequent video frames, were used for quantitative analysis. Sensitivities, specificities, and area under curve were estimated for the first and second recording, or a mean of both. FMs were classified based on the Prechtl approach of general movement assessment. CP status was reported at 2 years. Nine children developed CP of whom all recordings had absent FMs. The mean variability of the centroid of motion (C SD ) from two recordings was more accurate than using only one recording, and identified all children who were diagnosed with CP at 2 years. Age at assessment did not influence the detection of FMs or prediction of CP. The accuracy of computer vision techniques in identifying FMs and predicting CP based on two recordings should be confirmed in future studies.

Background: Modern biology has shifted from "one gene" approaches to methods for genomic-scale analysis like microarray technology, which allow simultaneous measurement of thousands of genes. This has created a need for tools facilitating interpretation of biological data in "batch" mode. However, such tools often leave the investigator with large volumes of apparently unorganized information. To meet this interpretation challenge, gene-set, or cluster testing has become a popular analytical tool. Many gene-set testing methods and software packages are now available, most of which use a variety of statistical tests to assess the genes in a set for biological information. However, the field is still evolving, and there is a great need for "integrated" solutions.

Background: A limiting factor of cDNA microarray technology is the need for a substantial amount of RNA per labeling reaction. Thus, 20-200 micro-grams total RNA or 0.5-2 micro-grams poly (A) RNA is typically required for monitoring gene expression. In addition, gene expression profiles from large, heterogeneous cell populations provide complex patterns from which biological data for the target cells may be difficult to extract. In this study, we chose to investigate a widely used mRNA amplification protocol that allows gene expression studies to be performed on samples with limited starting material. We present a quantitative study of the variation and noise present in our data set obtained from experiments with either amplified or non-amplified material.

Aerobic capacity is a strong predictor of cardiovascular mortality. To determine the relationship between inborn aerobic capacity and cardiac gene expression we examined genome-wide gene expression in hearts of rats artificially selected for high and low running capacity (HCR and LCR, respectively) over 16 generations. The artificial selection of LCR caused accumulation of risk factors of cardiovascular disease similar to the metabolic syndrome seen in human, whereas HCR had markedly better cardiac function. We also studied alterations in gene expression in response to exercise training in these animals. Left ventricle gene expression of both sedentary and exercise-trained HCR and LCR was characterized by microarray and gene ontology analysis. Out of 28,000 screened genes, 1,540 were differentially expressed between sedentary HCR and LCR. Only one gene was found differentially expressed by exercise training, but this gene had unknown name and function. Sedentary HCR expressed higher amounts of genes involved in lipid metabolism, whereas sedentary LCR expressed higher amounts of the genes involved in glucose metabolism. This suggests a switch in cardiac energy substrate utilization from normal mitochondrial fatty acid ␤-oxidation in HCR to carbohydrate metabolism in LCR, an event that often occurs in diseased hearts. LCR were also associated with pathological growth signaling and cellular stress. Hypoxic conditions seemed to be a common source for several of these observations, triggering hypoxia-induced alterations of transcription. In conclusion, inborn high vs. low aerobic capacity was associated with differences in cardiac energy substrate, growth signaling, and cellular stress. metabolic syndrome; metabolism; hypoxia; V O2max; hypertrophy ALTHOUGH MAXIMAL OXYGEN UPTAKE (V O 2max ) is statistically linked with cardiovascular mortality (23, 36), the mechanistic nature of this association is unknown and difficult to explore in humans. Specifically, it is well defined that the continuum of heart function is linearly related with the level of V O 2max (39). Within the gene-environment interactions, inheritance may account for as much as 70% of the variation in aerobic capacity in human (7). Hence, genetic predisposition and inborn aerobic capacity are likely to contribute toward cardiovascular disease and mortality.Rats with different inborn running capacities have been artificially selected over generations to generate strains with genetically determined high or low intrinsic capacity (25). The evolved strains of high capacity runners (HCR) and low capacity runners (LCR) have a 30% difference in V O 2max (17). Selecting for low running capacity also resulted in accumulation of risk factors that predispose to cardiovascular disease. That is, LCR have features of the metabolic syndrome, whereas HCR show an athletic phenotype with markedly better cardiac and vascular function relative to LCR (17, 52). These models were generated expressly for efficient and invasive evaluation of cardiometabolic disease that can lea...

Continued ASA treatment until the time of CABG reduced oxidative and inflammatory responses. Also, a likely beneficial effect upon myocardial injury was noticed. Although none of the genes known to be involved in oxidative stress or inflammation took a different expression in myocardial tissue, the genetic analysis showed interesting differences in the mRNA level. Further research in this field is necessary to understand the role of the genes.

BackgroundOur aim was to assess the influence of age, gender and lifestyle factors on the effect of the obesity-promoting alleles of FTO and MCR4.MethodsThe HUNT study comprises health information on the population of Nord-Trøndelag county, Norway. Extreme phenotype participants (gender-wise lower and upper quartiles of waist-hip-ratio and BMI ≥ 35 kg/m2) in the third survey, HUNT3 (2006–08), were genotyped for the single-nucleotide polymorphisms rs9939609 (FTO) and rs17782313 (MC4R); 25686 participants were successfully genotyped. Extreme sampling was chosen to increase power to detect genetic and gene-environment effects on waist-hip-ratio and BMI. Statistical inference was based on linear regression models and a missing-covariate likelihood approach for the extreme phenotype sampling design. Environmental factors were physical activity, diet (artificially sweetened beverages) and smoking. Longitudinal analysis was performed using material from HUNT2 (1995–97).ResultsCross-sectional and longitudinal genetic effects indicated stronger genetic associations with obesity in young than in old, as well as differences between women and men. We observed larger genetic effects among physically inactive compared to active individuals. This interaction was age-dependent and seen mainly in 20–40 year olds. We observed a greater FTO effect among men with a regular intake of artificially sweetened beverages, compared to non-drinkers. Interaction analysis of smoking was mainly inconclusive.ConclusionsIn a large all-adult and area-based population survey the effects of obesity-promoting minor-alleles of FTO and MCR4, and interactions with life style factors are age- and gender-related. These findings appear relevant when designing individualized treatment for and prophylaxis against obesity.

We report a strategy for analysis of data quality in cDNA microarrays based on the repeatability of repeatedly spotted clones. We describe how repeatability can be used to control data quality by developing adaptive filtering criteria for microarray data containing clones spotted in multiple spots. We have applied the method on five publicly available cDNA microarray data sets and one previously unpublished data set from our own laboratory. The results demonstrate the feasibility of the approach as a foundation for data filtering, and indicate a high degree of variation in data quality, both across the data sets and between arrays within data sets.