bluuebunny/crossref_metadata_2025_split huggingface dataset:
Coordination Modes in a Tridentate NNS (Thiosemicarbazonato)copper(II) System Containing Oxygen‐Donor Coligands − Structures of [{Cu(L)(X)}2] (X = Formato, Propionato, Nitrito)
Authors: Gómez‐Saiz Patricia , García‐Tojal Javier , Mendia Aránzazu , Donnadieu Bruno , Lezama Luis , Pizarro José Luis , Arriortua Maria Isabel , Rojo Teófilo 
Published: January 2003

AbstractComplexes with the formula [{Cu(L)X}2] [X = HCOO− (1), CH3CH2COO− (2), NO2− (3)], where HL = C7H8N4S (pyridine‐2‐carbaldehyde thiosemicarbazone), have been synthesised and characterised. Single‐crystal X‐ray diffraction studies show that the structures of these compounds consist of centrosymmetric dimers containing distorted square‐pyramidal copper(II) ions. The metal centres are coordinated to the NNS atoms of the tridentate thiosemicarbazonato ligand and one oxygen atom of the X coligand in the basal position. These complexes mainly differ in the atom that occupies the apical position. The structures of compounds 1 and 3 are made up of {Cu2(μ−SL)2} entities in which the sulfur atom of the tridentate ligand acts as a bridge occupying the apical position. Compound 2 contains a {Cu2(μ‐OX)2} species bridged through the oxygen atoms from both propionato ligands. The results demonstrate the influence of the size of the coligand on the structure of these complexes. Structural and spectroscopic results suggest the presence of relevant ligand‐to‐metal charge transfers in these compounds. The EPR spectra exhibit rhombic symmetry. Magnetic measurements show antiferromagnetic couplings. The susceptibility data were fitted using the Bleaney−Bowers equation for copper(II) dimers. The J/k values obtained are −4.0, −4.8 and −4.9 K for compounds 1, 2 and 3, respectively. (© Wiley‐VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2003)
DNA Cleavage by Copper Complexes of 2‐ and 3‐Clip‐Phen Derivatives
Authors: Pitié Marguerite , Boldron Christophe , Gornitzka Heinz , Hemmert Catherine , Donnadieu Bruno , Meunier Bernard 
Published: January 2003

AbstractThe DNA cleavage activity of copper complexes of phenanthroline has been increased by the use of “2‐Clip‐Phen” and “3‐Clip‐Phen” ligands containing two phenanthroline entities linked by a serinol bridge. In order to optimize DNA cleavage activity, two series of new Clip‐Phen ligands (L) with two phenanthroline residues linked through their C‐2 or C‐3 carbon atoms by different bridges have been synthesized. The physicochemical properties and the DNA cleavage activities of the corresponding (Clip‐Phen)copper complexes were investigated in the presence of a reductant and air. X‐ray analyses of single crystals showed that the cupric complexes of Clip‐Phen were able adopt dimeric double‐helical geometries with L2Cu2 stoichiometries in the solid state. These complexes adopt different geometries and stoichiometries in solution, with monomeric LCu species predominant. The compounds with a bridge connected at C‐2 are less active as DNA cleavage agents than complexes with the bridge at the C‐3 positions. Copper complexes with a bridge containing three methylene units appear to give the best results in DNA cleavage experiments. This activity is increased in the case of 3‐Clip‐Phen·CuCl2 by the presence of the primary amine function of the serinol bridge. This amine function is probably coordinated to the copper atom in the case of 2‐Clip‐Phen·CuCl2, decreasing the reactivity toward DNA. (© Wiley‐VCH Verlag GmbH & Co KGaA, 69451 Weinheim, Germany, 2003)
Ground Spin State Variation in Carboxylate‐Bridged Tetranuclear [Fe2Mn2O2]8+ Cores and a Comparison with Their [Fe4O2]8+ and [Mn4O2]8+ Congeners
Authors: Chaudhuri Phalguni , Rentschler Eva , Birkelbach Frank , Krebs Carsten , Bill Eckhard , Weyhermüller Thomas , Flörke Ulrich 
Published: January 2003

AbstractSyntheses of ten new tetranuclear complexes containing the [MA(μ3‐O)2MB]8+ butterfly core [MA = MB = FeIII (1 and 2), MA = MB = MnIII (3 and 4) and MA = FeIII, MB = MnIII (5−10)] using 1,4,7‐trimethyl‐1,4,7‐triazacyclononane (L) as the capping ligand, salicylaldoximato dianion (salox2−) and six different carboxylate anions as bridging ligands, are described. The crystal structures of [L2Fe2(μ3‐O)2(salox)2(diphenylglycolate)3Fe2](ClO4) (1), [L2Mn2(μ3‐O)2(salox)2(diphenylglycolate)3Mn2](ClO4) (3), [L2Fe2(μ3‐O)2(salox)2(acetate)3Mn2](ClO4) (5), [L2Fe2(μ3‐O)2(salox)2(diphenylglycolate)3Mn2](ClO4) (6), and [L2Fe2(μ3‐O)2(salox)2(benzoate)3Mn2](ClO4) (8) were determined by X‐ray crystallography. The complexes are isostructural, with MIII ions disposed in a butterfly core where bridging between the MIII ions occurs via two μ3‐oxo anions. In complexes 5, 6 and 8 the “wing‐tip” positions of the butterfly are occupied by the LFe3+ units, whereas the “body” metal ions are d4 high‐spin MnIII ions. Complexes 1−10 have been characterised by variable‐temperature (2−290 K) magnetic susceptibility measurements (1 T) and by Mössbauer spectroscopy. A “2J” model has been applied to simulate the experimental μeff vs. T plots. Overall exchange interactions are antiferromagnetic in nature. Complexes with the Fe4O2 core (1 and 2) and the Mn4O2 core (3 and 4) possess an St = 0 and St = 3 ground state, respectively, regardless of the nature of the bridging carboxylate ligand. In contrast, changing the bridging carboxylates in the [Fe2Mn2O2] core from acetate (5) to diphenylglycolate (6), triphenyl acetate (7), benzoate (8), chloroacetate (9) and propionate (10), results in a variation of the ground state from St = 1 to St = 3, due to spin frustration of the “body” manganese centres. The spin‐correlation diagram for the Fe2Mn2O2 butterfly arrangement clearly demonstrates the ground state variation as a function of the ratio of two competing coupling interactions. (© Wiley‐VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2003)
Chiral Complexes of RhI Containing Binaphthalene‐Core P,S‐Heterobidentate Ligands − Synthesis, Characterization, and Catalytic Activity in Asymmetric Hydrogenation of α,β‐Unsaturated Acids and Esters
Authors: Gladiali Serafino , Grepioni Fabrizia , Medici Serenella , Zucca Antonio , Berente Zoltán , Kollár László 
Published: January 2003

AbstractThe enantiopure complexes 3a and 3b [Rh(NBD)(P,S)]+BF4− [P,S = (S)‐2‐(diphenylphosphanyl)‐2′‐(methylthio)‐1,1′‐binaphthalene (a); (S)‐2‐(diphenylphosphanyl)‐2′‐(isopropylthio)‐1,1′‐binaphthalene (b)] have been prepared from [Rh(NBD)(THF)2]+BF4− by reaction with a stoichiometric amount of the appropriate P,S‐heterobidentate ligand. Single‐crystal X‐ray analysis of the S‐methyl derivative shows that the seven‐membered chelate ring is locked in a boat‐like conformation with the methyl group in the equatorial position. Variable‐temperature NMR measurements confirm that this conformation is maintained in solution and that the dynamic behaviour displayed by the complex is due to pseudo‐rotation of the diolefin. Complexes 3 have been tested in the asymmetric hydrogenation of α,β‐unsaturated acids and esters. Enantioselectivities of up to 60% ee have been recorded. (© Wiley‐VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2003)
Activation of C−S Bonds in Organosulfur Compounds Containing α,β‐Unsaturated Ketone Systems by Carbonylruthenium and ‐iron Complexes
Authors: Alvarez‐Toledano Cecilio , Delgado Esther , Donnadieu Bruno , Gómez M. Angeles , Hernández Elisa , Martín Gema , Ortega‐Jiménez Fernando , Zamora Félix 
Published: January 2003

AbstractVinylidenetetraruthenium clusters have been obtained from the reactions between [Ru3(CO)12] and [CH3C(O)CH=C(SCH3)2] or [(C5H5)Fe{C5H4CH=CHC(O)CH=C(SCH2CH2S)}] by cleavage of the S−C sp2 bonds in these ligands. An excess of [CH3C(O)CH=C(SCH3)2] afforded the dinuclear complex [Ru2(CO)4(μ‐SCH3)2{η2:κ‐C,O‐C(SCH3)CHC(O)CH3}2], which was then converted into the vinylidene cluster [Ru4(CO)10(μ‐SCH3)2{μ4,η3:κ‐C,C,O‐C=CHC(O)CH3}] in the presence of more of the carbonylruthenium complex. However, the carbonyliron complex led to the formation of the dinuclear compounds [Fe2(CO)4(μ‐SCH3)2{η2:κ‐C,O‐C(SCH3)CHC(O)CH3}2] and [Fe2(CO)5{μ,η4:κ‐C,O,S,S‐(SCH2CH2S)C=CHC(O)CH=CHC5H4}Fe(C5H5)]. All of the new complexes exhibit a pentametallacycle group as a consequence of the rupture of the S−C bonds, as well as the presence of the C(O)R substituent in these ligands. The compounds have been characterised by analytical and spectroscopic data and the crystal structures of some of them have been solved by X‐ray diffraction. (© Wiley‐VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2003)
Short communication: Autoignition temperature of trichlorosilanes
Authors: Hshieh Fu‐Yu , Hirsch David B. , Williams James H. 
Published: January 2003

AbstractTrichlorosilanes are important silicon intermediates used to manufacture silicone materials. Because they are produced and used in large quantities and some are very reactive, it is important to determine the autoignition temperature (AIT) of trichlorosilanes. This short communication reports the AIT of eight important trichlorosilanes and discusses the effect of substituted groups on the AIT. Copyright © 2002 John Wiley & Sons, Ltd.
Molecular cytogenetic characterization of Sézary syndrome
Authors: Mao Xin , Lillington Debra M. , Czepulkowski Barbara , Russell‐Jones Robin , Young Bryan D. , Whittaker Sean 
Published: January 2003

AbstractSézary syndrome (SS) is a rare form of erythrodermic cutaneous T‐cell lymphoma with hematological involvement and a poor prognosis. At present little is known about the molecular pathogenesis of this malignancy. To address this issue, we analyzed 28 SS cases through the use of molecular cytogenetic techniques. Conventional cytogenetic analysis showed 12 of 28 cases with clonal chromosome abnormalities (43%). Seven cases had aberrations affecting chromosomes 1 and 17; five demonstrated rearrangement of chromosomes 10 and 14; four presented with an abnormality of 6q. Multiplex‐fluorescence in situ hybridization (M‐FISH) revealed complex karyotypes in 6 of 17 cases (35%), and recurrent der(1)t(1;10)(p2;q2) and der(14)t(14;15)(q;q?) translocations were each identified in two cases, and confirmed by dual‐color FISH. There was an overall difference in the incidence of clonal abnormalities detected by G‐banded karyotyping and M‐FISH. In addition, comparative genomic hybridization studies revealed chromosome imbalances (CIs) in 9 of 20 cases (45%), with a mean DNA copy number change per sample of 1.95 ± 2.74, and losses (mean: 1.25 ± 1.77) more frequent than gains (mean: 0.7 ± 1.26). The most common CIs noted were loss of 1p, followed by losses of 10/10q, 17p, and 19, and gains of 17q and 18. Furthermore, in conjunction with this study a systematic literature review was conducted, which showed a high frequency and consistent pattern of chromosome changes in SS. These findings suggest that chromosomal instability is common in SS, although there are specific chromosomal abnormalities that appear to be characteristic, and the identification of two different recurrent chromosome translocations provides the basis for further studies. © 2003 Wiley‐Liss, Inc.
Multivariate and multilocus variance components method, based on structural relationships to assess quantitative trait linkage via SEGPATH
Authors: Province M.A. , Rice T.K. , Borecki I.B. , Gu C. , Kraja A. , Rao D.C. 
Published: January 2003

AbstractA general‐purpose modeling framework for performing path and segregation analysis jointly, called SEGPATH (Province and Rao [1995] Stat. Med. 7:185–198), has been extended to cover “model‐free” robust, variance‐components linkage analysis, based on identity‐by‐descent (IBD) sharing. These extended models can be used to analyze linkage to a single marker or to perform multipoint linkage analysis, with a single phenotype or multivariate vector of phenotypes, in pedigrees. Within a single, consistent approach, SEGPATH models can perform segregation analysis, path analysis, linkage analysis, or combinations thereof. SEGPATH models can incorporate environmental or other measured covariate fixed effects (including measured genotypes), genotype‐specific covariate effects, population heterogeneity models, repeated‐measures models, longitudinal models, autoregressive models, developmental models, gene‐by‐environment interaction models, etc., with or without linkage components. The data analyzed can have any missing value structure (assumed missing at random), with entire individuals missing, or missing on one or more measurements. Corrections for ascertainment can be made on a vector of phenotypes and/or other measures. Because of the flexibility of the class of models, the SEGPATH approach can also be used in nongenetic applications where there is a hierarchical structure, such as longitudinal, repeated‐measures, time series, or nested models. A variety of specific models are provided, as well as some comparisons with other linkage analysis models. Particular applications demonstrate the importance of correctly accounting for the extraneous sources of familial resemblance, as can be done easily with these SEGPATH models, so as to give added power to detect linkage as well as to protect against spuriously inferring linkage. Genet Epidemiol 24:128–138, 2003. © 2003 Wiley‐Liss, Inc.
Three‐state frailty model for age at onset of dementia and death in Swedish twins
Authors: Ripatti Samuli , Gatz Margaret , Pedersen Nancy L. , Palmgren Juni 
Published: January 2003

AbstractWe present a frailty model to estimate the relative importance of genetic and environmental factors on age at onset of dementia in a twin design. We use modern survival methodology to define a model that accounts simultaneously for longitudinal aspects, e.g., left truncation and right censoring in data, and the multivariate nature of twin data. Additionally, we present a novel three‐state frailty model, with nondemented, demented, and dead states, describing variation in the onset of disease and mortality simultaneously in one model, while accounting for possible dependence for the two competing events. The frailty structure, i.e., the latent random effects structure, mimics the traditional twin model for continuous variables used in quantitative genetics, and as such describes within‐pair dependence. This in turn leads to estimates for intrapair correlations, as well as for additive genetic, and shared and nonshared environmental components of variance. A hierarchical Bayesian model formulation and Gibbs sampling are used to estimate posterior distributions of the parameters. The models are applied to Swedish Twin Registry data on the onset of dementia in elderly twins. Based on the three‐state frailty model, we estimate the intrapair correlations for dementia to be 0.87 [90% credible interval: 0.61,0.98] and 0.68[0.18,0.91] for MZ and DZ twins, respectively. Based on our model, we estimate that genetic effects account for about one third, and shared environmental effects for almost a half, of the variation in dementia hazards between individuals. More data, however, are needed to gain precision in these estimates.Genet Epidemiol24:139–149, 2003. © 2003 Wiley‐Liss, Inc.
Genetic association tests with age at onset
Authors: Hsu L. 
Published: January 2003

AbstractMany diseases or traits exhibit a varying age at onset. Recent data examples of prostate cancer and childhood diabetes show that compared to simply treating the disease outcome as affected vs. unaffected, incorporation of age‐at‐onset information into the transmission/disequilibrium type of test (TDT) does not appear to change the results much. In this paper, we evaluate the power of TDT as a function of age at onset, and show that age‐at‐onset information is most useful when the disease is common, or the relative risk associated with the high‐risk genotype varies with age. Moreover, an extremely old unaffected subject can contribute substantially to the power of the TDT, sometimes as much as old‐onset subjects. We propose a modified test statistic for testing no association between the marker at the candidate locus and age at onset. The simulation study was conducted to evaluate the finite sample properties of proposed and the TDT test statistics under various sampling schemes for trios of parents and offspring, as well as for sibling clusters where unaffected siblings were used as controls.Genet Epidemiol24:118–127, 2003. © 2003 Wiley‐Liss, Inc.
Multipoint affected sibpair linkage methods for localizing susceptibility genes of complex diseases
Authors: Glidden David V. , Liang Kung‐Yee , Chiu Yen‐Feng , Pulver Ann E. 
Published: January 2003

AbstractRecently, Liang et al. ([2001] Hum. Hered. 51:64–78) proposed a general multipoint linkage method for estimating the chromosomal position of a putative susceptibility locus. Their technique is computationally simple and does not require specification of penetrance or a mode of inheritance. In complex genetic diseases, covariate data may be available which reflect etiologic or locus heterogeneity. We developed approaches to incorporating covariates into the method of Liang et al. ([2001] Hum. Hered. 51:64–78) with particular attention to exploiting age‐at‐onset information. The results of simulation studies, and a worked data example using a family data set ascertained through probands with schizophrenia, suggest that utilizing covariate information can yield substantial efficiency gains in localizing susceptibility genes. Genet Epidemiol 24: 107–117, 2003. © 2003 Wiley‐Liss, Inc.
Power of multifactor dimensionality reduction for detecting gene‐gene interactions in the presence of genotyping error, missing data, phenocopy, and genetic heterogeneity
Authors: Ritchie Marylyn D. , Hahn Lance W. , Moore Jason H. 
Published: January 2003

AbstractThe identification and characterization of genes that influence the risk of common, complex multifactorial diseases, primarily through interactions with other genes and other environmental factors, remains a statistical and computational challenge in genetic epidemiology. This challenge is partly due to the limitations of parametric statistical methods for detecting genetic effects that are dependent solely or partially on interactions with other genes and environmental exposures. We previously introduced multifactor dimensionality reduction (MDR) as a method for reducing the dimensionality of multilocus genotype information to improve the identification of polymorphism combinations associated with disease risk. The MDR approach is nonparametric (i.e., no hypothesis about the value of a statistical parameter is made), is model‐free (i.e., assumes no particular inheritance model), and is directly applicable to case‐control and discordant sib‐pair study designs. Both empirical and theoretical studies suggest that MDR has excellent power for identifying high‐order gene‐gene interactions. However, the power of MDR for identifying gene‐gene interactions in the presence of common sources of noise is not currently known. The goal of this study was to evaluate the power of MDR for identifying gene‐gene interactions in the presence of noise due to genotyping error, missing data, phenocopy, and genetic or locus heterogeneity. Using simulated data, we show that MDR has high power to identify gene‐gene interactions in the presence of 5% genotyping error, 5% missing data, or a combination of both. However, MDR has reduced power for some models in the presence of 50% phenocopy, and very limited power in the presence of 50% genetic heterogeneity. Extending MDR to address genetic heterogeneity should be a priority for the continued methodological development of this new approach. Genet. Epidemiol. 24:150–154, 2003. © 2003 Wiley‐Liss, Inc.
Limits of fine‐mapping a quantitative trait
Authors: Atwood Larry D. , Heard‐Costa Nancy L. 
Published: January 2003

AbstractOnce a significant linkage is found, an important goal is reducing the error in the estimated location of the linked locus. A common approach to reducing location error, called fine‐mapping, is the genotyping of additional markers in the linked region to increase the genetic information. The utility of fine‐mapping for quantitative trait linkage analysis is largely unknown. To explore this issue, we performed a fine‐mapping simulation in which the region containing a significant linkage at a 10‐centiMorgan (cM) resolution was fine‐mapped at 2, 1, and 0.5 cM. We simulated six quantitative trait models in which the proportion of variation due to the quantitative trait locus (QTL) ranged from 0.20–0.90. We used four sampling designs that were all combinations of 100 and 200 families of sizes 5 and 7. Variance components linkage analysis (Genehunter) was performed until 1,000 replicates were found with a maximum lodscore greater than 3.0. For each of these 1,000 replications, we repeated the linkage analysis three times: once for each of the fine‐map resolutions. For the most realistic model, reduction in the average location error ranged from 3–15% for 2‐cM fine‐mapping and from 3–18% for 1‐cM fine‐mapping, depending on the number of families and family size. Fine‐mapping at 0.5 cM did not differ from the 1‐cM results. Thus, if the QTL accounts for a small proportion of the variation, as is the case for realistic traits, fine‐mapping has little value. Genet Epidemiol 24:99–106, 2003. © 2003 Wiley‐Liss, Inc.
Review of proteomics with applications to genetic epidemiology
Authors: Sellers Thomas A. , Yates John R. 
Published: January 2003

AbstractMapping of the human genome has the potential to transform the traditional methods of genetic epidemiology. The complete draft sequence of the 3.3 billion nucleotides comprising the genome is now available over the Internet, including the location and nearly complete sequence of the 26,000 to 31,000 protein‐encoding genes. However, aside from water, almost everything in the human body is either made of, or by, proteins. Although the DNA code provides the instructions for their amino acid sequence, there are an estimated 1.5 million proteins. Thus, the correlation between DNA sequence and protein is low, reflecting alternate splicing as well as post‐translational modification. The purpose of this article is to explore ways in which the emerging field of proteomics, the study of proteins in a cell, may inform our approach to gene mapping. This article reviews the various technical approaches currently available for proteomics. Technologies are available to quantify protein expression (and compare normal versus disease states), identify proteins through comparison with sequence information in databases or direct sequencing (which can then be mapped to chromosomal locations to ensure appropriate markers), elucidate protein‐protein interactions (which may underlie disease), determine localization of proteins within the cell (abnormal trafficking of proteins could have an inherited basis), and characterize modifications of proteins (which is relevant to modifier gene candidates). Several examples are presented to illustrate the potential application of proteomics to the field of genetic epidemiology, and we conclude with various considerations regarding design and analysis. Genet Epidemiol 24:83–98, 2003. © 2003 Wiley‐Liss, Inc.