Reply to comment on `Integrable Kondo impurity in one-dimensional q-deformed t - J models

This is a reply to the comment by P Schlottmann and A A Zvyagin.

Estimating Two-Stage Models for Genetic Influences on Alcohol, Tobacco or Drug Use Initiation and Dependence Vulnerability in Twin and Family Data

Genetic research on risk of alcohol, tobacco or drug dependence must make allowance for the partial overlap of risk-factors for initiation of use, and risk-factors for dependence or other outcomes in users. Except in the extreme cases where genetic and environmental risk-factors for initiation and dependence overlap completely or are uncorrelated, there is no consensus about how best to estimate the magnitude of genetic or environmental correlations between Initiation and Dependence in twin and family data. We explore by computer simulation the biases to estimates of genetic and environmental parameters caused by model misspecification when Initiation can only be defined as a binary variable. For plausible simulated parameter values, the two-stage genetic models that we consider yield estimates of genetic and environmental variances for Dependence that, although biased, are not very discrepant from the true values. However, estimates of genetic (or environmental) correlations between Initiation and Dependence may be seriously biased, and may differ markedly under different two-stage models. Such estimates may have little credibility unless external data favor selection of one particular model. These problems can be avoided if Initiation can be assessed as a multiple-category variable (e.g. never versus early-onset versus later onset user), with at least two categories measurable in users at risk for dependence. Under these conditions, under certain distributional assumptions., recovery of simulated genetic and environmental correlations becomes possible, Illustrative application of the model to Australian twin data on smoking confirmed substantial heritability of smoking persistence (42%) with minimal overlap with genetic influences on initiation.

Chemistry of stable iminopropadienones, RN=C=C=C=O

The synthesis, spectroscopic properties, and chemical reactions of the stable (neopentylimino)-, (mesitylimino)-, and (o-tert-butylphenylimino)propadienones (6) are reported. Nucleophilic addition of amines affords the malonic amidoamidines 7 and 8. 3,5-Dimethylpyrazole reacts analogously to form 9b. Addition of 1,2-dimethylhydrazine produces pyrazolinones 10-12. Addition of N,Y'-dimethyldiaminoethane, -propane, and -butane gives diazepine, diazocine, and diazonine derivatives 13-15, respectively (X-ray structures of 13c, 14a, and 15a are available). The mesoionic pyridopyrimidinium olates IS are obtained by addition of 2-(methylamino)pyridine (X-ray structure of 18b available). Primary 2-aminopyridines afford the pyridopyrimidininones 20-29 and 31 (X-ray structure of 21a available), and 2-aminopyrimidines and 2-aminopyrazine afford pyrimidopyrimidinones and pyrazinopyrimidinones 33-35. Pyrimidoisoquinolinone 36 results from 1-aminoisoquinoline and pyridoquinolinone 40 from 8-aminoquinoline. 2-Aminothiazoline and 2-aminothiazole afford thiazolopyrimidinone derivatives 41-43 (X-ray structure of 43a available).

Reconciling paleodistribution models and comparative phylogeography in the Wet Tropics rainforest land snail Gnarosophia bellendenkerensis (Brazier 1875)

Comparative phylogeography has proved useful for investigating biological responses to past climate change and is strongest when combined with extrinsic hypotheses derived from the fossil record or geology. However, the rarity of species with sufficient, spatially explicit fossil evidence restricts the application of this method. Here, we develop an alternative approach in which spatial models of predicted species distributions under serial paleoclimates are compared with a molecular phylogeography, in this case for a snail endemic to the rainforests of North Queensland, Australia. We also compare the phylogeography of the snail to those from several endemic vertebrates and use consilience across all of these approaches to enhance biogeographical inference for this rainforest fauna. The snail mtDNA phylogeography is consistent with predictions from paleoclimate modeling in relation to the location and size of climatic refugia through the late Pleistocene-Holocene and broad patterns of extinction and recolonization. There is general agreement between quantitative estimates of population expansion from sequence data (using likelihood and coalescent methods) vs. distributional modeling. The snail phylogeography represents a composite of both common and idiosyncratic patterns seen among vertebrates, reflecting the geographically finer scale of persistence and subdivision in the snail. In general, this multifaceted approach, combining spatially explicit paleoclimatological models and comparative phylogeography, provides a powerful approach to locating historical refugia and understanding species' responses to them.

Model specification tests in nonparametric stochastic regression models

In this paper, we consider testing for additivity in a class of nonparametric stochastic regression models. Two test statistics are constructed and their asymptotic distributions are established. We also conduct a small sample study for one of the test statistics through a simulated example. (C) 2002 Elsevier Science (USA).

Supersymmetric t-J Gaudin models and KZ equations

Supersymmetric t-J Gaudin models with open boundary conditions are investigated by means of the algebraic Bethe ansatz method. Off-shell Bethe ansatz equations of the boundary Gaudin systems are derived, and used to construct and solve the KZ equations associated with sl (2\1)((1)) superalgebra.

A review of animal models for the study of arsenic carcinogenesis

As inorganic arsenic is a proven human carcinogen, significant effort has been made in recent decades in an attempt to understand arsenic carcinogenesis using animal models, including rodents (rats and mice) and larger mammals such as beagles and monkeys. Transgenic animals were also used to test the carcinogenic effect of arsenicals, but until recently all models had failed to mimic satisfactorily the actual mechanism of arsenic carcinogenicity. However, within the past decade successful animal models have been developed using the most common strains of mice or rats. Thus dimethylarsinic acid (DMA), an organic arsenic compound which is the major metabolite of inorganic arsenicals in mammals, has been proven to be tumorigenic in such animals. Reports of successful cancer induction in animals by inorganic arsenic (arsenite and arsenate) have been rare, and most carcinogenetic studies have used organic arsenicals such as DMA combined with other tumor initiators. Although such experiments used high concentrations. of arsenicals for the promotion of tumors, animal models using doses of arsenicals species closed to the exposure level of humans in endemic areas are obviously the most significant. Almost all researchers have used drinking water or food as the pathway for the development of animal model test systems in order to mimic chronic arsenic poisoning in humans; such pathways seem more likely to achieve desirable results. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

Partial automation of database processing of simulation outputs from L-systems models of plant morphogenesis

Models of plant architecture allow us to explore how genotype environment interactions effect the development of plant phenotypes. Such models generate masses of data organised in complex hierarchies. This paper presents a generic system for creating and automatically populating a relational database from data generated by the widely used L-system approach to modelling plant morphogenesis. Techniques from compiler technology are applied to generate attributes (new fields) in the database, to simplify query development for the recursively-structured branching relationship. Use of biological terminology in an interactive query builder contributes towards making the system biologist-friendly. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

Coordination and movement pathology: models of structure and function

Here we consider the role of abstract models in advancing our understanding of movement pathology. Models of movement coordination and control provide the frameworks necessary for the design and interpretation of studies of acquired and developmental disorders. These models do not however provide the resolution necessary to reveal the nature of the functional impairments that characterise specific movement pathologies. In addition, they do not provide a mapping between the structural bases of various pathologies and the associated disorders of movement. Current and prospective approaches to the study and treatment of movement disorders are discussed. It is argued that the appreciation of structure-function relationships, to which these approaches give rise, represents a challenge to current models of interlimb coordination, and a stimulus for their continued development. (C) 2002 Elsevier Science B.V. All rights reserved.

Fluid-mobile trace element constraints on the role of slab melting and implications for Archaean crustal growth models

We use published and new trace element data to identify element ratios which discriminate between arc magmas from the supra-subduction zone mantle wedge and those formed by direct melting of subducted crust (i.e. adakites). The clearest distinction is obtained with those element ratios which are strongly fractionated during refertilisation of the depleted mantle wedge, ultimately reflecting slab dehydration. Hence, adakites have significantly lower Pb/Nd and B/Be but higher Nb/Ta than typical arc magmas and continental crust as a whole. Although Li and Be are also overenriched in continental crust, behaviour of Li/Yb and Be/Nd is more complex and these ratios do not provide unique signatures of slab melting. Archaean tonalite-trondhjemite-granodiorites (TTGs) strongly resemble ordinary mantle wedge-derived arc magmas in terms of fluid-mobile trace element content, implying that they-did not form by slab melting but that they originated from mantle which was hydrated and enriched in elements lost from slabs during prograde dehydration. We suggest that Archaean TTGs formed by extensive fractional crystallisation from a mafic precursor. It is widely claimed that the time between the creation and subduction of oceanic lithosphere was significantly shorter in the Archaean (i.e. 20 Ma) than it is today. This difference was seen as an attractive explanation for the presumed preponderance of adakitic magmas during the first half of Earth's history. However, when we consider the effects of a higher potential mantle temperature on the thickness of oceanic crust, it follows that the mean age of oceanic lithosphere has remained virtually constant. Formation of adakites has therefore always depended on local plate geometry and not on potential mantle temperature.

Rumors and stable-cause attribution in prediction and behavior

Two stock-market simulation experiments investigated the notion that rumors that invoke stable-cause attributions spawn illusory associations and less regressive predictions and behavior. In Study 1, illusory perceptions of association and stable causation (rumors caused price changes on the day after they appeared) existed despite rigorous conditions of nonassociation (price changes were unrelated to rumors). Predictions (recent price trends will continue) and trading behavior (departures from a strong buy-low-sell-high strategy) were both anti-regressive. In Study 2, stability of attribution was manipulated via a computerized tutorial. Participants taught to view price-changes as caused by stable forces predicted less regressively and departed more from buy-low-sell-high trading patterns than those taught to perceive changes as caused by unstable forces. Results inform a social cognitive and decision theoretic understanding of rumor by integrating it with causal attribution, covariation detection, and prediction theory. (C) 2002 Elsevier Science (USA). All rights reserved.

Comparison of two population pharmacokinetic programs, NONMEM and P-PHARM, for tacrolimus

Objectives: To compare the population modelling programs NONMEM and P-PHARM during investigation of the pharmacokinetics of tacrolimus in paediatric liver-transplant recipients. Methods: Population pharmacokinetic analysis was performed using NONMEM and P-PHARM on retrospective data from 35 paediatric liver-transplant patients receiving tacrolimus therapy. The same data were presented to both programs. Maximum likelihood estimates were sought for apparent clearance (CL/F) and apparent volume of distribution (V/F). Covariates screened for influence on these parameters were weight, age, gender, post-operative day, days of tacrolimus therapy, transplant type, biliary reconstructive procedure, liver function tests, creatinine clearance, haematocrit, corticosteroid dose, and potential interacting drugs. Results: A satisfactory model was developed in both programs with a single categorical covariate - transplant type - providing stable parameter estimates and small, normally distributed (weighted) residuals. In NONMEM, the continuous covariates - age and liver function tests - improved modelling further. Mean parameter estimates were CL/F (whole liver) = 16.3 1/h, CL/F (cut-down liver) = 8.5 1/h and V/F = 565 1 in NONMEM, and CL/F = 8.3 1/h and V/F = 155 1 in P-PHARM. Individual Bayesian parameter estimates were CL/F (whole liver) = 17.9 +/- 8.8 1/h, CL/F (cutdown liver) = 11.6 +/- 18.8 1/h and V/F = 712 792 1 in NONMEM, and CL/F (whole liver) = 12.8 +/- 3.5 1/h, CL/F (cut-down liver) = 8.2 +/- 3.4 1/h and V/F = 221 1641 in P-PHARM. Marked interindividual kinetic variability (38-108%) and residual random error (approximately 3 ng/ml) were observed. P-PHARM was more user friendly and readily provided informative graphical presentation of results. NONMEM allowed a wider choice of errors for statistical modelling and coped better with complex covariate data sets. Conclusion: Results from parametric modelling programs can vary due to different algorithms employed to estimate parameters, alternative methods of covariate analysis and variations and limitations in the software itself.