Mercaptoethanesulfonic acid (CoM imitator) interaction studies with nickel(II) complexes of pyridyl groups containing tetradentate ligands: Synthesis, structure, spectra and redox properties

Nickel(II) complexes of N,N′-dimethyl-N,N′-bis(pyridyl-2yl-methyl)ethylene-diamine (L¹), N,N′-dimethyl-N,N′-bis(pyridyl-2-ylmethyl)-1,2-diaminopropane (L²) and N,N′-dimethyl-N,N′-bis(pyridyl-2-ylmethyl)-1,3-diaminopropane (L³) were prepared and their spectroscopic and redox properties studied. The distorted octahedral structure was determined for [NiL³ClCH₃OH](ClO₄) by using X-ray crystallography. The electronic spectral behavior of the complexes at different pHs was analyzed; it is shown that a new band grew at the expense of the other band intensity in acid media. The redox properties of ligands and their complexes show the peaks of Ni(II) → Ni(III) and Ni(II) → Ni(0) as these were detected at low concentration while Ni(II) → Ni(I) process was detectable clearly at high concentration. Furthermore, the interaction studies of 2-mercaptoethanesulfonic acid as a simulator of coenzyme M reductase (CoM) with NiN₄ chromophores are discussed.     

Periodic habitat loss alters the competitive coexistence between brown trout and bullheads in a small stream over 34 years

1. Changes in the population density of juvenile sea trout Salmo trutta L. and bullheads Cottus gobio L. were compared in a small stream over 34 years. Both species have a similar diet and obviously live in the same general habitat. Habitat loss was most marked in seven summer droughts: severest in 1976, 1983, 1984, 1995, and less severe but followed by autumn droughts in 1969, 1989 and 1993. The contrasting effects of habitat loss on the two species were examined. 2. For both species, the Ricker curvilinear model significantly fit (P < 0.001) the relationship between initial egg density and survivor density for successive life stages, even though egg densities were much lower for bullheads than trout. These analyses provided evidence for density-dependent population regulation and also identified extreme outliers, most being for year-classes affected by summer droughts. 3. The variable effects of changes in habitable area (= % wettable area in sampling section) were quantified by using the residuals, each residual being the absolute value expressed as a percentage of the expected value from the Ricker curve. Significant relationships between the residuals and habitable area showed that habitat loss had a marked effect on survivor density, this being negative for 0+ and 1+ trout, and positive for 0+, 1+ and 2+/3+ bullheads. 4. Therefore, during periods of habitat loss in the summer months, bullhead density increased at the expense of trout density. Low flows and a decrease in wettable area were associated with a marked reduction in habitat quality for drift-feeding trout and an increase in habitat quality, and perhaps also quantity, for benthic-feeding bullheads. This case study shows that, during a major perturbation, the relationship between the densities of two species can change markedly in favour of the less numerous species. The competitive coexistence between the two species is therefore a dynamic process that changes through time with periodic changes in the environment.     

A nonlinear model with latent process for cognitive evolution using multivariate longitudinal data

Cognition is not directly measurable. It is assessed using psychometric tests, which can be viewed as quantitative measures of cognition with error. The aim of this article is to propose a model to describe the evolution in continuous time of unobserved cognition in the elderly and assess the impact of covariates directly on it. The latent cognitive process is defined using a linear mixed model including a Brownian motion and time-dependent covariates. The observed psychometric tests are considered as the results of parameterized nonlinear transformations of the latent cognitive process at discrete occasions. Estimation of the parameters contained both in the transformations and in the linear mixed model is achieved by maximizing the observed likelihood and graphical methods are performed to assess the goodness of fit of the model. The method is applied to data from PAQUID, a French prospective cohort study of ageing.     

A general approach for two-stage analysis of multilevel clustered non-Gaussian data

In this article, we propose a two-stage approach to modeling multilevel clustered non-Gaussian data with sufficiently large numbers of continuous measures per cluster. Such data are common in biological and medical studies utilizing monitoring or image-processing equipment. We consider a general class of hierarchical models that generalizes the model in the global two-stage (GTS) method for nonlinear mixed effects models by using any square-root-n-consistent and asymptotically normal estimators from stage 1 as pseudodata in the stage 2 model, and by extending the stage 2 model to accommodate random effects from multiple levels of clustering. The second-stage model is a standard linear mixed effects model with normal random effects, but the cluster-specific distributions, conditional on random effects, can be non-Gaussian. This methodology provides a flexible framework for modeling not only a location parameter but also other characteristics of conditional distributions that may be of specific interest. For estimation of the population parameters, we propose a conditional restricted maximum likelihood (CREML) approach and establish the asymptotic properties of the CREML estimators. The proposed general approach is illustrated using quartiles as cluster-specific parameters estimated in the first stage, and applied to the data example from a collagen fibril development study. We demonstrate using simulations that in samples with small numbers of independent clusters, the CREML estimators may perform better than conditional maximum likelihood estimators, which are a direct extension of the estimators from the GTS method.     

A goodness-of-fit test for multinomial logistic regression

This article presents a score test to check the fit of a logistic regression model with two or more outcome categories. The null hypothesis that the model fits well is tested against the alternative that residuals of samples close to each other in covariate space tend to deviate from the model in the same direction. We propose a test statistic that is a sum of squared smoothed residuals, and show that it can be interpreted as a score test in a random effects model. By specifying the distance metric in covariate space, users can choose the alternative against which the test is directed, making it either an omnibus goodness-of-fit test or a test for lack of fit of specific model variables or outcome categories.     

Characterization of an unusual folding pattern in a catalytically active guanine quadruplex structure

In the presence of certain metal ions, DNA and RNA can form guanine quadruplex structures, which have been proposed to play a functional role in a variety of biological processes. An 18-nucleotide DNA oligomer, PS2.M, d(GTG3TAG3CG3T2G2), was previously reported to bind hemin and the resulting complex exhibited peroxidase activity. It was proposed that PS2.M folds unimolecularly into an antiparallel quadruplex with unusual, single-base loops and terminal guanines positioned in adjacent quartets. Here we describe structural and stability properties of PS2.M alone in different buffers and metal ions, using gel electrophoresis, circular dichroism (CD), ultraviolet (UV)-visible spectroscopies, and one-dimensional 1H nuclear magnetic resonance (NMR). Native gel behavior of PS2.M in the presence of either Na+ or Pb2+ suggests the formation of unimolecular structures but, in the presence of K+, both unimolecular and multistranded structures are observed. In the presence of Pb2+ ions, PS2.M forms a unimolecular quadruplex containing three guanine quartets. CD titrations reveal that binding of Pb2+ ions to PS2.M is stoichiometric, and a single lead cation suffices to fully fold PS2.M. The PS2.M-Na+ system also forms a similar unimolecular quadruplex. In the presence of K+, the PS2.M-K+ system forms mixed species. With increasing time and PS2.M concentration, the contribution of unimolecular species decreases while that of multimolecular species increases, and this behavior is independent of buffer media. These results suggest that the catalytically active form, studied in the presence of K+, may be a parallel, multistranded quadruplex rather than an antiparallel, unimolecular quadruplex.     

Estimating effects of a single gene and polygenes on quantitative traits from a diallel design

A genetic model is developed with additive and dominance effects of a single gene and polygenes as well as general and specific reciprocal effects for the progeny from a diallel mating design. The methods of ANOVA, minimum norm quadratic unbiased estimation (MINQUE), restricted maximum likelihood estimation (REML), and maximum likelihood estimation (ML) are suggested for estimating variance components, and the methods of generalized least squares (GLS) and ordinary least squares (OLS) for fixed effects, while best linear unbiased prediction, linear unbiased prediction (LUP), and adjusted unbiased prediction are suggested for analyzing random effects. Monte Carlo simulations were conducted to evaluate the unbiasedness and efficiency of statistical methods involving two diallel designs with commonly used sample sizes, 6 and 8 parents, with no and missing crosses, respectively. Simulation results show that GLS and OLS are almost equally efficient for estimation of fixed effects, while MINQUE (1) and REML are better estimators of the variance components and LUP is most practical method for prediction of random effects. Data from a Drosophila melanogaster experiment (Gilbert 1985a, Theor appl Genet 69:625–629) were used as a working example to demonstrate the statistical analysis. The new methodology is also applicable to screening candidate gene(s) and to other mating designs with multiple parents, such as nested (NC Design I) and factorial (NC Design II) designs. Moreover, this methodology can serve as a guide to develop new methods for detecting indiscernible major genes and mapping quantitative trait loci based on mixture distribution theory. The computer program for the methods suggested in this article is freely available from the authors.     

Direct determination of the influence of extreme temperature on transposition and structural mutation rates of Drosophila melanogaster mobile elements

Two sets of mutation accumulation lines, one reared at 28°C and the other at 24°C, were compared for their transposition and rearrangement rates of eleven transposable element families. The changes affecting mobile elements were analysed by the Southern technique and in situ hybridization. No differences were found between treated and control lines. The role of the host genotype in transposition control and the significance of structural mutations in transposable element dynamics are discussed.