**Ventricular pressure-volume curve indices change with end-diastolic pressure.**

Many indices have been proposed to describee the diastolic pressure-volume curve mathematically and permit quantification of the elastic properties of the myocardium itself in hopes that changes in the muscle caused by disease would b.e reflected in the diastolic pressure-volume curve. To date, none of the proposed indices has been shown convincingly to discriminate one group of patients from another. While this situation in part arises from the relatively large amount of noise introduced by the technical difficulties of measuring synchronous pressures and volumes during diastole in man, ther is a more fundamental difficulty. In practice, one can measure only a short segment of the entire pressure-volume curve, and the values of all diastolic pressure-volume curve parameters investigated change significantly when one uses different segments of the same pressure-volume curve to compute them. These results were derived from relatively noise-free pressure-volume curves obtained by filling nine excised dog left ventricles at a known rate and monitoring pressure-volume curve used to compute the parameter. Merely increasing measurement fidelity will not resolve this problem, because none of these parameters accurately characterizes the entire diastolic pressure-volume curbe from a segment like that which one can reasonably expect to obtain from humans. (+info)

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**Testing for selective neutrality of electrophoretically detectable protein polymorphisms.**

The statistical assessment of gene-frequency data on protein polymorphisms in natural populations remains a contentious issue. Here we formulate a test of whether polymorphisms detected by electrophoresis are in accordance with the stepwise, or charge-state, model of mutation in finite populations in the absence of selection. First, estimates of the model parameters are derived by minimizing chi-square deviations of the observed frequencies of genotypes with alleles (0,1,2...) units apart from their theoretical expected values. Then the remaining deviation is tested under the null hypothesis of neutrality. The procedure was found to be conservative for false rejections in simulation data. We applied the test to Ayala and Tracey 's data on 27 allozymic loci in six populations of Drosophila willistoni . About one-quarter of polymorphic loci showed significant departure from the neutral theory predictions in virtually all populations. A further quarter showed significant departure in some populations. The remaining data showed an acceptable fit to the charge state model. A predominating mode of selection was selection against alleles associated with extreme electrophoretic mobilities. The advantageous properties and the difficulties of the procedure are discussed. (+info)

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**The significance of non-significance.**

We discuss the implications of empirical results that are statistically non-significant. Figures illustrate the interrelations among effect size, sample sizes and their dispersion, and the power of the experiment. All calculations (detailed in Appendix) are based on actual noncentral t-distributions, with no simplifying mathematical or statistical assumptions, and the contribution of each tail is determined separately. We emphasize the importance of reporting, wherever possible, the a priori power of a study so that the reader can see what the chances were of rejecting a null hypothesis that was false. As a practical alternative, we propose that non-significant inference be qualified by an estimate of the sample size that would be required in a subsequent experiment in order to attain an acceptable level of power under the assumption that the observed effect size in the sample is the same as the true effect size in the population; appropriate plots are provided for a power of 0.8. We also point out that successive outcomes of independent experiments each of which may not be statistically significant on its own, can be easily combined to give an overall p value that often turns out to be significant. And finally, in the event that the p value is high and the power sufficient, a non-significant result may stand and be published as such. (+info)

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**The Dictyostelium developmental cDNA project: generation and analysis of expressed sequence tags from the first-finger stage of development.**

In an effort to identify and characterize genes expressed during multicellular development ill Dictyostelium, we have undertaken a cDNA sequencing project. Using size-fractionated subsets of cDNA from the first finger stage, two sets of gridded libraries were constructed for cDNA sequencing. One, library S, consisting of 9984 clones, carries relatively short inserts, and the other, library L, which consists of 8448 clones, has longer inserts. We sequenced all the selected clones in library S from their 3'-ends, and this generated 3093 non-redundant, expressed sequence tags (ESTs). Among them, 246 ESTs hit known Dictyostelium genes and 910 showed significant similarity to genes of Dictyostelium and other organisms. For library L, 1132 clones were randomly sequenced and 471 non-redundant ESTs were obtained. In combination, the ESTs from the two libraries represent approximately 40% of genes expressed in late development, assuming that the non-redundant ESTs correspond to independent genes. They will provide a useful resource for investigating the genetic networks that regulate multicellular development of this organism. (+info)

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**The transmission/disequilibrium test and parental-genotype reconstruction: the reconstruction-combined transmission/ disequilibrium test.**

Spielman and Ewens recently proposed a method for testing a marker for linkage with a disease, which combines data from families with and without information on parental genotypes. For some families without parental-genotype information, it may be possible to reconstruct missing parental genotypes from the genotypes of their offspring. The treatment of such a reconstructed family as if parental genotypes have been typed, however, can introduce bias. In the present study, a new method is presented that employs parental-genotype reconstruction and corrects for the biases resulting from reconstruction. The results of an application of this method to a real data set and of a simulation study suggest that this approach may increase the power to detect linkage. (+info)

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**Analysis of affected sib pairs, with covariates--with and without constraints.**

Covariate models have previously been developed as an extension to affected-sib-pair methods in which the covariate effects are jointly estimated with the degree of excess allele sharing. These models can estimate the differences in sib-pair allele sharing that are associated with measurable environment or genes. When there are no covariates, the pattern of identical-by-descent allele sharing in affected sib pairs is expected to fall within a small triangular region of the potential parameter space, under most genetic models. By restriction of the estimated allele sharing to this triangle, improved power is obtained in tests for genetic linkage. When the affected-sib-pair model is generalized to allow for covariates that affect allele sharing, however, new constraints and new methods for the application of constraints are required. Three generalized constraint methods are proposed and evaluated by use of simulated data. The results compare the power of the different methods, with and without covariates, for a single-gene model with age-dependent onset and for quantitative and qualitative gene-environment and gene-gene interaction models. Covariates can improve the power to detect linkage and can be particularly valuable when there are qualitative gene-environment interactions. In most situations, the best strategy is to assume that there is no dominance variance and to obtain constrained estimates for covariate models under this assumption. (+info)

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**A parametric copula model for analysis of familial binary data.**

Modeling the joint distribution of a binary trait (disease) within families is a tedious challenge, owing to the lack of a general statistical model with desirable properties such as the multivariate Gaussian model for a quantitative trait. Models have been proposed that either assume the existence of an underlying liability variable, the reality of which cannot be checked, or provide estimates of aggregation parameters that are dependent on the ordering of family members and on family size. We describe how a class of copula models for the analysis of exchangeable categorical data can be incorporated into a familial framework. In this class of models, the joint distribution of binary outcomes is characterized by a function of the given marginals. This function, referred to as a "copula," depends on an aggregation parameter that is weakly dependent on the marginal distributions. We propose to decompose a nuclear family into two sets of equicorrelated data (parents and offspring), each of which is characterized by an aggregation parameter (alphaFM and alphaSS, respectively). The marginal probabilities are modeled through a logistic representation. The advantage of this model is that it provides estimates of the aggregation parameters that are independent of family size and does not require any arbitrary ordering of sibs. It can be incorporated easily into segregation or combined segregation-linkage analysis and does not require extensive computer time. As an illustration, we applied this model to a combined segregation-linkage analysis of levels of plasma angiotensin I-converting enzyme (ACE) dichotomized into two classes according to the median. The conclusions of this analysis were very similar to those we had reported in an earlier familial analysis of quantitative ACE levels. (+info)

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**Parental hyperdynamic circulation predicts insulin resistance in offspring: The Tecumseh Offspring Study.**

Controversy surrounds the pathogenetic mechanisms of the relationship between hyperdynamic circulation and insulin resistance. Two hundred eight children and young adults (mean age, 17.2+/-3.0 years; range, 11 to 26 years) from the Tecumseh Offspring Study whose parents had been assessed with Doppler echocardiography at the age of 34 years during the previous Tecumseh Blood Pressure Study were considered for this analysis. Offspring data were stratified according to tertiles of parental cardiac index. Parents in the top cardiac index tertile had increased heart rate (P=0.001), stroke volume (P=0.0001), left ventricular fractional shortening (P=0.02), and plasma epinephrine (P=0.02) compared with parents in the other tertiles. Body mass index (BMI) and blood pressure were similar in all groups. Offspring of parents with a high cardiac index had greater BMI (P=0.001), skinfold thickness (P=0.008), and waist/hip ratio (P=0.02), higher diastolic blood pressure (P=0.02) and plasma insulin level (P=0.001), and higher heart rate during Stroop's color test (P=0.02) than offspring of parents with a lower cardiac index. In a multivariate regression analysis, offspring BMI was predicted by parental BMI and cardiac index (P=0.0001 and 0.003, respectively). The mother-child relationship explained most of the cardiac index-BMI association. In summary, parental hyperdynamic circulation was an important predictor of overweight, abnormal fat distribution, increased blood pressure, and hyperinsulinemia in offspring. Our results illustrate the complexity of interaction between a genetic tendency and its phenotypic expression. We speculate that the degree of beta-adrenergic responsiveness may be a major determinant of the phenotypic differences between the parents and offspring found in this study. (+info)