Synthesis, X-ray structure and catalytic properties of a copper(II) Schiff base complex modeling the activity of the Cu-B site of dopamine beta-hydroxylase

The copper(II) complex [Cu(salgly) (bpy)] . 4H(2)O (1), where salgly is a tridentate glycinatosalicylaldimine Schiffbase Ligand, is prepared and structurally characterized. The complex is found to be catalytically active in the oxidation of ascorbic acid by dioxygen and the process is also effective in the presence of benzylamine giving benzaldehyde as a product, thus modeling the activity of the Cu-B site of dopamine beta-hydroxylase. (C) 2000 Elsevier Science S.A. All rights reserved.

Photocytotoxicity and DNA cleavage activity of L-arg and L-lys Schiff base oxovanadium(IV) complexes having phenanthroline bases

Oxovanadium(IV) complexes [VO(sal-argH)(B)] Cl (1-3) and [VO(sal-lysH)(B)] Cl (4-6), where sal-argH2 and sal-lysH(2) are N-salicylidene-L-arginine and N-salicylidene-L-lysine Schiff bases and B is a phenanthroline base, viz. 1,10-phenanthroline (phen in 1 and 4); dipyrido[3,2-d: 2', 3'-f] quinoxaline (dpq in 2 and 5) and dipyrido[3,2-a: 2', 3'-c] phenazine (dppz in 3 and 6), have been prepared, characterized and their DNA photocleavage activity studied. Complex 1, characterized by X-ray crystallography, shows the presence of a vanadyl group in VIVO3N3 coordination geometry with a tridentate Schiff base having a pendant guanidinium moiety and bidentate phen ligand. The complexes exhibit a d-d band at similar to 715 nm in 20% DMF-Tris-HCl buffer. The complexes are redox active showing cathodic and anodic responses near -1.0 V and 0.85 V (vs. SCE) for the V(IV)-V(III) and V(V)-V(IV) couples, respectively, in DMF-Tris-HCl buffer. The complexes bind to calf thymus DNA giving Kb values in the range of 3.8 x 10(4) to 1.6 x 10(5) M-1. Thermal denaturation and viscosity data suggest DNA groove binding nature of the complexes. The complexes do not show any `chemical nuclease'' activity in dark in the presence of 3-mercaptopropionic acid or H2O2. The dpq and dppz complexes are efficient photocleavers of plasmid DNA in UV-A (365 nm) and red light (676 nm) via singlet oxygen pathway. The dppz complexes exhibit photocytotoxicity in HeLa cancer cells giving IC50 values of 15.4 mu M for 3 and 17.5 mu M for 6 in visible light while being non-toxic in dark giving IC50 values of > 100 mu M.

An ab-initio study of the proton affinity of conjugated schiff-base and related nitrogen compounds: an analysis of the triggering site of bacteriorhodopsin

The chemical groups which take part in the proton transfer reaction in bacteriorhodopsin have been studied by ab initio quantum chemical methods. The various factors such as conjugation with a linear system, electron delocalization of the guanidine type, cis-trans isomerism, geometry distortion and hydrogen bonding with charged groups can influence the properties of a given chemical group. Several systems are studied at 4-31G and STO-3G levels. Some of the Schiff-base analogues and guanidine type molecules are characterized by their molecular orbital diagrams, energy levels and the nature of charge distribution. Also, the effects of the above-mentioned factors on proton affinity are studied. It is hoped that the values thus obtained can be helpful in evaluating various structural models for proton transfer.

Reactions of coordinated bivalent tetradentate schiff-base chelates of nickel (II) and palladium (II)

Reactions of N,N′-n-propylene-bis(acetylacetoneimino) metal (II), M[n-P-(AI)2], where M=Ni(II) or Pd(II), with nitrosating reagents have been investigated. Mono- and di-nitrosated complexes were obtained selectively, depending upon the concentration of the nitrosating reagents and the reaction time. In both the cases, the γ-CH group is transformed to an ambidentate isonitroso group (>C=NOH), which coordinates to the metal ion by dislodging the already coordinated carbonyl group. The factors influencing the mode of binding of the isonitroso group have been discussed. The bromination reactions of the mono-nitrosated products of M[n-P-(AI)2] and Pd (II) complexes, Pd [E/i-P-(AI)2], where E/i-P-(AI)2 is a dianion of ethylene/i-propylene-bis (acetylacetoneimine), are also reported. The reaction products have been characterized by elemental analyses, electrical conductivity molecular weight determination, and ir, pmr and electronic spectral data.

A novel fiber-coated strong base-type anion exchanger with superfast kinetics. Removal and recovery of silver thiosulfate from aqueous solutions

A commercial acrylic fiber with 92% (w/w) acrylonitrile content was partially hydrolyzed converting a fraction of the nitrile (-CN) groups to carboxylic acid (-COOH) groups, to coat the fiber with polyethylenimine (PEI) resin, which was then crosslinked with glutaraldehyde and further quaternized with ethyl chloroacetate to produce a novel strong-base anionic exchanger in the form of fiber. Designated as PAN(QPEI.XG)(Cl-), the fibrous sorbent was compared with a commercial bead-form resin Amberlite IRA-458(Cl-) in respect of sorption capacity, selectivity, and kinetics for removal of silver thiosulfate complexes from aqueous solutions. Though the saturation level of [Ag(S2O3)(2)](3-) on PAN(QPEI.XG)(Cl-) is considerably less than that on IRA-458(Cl-), the gel-coated fibrous sorbent exhibits, as compared to the bead-form sorbent, a significantly higher sorption selectivity for the silver thiosulfate complex in the presence of excess of other anions Such as S2O32-, SO42-, and Cl-, and a remarkably faster rate of both sorption and stripping. The initial uptake of the sorbate by the fibrous sorbent is nearly instantaneous, reaching up to similar to 80% of the saturation capacity within 10 s, as compared to only similar to 12% on the bead-form sorbent. The high initial rate of uptake fits a shell-core kinetic model for sorption on fiber of cylindrical geometry. With 4M HCl, the stripping of the sorbed silver complex from the fibrous sorbent is clean and nearly instantaneous, while, in contrast, a much slower rate of stripping on the bead-form sorbent leads to its fouling due to a slow decomposition of the silver thiosulfate complex in the acidic medium.

Gas turbine diagnostics using a soft computing approach

A fuzzy system is developed using a linearized performance model of the gas turbine engine for performing gas turbine fault isolation from noisy measurements. By using a priori information about measurement uncertainties and through design variable linking, the design of the fuzzy system is posed as an optimization problem with low number of design variables which can be solved using the genetic algorithm in considerably low amount of computer time. The faults modeled are module faults in five modules: fan, low pressure compressor, high pressure compressor, high pressure turbine and low pressure turbine. The measurements used are deviations in exhaust gas temperature, low rotor speed, high rotor speed and fuel flow from a base line 'good engine'. The genetic fuzzy system (GFS) allows rapid development of the rule base if the fault signatures and measurement uncertainties change which happens for different engines and airlines. In addition, the genetic fuzzy system reduces the human effort needed in the trial and error process used to design the fuzzy system and makes the development of such a system easier and faster. A radial basis function neural network (RBFNN) is also used to preprocess the measurements before fault isolation. The RBFNN shows significant noise reduction and when combined with the GFS leads to a diagnostic system that is highly robust to the presence of noise in data. Showing the advantage of using a soft computing approach for gas turbine diagnostics.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Genetic Heterogeneity in Wild Isolates of Cellular Slime Mold Social Groups

This study addresses the issues of spatial distribution, dispersal, and genetic heterogeneity in social groups of the cellular slime molds (CSMs). The CSMs are soil amoebae with an unusual life cycle that consists of alternating solitary and social phases. Because the social phase involves division of labor with what appears to be an extreme form of "altruism", the CSMs raise interesting evolutionary questions regarding the origin and maintenance of sociality. Knowledge of the genetic structure of social groups in the wild is necessary for answering these questions. We confirm that CSMs are widespread in undisturbed forest soil from South India. They are dispersed over long distances via the dung of a variety of large mammals. Consistent with this mode of dispersal, most social groups in the two species examined for detailed study, Dictyostelium giganteum and Dictyostelium purpureum, are multi-clonal.

Cognitive Functioning in Alcohol and Other Substance Use Disorders in Young Adulthood : A Genetic Epidemiological Study

Alcohol and other substance use disorders (SUDs) result in great costs and suffering for individuals and families and constitute a notable public health burden. A multitude of factors, ranging from biological to societal, are associated with elevated risk of SUDs, but at the level of individuals, one of the best predictors is a family history of SUDs. Genetically informative twin and family studies have consistently indicated this familial risk to be mainly genetic. In addition, behavioral and temperamental factors such as early initiation of substance use and aggressiveness are associated with the development of SUDs. These familial, behavioral and temperamental risk factors often co-occur, but their relative importance is not well known. People with SUDs have also been found to differ from healthy controls in various domains of cognitive functioning, with poorer verbal ability being among the most consistent findings. However, representative population-based samples have rarely been used in neuropsychological studies of SUDs. In addition, both SUDs and cognitive abilities are influenced by genetic factors, but whether the co-variation of these traits might be partly explained by overlapping genetic influences has not been studied. Problematic substance use also often co-occurs with low educational level, but it is not known whether these outcomes share part of their underlying genetic influences. In addition, educational level may moderate the genetic etiology of alcohol problems, but gene-environment interactions between these phenomena have also not been widely studied. The incidence of SUDs peaks in young adulthood rendering epidemiological studies in this age group informative. This thesis investigated cognitive functioning and other correlates of SUDs in young adulthood in two representative population-based samples of young Finnish adults, one of which consisted of monozygotic and dizygotic twin pairs enabling genetically informative analyses. Using data from the population-based Mental Health in Early Adulthood in Finland (MEAF) study (n=605), the lifetime prevalence of DSM-IV any substance dependence or abuse among persons aged 21—35 years was found to be approximately 14%, with a majority of the diagnoses being alcohol use disorders. Several correlates representing the domains of behavioral and affective factors, parental factors, early initiation of substance use, and educational factors were individually associated with SUDs. The associations between behavioral and affective factors (attention or behavior problems at school, aggression, anxiousness) and SUDs were found to be largely independent of factors from other domains, whereas daily smoking and low education were still associated with SUDs after adjustment for behavioral and affective factors. Using a wide array of neuropsychological tests in the MEAF sample and in a subsample (n=602) of the population-based FinnTwin16 (FT16) study, consistent evidence of poorer verbal cognitive ability related to SUDs was found. In addition, participants with SUDs performed worse than those without disorders in a task assessing psychomotor processing speed in the MEAF sample, whereas no evidence of more specific cognitive deficits was found in either sample. Biometrical structural equation models of the twin data suggested that both alcohol problems and verbal ability had moderate heritabilities (0.54—0.72), and that their covariation could be explained by correlated genetic influences (genetic correlations -0.20 to -0.31). The relationship between educational level and alcohol problems, studied in the full epidemiological FT16 sample (n=4,858), was found to reflect both genetic correlation and gene-environment interaction. The co-occurrence of low education and alcohol problems was influenced by overlapping genetic factors. In addition, higher educational level was associated with increased relative importance of genetic influences on alcohol problems, whereas environmental influences played a more important role in young adults with lower education. In conclusion, SUDs, especially alcohol abuse and dependence, are common among young Finnish adults. Behavioral and affective factors are robustly related to SUDs independently of many other factors, and compared to healthy peers, young adults who have had SUDs during their life exhibit significantly poorer verbal cognitive ability, and possibly less efficient psychomotor processing. Genetic differences between individuals explain a notable proportion of individual differences in risk of alcohol dependence, verbal ability, and educational level, and the co-occurrence of alcohol problems with poorer verbal cognition and low education is influenced by shared genetic backgrounds. Finally, various environmental factors related to educational level in young adulthood moderate the relative importance of genetic factors influencing the risk of alcohol problems, possibly reflecting differences in social control mechanisms related to educational level.

Optimal reservoir operation for irrigation of multiple crops using genetic algorithms

This paper presents a genetic algorithm (GA) model for obtaining an optimal operating policy and optimal crop water allocations from an irrigation reservoir. The objective is to maximize the sum of the relative yields from all crops in the irrigated area. The model takes into account reservoir inflow, rainfall on the irrigated area, intraseasonal competition for water among multiple crops, the soil moisture dynamics in each cropped area, the heterogeneous nature of soils. and crop response to the level of irrigation applied. The model is applied to the Malaprabha single-purpose irrigation reservoir in Karnataka State, India. The optimal operating policy obtained using the GA is similar to that obtained by linear programming. This model can be used for optimal utilization of the available water resources of any reservoir system to obtain maximum benefits.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Intermolecular Chelate Linkage Isomerism of the Hydroxyimino Group in the Nickel(II), Copper(II), and Palladium(II) Complexes of Quadridentate Schiff-base Ligands

The C-nitrosation of bivalent quadridentate β-imino ketone complexes of nickel(II), copper(II), and palladium(II), with nitrosating reagents has been investigated. The chemical analysis and spectroscopic results reveal that one of the α-CH groups of the coordinated lignad undergoes selective nitrosation forming mono(hydroxyimino) derivative. The hydroxyimino group introduced coordinates through either N- or O- atom to metal(II) by dislodging the carbonyl group already coordinated. This gives rise to two linkage isomers, one with N-bonded and the other with O-bonded hydroxyimino group in the case of nickel(II) (except for 1d) and palladium(II), and a single isomer with O-bonded hydroxyimino group in copper(II) complexes. The isomers obtained from 1b and 1i have been separated by column chromatography. In chloroform each of the isomers of nickel(II) isomerizes to give an equilibrium mixture of two isomers, but not those of copper(II) and palladium(II).

Determinants of Cognitive Impairment in Old Age and Their Genetic Architecture

Cognitive health is of central importance for independent and balanced old age, while memory disorders represent the leading cause of intensive and long-term care among the Finnish elderly. The aims of this study were to analyse the effect of height, body mass index, weight change, metabolic conditions and coffee drinking in midlife on cognitive performance in old age among a sample of 2606 Finnish twins aged 65 years or older who had participated in a telephone interview to assess their cognitive status. Since coffee drinking associates with several metabolic conditions and Finns are known to be the greatest consumers of coffee in the world, the heritability and stability of coffee drinking was analysed in the whole Older Finnish Twin Cohort (n=10716). In order to investigate the association between height and cognitive performance in a population with more supportive childhood living conditions, a total of 2161 Danish twins were included in this study. A greater height was found to clearly associate with better cognitive performance in Finnish subjects, but less so among the Danish sample, which may reflect the childhood environmental differences between these cohorts. In the Finnish subjects, there was greater variance in cognitive performance among shorter subjects, and environmental factors were found to play a greater role in their cognitive performance, whereas the cognitive performance of taller participants was mainly explained by genetic factors. Midlife metabolic variables that were found to be significantly associated with a poorer cognitive performance in old age included a higher body mass index and three metabolic conditions: cardiovascular disease, hypertension and, most significantly of all, diabetes. Moreover, both weight gain and loss, even to a lesser degree than suggested previously, were found to be associated with poorer cognition. Furthermore, evidence of a causal relationship between midlife cardiovascular disease and cognitive performance in old age was demonstrated among discordant twin pairs. Conversely, no effect of coffee drinking in midlife on cognitive performance in old age was observed, although coffee drinking was demonstrated to be stable in the study population. The heritability of coffee drinking was found to differ across sexes and age groups, being 51% in men and 52% in women in the whole study population. This study supports the contention that cognitive performance in old age reflects the effects of multiple genetic and environmental exposures, including their complex interactions during the life-span. The demonstrated associations and evidence of a causal pathway between potentially preventable exposures and poorer cognitive performance highlight the importance of preventive medicine.