Effects of Organic Solvents on the Coupling Between ATP Hydrolysis and Sliding of Microtubules in Axonemes from Chlamydomonas Flagella

ABSTRACT. The effects of organic solvents on the ATPase activity and the sliding disintegration of axonemes from Chlamydomonas were investigated. The axonemal ATPase was markedly activated by methanol accompanying with marked inhibition of the sliding disintegration of axonemes. On the contrary, glycerol inhibited the ATPase activity without serious inhibition of the sliding disintegration. As far as the axonemes are not irreversibly denatured by extremely high concentration of solvents, the effects of solvents both on the ATPase and the ability of sliding are reversible. Therefore, the inhibition of sliding accompanied by the activation of ATPase is probably due to an inability to couple the hydrolysis of ATP to sliding between dynein and microtubule in the presence of methanol. The axonemal ATPase was less sensitive to vanadate inhibition after exposure to methanol. This indicates that methanol makes the dyneinADP.Pi complex unstable and increases product release. On the other hand, glycerol and ethylene glycol seem to stabilize the force generation responsible for the sliding through stabilizing the dynein.ADP.Pi complex.     

The Treatment of Missing Values in Logistic Regression

The efficiencies of the estimators in the linear logistic regression model are examined using simulations under six missing value treatments. These treatments use either the maximum likelihood or the discriminant function approach in the estimation of the regression coefficients. Missing values are assumed to occur at random. The cases of multivariate normal and dichotomous independent variables are both considered. We found that in general, there is no uniformly best method. However, mean substitution and discriminant function estimation using existing pairs of values for correlations turn out to be favourable for the cases considered.     

The Monofactorial Model for Recurrence Risks with Generalized Penetrance

Recurrence risks are derived explicitly in terms of gene frequencies and penetrance coefficients for the general case in which all genotypes have incomplete penetrance. Maximum likelihood estimation of recurrence risks is achieved through the use of the semi-symmetric intraclass contingency table. The resulting formulas and estimation procedure can be useful for the analysis of population and family data, and in genetic counselling.     

EVOLUTION AND EXTINCTION IN A CHANGING ENVIRONMENT: A QUANTITATIVE-GENETIC ANALYSIS

Because of the ubiquity of genetic variation for quantitative traits, virtually all populations have some capacity to respond evolutionarily to selective challenges. However, natural selection imposes demographic costs on a population, and if these costs are sufficiently large, the likelihood of extinction will be high. We consider how the mean time to extinction depends on selective pressures (rate and stochasticity of environmental change, and strength of selection), population parameters (carrying capacity, and reproductive capacity), and genetics (rate of polygenic mutation). We assume that in a randomly mating, finite population subject to density-dependent population growth, individual fitness is determined by a single quantitative-genetic character under Gaussian stabilizing selection with the optimum phenotype exhibiting directional change, or random fluctuations, or both. The quantitative trait is determined by a finite number of freely recombining, mutationally equivalent, additive loci. The dynamics of evolution and extinction are investigated, assuming that the population is initially under mutation-selection-drift balance. Under this model, in a directionally changing environment, the mean phenotype lags behind the optimum, but on the average evolves parallel to it. The magnitude of the lag determines the vulnerability to extinction. In finite populations, stochastic variation in the genetic variance can be quite pronounced, and bottlenecks in the genetic variance temporarily can impair the population's adaptive capacity enough to cause extinction when it would otherwise be unlikely in an effectively infinite population. We find that maximum sustainable rates of evolution or, equivalently, critical rates of environmental change, may be considerably less than 10% of a phenotypic standard deviation per generation.     

Assessment of Optimal Selected Prognostic Factors

The identification and assessment of prognostic factors is one of the major tasks in clinical research. The assessment of one single prognostic factor can be done by recently established methods for using optimal cutpoints. Here, we suggest a method to consider an optimal selected prognostic factor from a set of prognostic factors of interest. This can be viewed as a variable selection method and is the underlying decision problem at each node of various tree building algorithms. We propose to use maximally selected statistics where the selection is defined over the set of prognostic factors and over all cutpoints in each prognostic factor. We demonstrate that it is feasible to compute the approximate null distribution. We illustrate the new variable selection test with data of the German Breast Cancer Study Group and of a small study on patients with diffuse large B‐cell lymphoma. Using the null distribution for a p‐value adjusted regression trees algorithm, we adjust for the number of variables analysed at each node as well. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Decision Support through Mass and Energy Flow Management in the Vehicle-Refinishing Sector

In the past few decades, major advances in environmental protection within the coating application industry have been made. In spite of this technological progress, approximately 50% of industrial-solvent emissions still come from the paint-application sector. The advances made in reducing emissions for plants requiring licensing have unfortunately had no influence on the environmental efforts of smaller companies. Solvent-reduced painting systems, such as high-solid paints, water-based coating, and powder coating have not been able to achieve acceptance, nor have innovative application technologies. The principal arguments against a conversion to these ecologically more favorable alternatives were related to cost and quality.
Recently, the EU Solvent Directive (1999/13/EC) went into effect, aiming to significantly reduce industrial-solvent emissions. Up until this point, however, instruments enabling smaller companies to determine their solvent emissions and to simultaneously develop process-improvement potentials while keeping costs in mind have been missing.
Using the mass and energy flow-management approach, cost structures and environmental benefits can be made transparent to the entrepreneur. The primary result of the research projects presented here is the computer-based mass and energy flow model called the individual computer-aided mass and energy flow model for the vehicle-refinishing sector (IMPROVE). It can be used as a detailed business-consultancy tool. Based upon this, practical guidelines were developed for easy orientation and activity planning. They can be used by companies to help them fulfill the requirements of environmental legislation and to display the benefits that can be achieved by various emission-reduction measures.