Formation of mononuclear and chloro-bridged binuclear copper(II) complexes of patellamide D, a naturally occurring cyclic peptide: influence of anion and solvent

Patellamide D (patH(4)) is a cyclic octapeptide isolated from the ascidian Lissoclinum patella. The peptide possesses a 24-azacrown-8 macrocyclic structure containing two oxazoline and two thiazole rings, each separated by an amino acid. The present spectrophotometric, electron paramagnetic resonance (EPR) and mass spectral studies show that patellamide D reacts with CuCl, and triethylamine in acetonitrile to form mononuclear and binuclear copper(II) complexes containing chloride. Molecular modelling and EPR studies suggest that the chloride anion bridges the copper(II) ions in the binuclear complex [Cu-2(patH(2))(mu-Cl)](+). These results contrast with a previous study employing both base and methanol, the latter substituting for chloride in the copper(II) complexes en route to the stable mu-carbonato binuclear copper(II) complex [Cu-2 (patH(2))(mu-CO3)]. Solvent clearly plays an important role in both stabilising these metal ion complexes and influencing their chemical reactivities. (C) 2004 Elsevier Inc. All rights reserved.

Piecing together evolution of the vertebrate endocrine system

One of the great challenges in biology is to understand how particular complex morphological and physiological characters originated in specific evolutionary lineages. In this article, we address the origin of the vertebrate hypothalamic-pituitary-peripheral gland (H-P-PG) endocrine system, a complex network of specialized tissues, ligands and receptors. Analysis of metazoan nucleotide and protein sequences reveals a patchwork pattern of H-P-PG gene conservation between vertebrates and closely related invertebrates (ascidians). This is consistent with a model of how the vertebrate H-P-PG endocrine system could have emerged in relatively few steps by gene family expansion and by regulatory and structural modifications to genes that are present in a chordate ancestor. Some of these changes might have resulted in new connections between metabolic or signaling pathways, such as the bridging of 'synthesis islands' to form an efficient system for steroid hormone synthesis.

The Rab5 effector rabankyrin-5 regulates and coordinates different endocytic mechanisms

The small GTPase Rab5 is a key regulator of clathrin-mediated endocytosis. On early endosomes, within a spatially restricted domain enriched in phosphatydilinositol-3-phosphate [PI(3)P], Rab5 coordinates a complex network of effectors that functionally cooperate in membrane tethering, fusion, and organelle motility. Here we discovered a novel PI(3)P-binding Rab5 effector, Rabankyrin-5, which localises to early endosomes and stimulates their fusion activity. In addition to early endosomes, however, Rabankyrin-5 localises to large vacuolar structures that correspond to macropinosomes in epithelial cells and fibroblasts. Overexpression of Rabankyrin-5 increases the number of macropinosomes and stimulates fluid-phase uptake, whereas its downregulation inhibits these processes. In polarised epithelial cells, this function is primarily restricted to the apical membrane. Rabankyrin-5 localises to large pinocytic structures underneath the apical surface of kidney proximal tubule cells, and its overexpression in polarised Madin-Darby canine kidney cells stimulates apical but not basolateral, non-clathrin-mediated pinocytosis. in demonstrating a regulatory role in endosome fusion and (macro) pinocytosis, our studies suggest that Rab5 regulates and coordinates different endocytic mechanisms through its effector Rabankyrin-5. Furthermore, its active role in apical pinocytosis in epithelial cells suggests an important function of Rabankyrin-5 in the physiology of polarised cells.

Co-expression of SOX9 and SOX10 during melanocytic differentiation in vitro

Investigations into pigment cell biology have relied on the ability to culture both murine and human melanocytes, numerous melanoma cell lines and more recently, murine and human melanoblasts. Melanoblast culture requires medium supplemented with a range of growth factors including Stem Cell Factor, Endothelin-3 and Fibroblast Growth Factor-2, withdrawal of which causes the cells to differentiate into melanocytes. Using the human melanoblast culture system, we have now examined the expression and/or DNA binding activity of several transcription factors implicated in melanocytic development and differentiation. Of these, the POU domain factor BRN2 and the SOX family member SOX10 are both highly expressed in unpigmented melanocyte precursors but are down-regulated upon differentiation. In contrast, the expression levels of the previously described MITF and PAX3 transcription factors remain relatively constant during the melanoblast-melanocyte transition. Moreover, BRN2 ablated melanoma cells lack expression of SOX10 and MITF but retain PAX3. A novel finding implicates a second SOX protein, SOX9, as a potential melanogenic transcriptional regulator, as its expression level is increased following the down-regulation of BRN2 and SOX10 in differentiated melanoblasts. Our results suggest that a complex network of transcription factor interactions requiring proper temporal coordination is necessary for acquisition and maintenance of the melanocytic phenotype. (c) 2005 Elsevier Inc. All rights reserved.

Optimal Paths and Costs of Adjustment in Dynamic DEA Models: With Application to Chilean Department Stores

In this paper we propose a range of dynamic data envelopment analysis (DEA) models which allow information on costs of adjustment to be incorporated into the DEA framework. We first specify a basic dynamic DEA model predicated on a number or simplifying assumptions. We then outline a number of extensions to this model to accommodate asymmetric adjustment costs, non-static output quantities, non-static input prices, and non-static costs of adjustment, technological change, quasi-fixed inputs and investment budget constraints. The new dynamic DEA models provide valuable extra information relative to the standard static DEA models-they identify an optimal path of adjustment for the input quantities, and provide a measure of the potential cost savings that result from recognising the costs of adjusting input quantities towards the optimal point. The new models are illustrated using data relating to a chain of 35 retail department stores in Chile. The empirical results illustrate the wealth of information that can be derived from these models, and clearly show that static models overstate potential cost savings when adjustment costs are non-zero.

Expansion-based algorithms for finding single pair shortest path on surface

Finding single pair shortest paths on surface is a fundamental problem in various domains, like Geographic Information Systems (GIS) 3D applications, robotic path planning system, and surface nearest neighbor query in spatial database, etc. Currently, to solve the problem, existing algorithms must traverse the entire polyhedral surface. With the rapid advance in areas like Global Positioning System (CPS), Computer Aided Design (CAD) systems and laser range scanner, surface models axe becoming more and more complex. It is not uncommon that a surface model contains millions of polygons. The single pair shortest path problem is getting harder and harder to solve. Based on the observation that the single pair shortest path is in the locality, we propose in this paper efficient methods by excluding part of the surface model without considering them in the search process. Three novel expansion-based algorithms are proposed, namely, Naive algorithm, Rectangle-based Algorithm and Ellipse-based Algorithm. Each algorithm uses a two-step approach to find the shortest path. (1) compute an initial local path. (2) use the value of this initial path to select a search region, in which the global shortest path exists. The search process terminates once the global optimum criteria are satisfied. By reducing the searching region, the performance is improved dramatically in most cases.

A D-optimal designed population pharmacokinetic study of itraconazole capsules and solution in adults with cystic fibrosis

Background: Oral itraconazole (ITRA) is used for the treatment of allergic bronchopulmonary aspergillosis in patients with cystic fibrosis (CF) because of its antifungal activity against Aspergillus species. ITRA has an active hydroxy-metabolite (OH-ITRA) which has similar antifungal activity. ITRA is a highly lipophilic drug which is available in two different oral formulations, a capsule and an oral solution. It is reported that the oral solution has a 60% higher relative bioavailability. The influence of altered gastric physiology associated with CF on the pharmacokinetics (PK) of ITRA and its metabolite has not been previously evaluated. Objectives: 1) To estimate the population (pop) PK parameters for ITRA and its active metabolite OH-ITRA including relative bioavailability of the parent after administration of the parent by both capsule and solution and 2) to assess the performance of the optimal design. Methods: The study was a cross-over design in which 30 patients received the capsule on the first occasion and 3 days later the solution formulation. The design was constrained to have a maximum of 4 blood samples per occasion for estimation of the popPK of both ITRA and OH-ITRA. The sampling times for the population model were optimized previously using POPT v.2.0.[1] POPT is a series of applications that run under MATLAB and provide an evaluation of the information matrix for a nonlinear mixed effects model given a particular design. In addition it can be used to optimize the design based on evaluation of the determinant of the information matrix. The model details for the design were based on prior information obtained from the literature, which suggested that ITRA may have either linear or non-linear elimination. The optimal sampling times were evaluated to provide information for both competing models for the parent and metabolite and for both capsule and solution simultaneously. Blood samples were assayed by validated HPLC.[2] PopPK modelling was performed using FOCE with interaction under NONMEM, version 5 (level 1.1; GloboMax LLC, Hanover, MD, USA). The PK of ITRA and OH‑ITRA was modelled simultaneously using ADVAN 5. Subsequently three methods were assessed for modelling concentrations less than the LOD (limit of detection). These methods (corresponding to methods 5, 6 & 4 from Beal[3], respectively) were (a) where all values less than LOD were assigned to half of LOD, (b) where the closest missing value that is less than LOD was assigned to half the LOD and all previous (if during absorption) or subsequent (if during elimination) missing samples were deleted, and (c) where the contribution of the expectation of each missing concentration to the likelihood is estimated. The LOD was 0.04 mg/L. The final model evaluation was performed via bootstrap with re-sampling and a visual predictive check. The optimal design and the sampling windows of the study were evaluated for execution errors and for agreement between the observed and predicted standard errors. Dosing regimens were simulated for the capsules and the oral solution to assess their ability to achieve ITRA target trough concentration (Cmin,ss of 0.5-2 mg/L) or a combined Cmin,ss for ITRA and OH-ITRA above 1.5mg/L. Results and Discussion: A total of 241 blood samples were collected and analysed, 94% of them were taken within the defined optimal sampling windows, of which 31% where taken within 5 min of the exact optimal times. Forty six per cent of the ITRA values and 28% of the OH-ITRA values were below LOD. The entire profile after administration of the capsule for five patients was below LOD and therefore the data from this occasion was omitted from estimation. A 2-compartment model with 1st order absorption and elimination best described ITRA PK, with 1st order metabolism of the parent to OH-ITRA. For ITRA the clearance (ClItra/F) was 31.5 L/h; apparent volumes of central and peripheral compartments were 56.7 L and 2090 L, respectively. Absorption rate constants for capsule (kacap) and solution (kasol) were 0.0315 h-1 and 0.125 h-1, respectively. Comparative bioavailability of the capsule was 0.82. There was no evidence of nonlinearity in the popPK of ITRA. No screened covariate significantly improved the fit to the data. The results of the parameter estimates from the final model were comparable between the different methods for accounting for missing data, (M4,5,6)[3] and provided similar parameter estimates. The prospective application of an optimal design was found to be successful. Due to the sampling windows, most of the samples could be collected within the daily hospital routine, but still at times that were near optimal for estimating the popPK parameters. The final model was one of the potential competing models considered in the original design. The asymptotic standard errors provided by NONMEM for the final model and empirical values from bootstrap were similar in magnitude to those predicted from the Fisher Information matrix associated with the D-optimal design. Simulations from the final model showed that the current dosing regimen of 200 mg twice daily (bd) would provide a target Cmin,ss (0.5-2 mg/L) for only 35% of patients when administered as the solution and 31% when administered as capsules. The optimal dosing schedule was 500mg bd for both formulations. The target success for this dosing regimen was 87% for the solution with an NNT=4 compared to capsules. This means, for every 4 patients treated with the solution one additional patient will achieve a target success compared to capsule but at an additional cost of AUD $220 per day. The therapeutic target however is still doubtful and potential risks of these dosing schedules need to be assessed on an individual basis. Conclusion: A model was developed which described the popPK of ITRA and its main active metabolite OH-ITRA in adult CF after administration of both capsule and solution. The relative bioavailability of ITRA from the capsule was 82% that of the solution, but considerably more variable. To incorporate missing data, using the simple Beal method 5 (using half LOD for all samples below LOD) provided comparable results to the more complex but theoretically better Beal method 4 (integration method). The optimal sparse design performed well for estimation of model parameters and provided a good fit to the data.

Actor-network theory as a theoretical lens and research strategy for investigating firm internationalisation

Totally generalisable theories of firm internationalisation in the post-industrial era of international business, where national barriers are becoming less significant and technology becoming more influential, appear to be illusory. Stepwise or evolutionary models that predict gradual internationalisation are under challenge from empirical evidence of rapid internationalisation such as the phenomenon of the “born global” firm. Similarly, equilibrium models such as the eclectic paradigm have been criticised for being static and unable to account for process and path dependency. In this paper, the information and knowledge assumptions implied in theories of firm internationalisation are outlined and discussed. From this discussion, we suggest that actor-network theory, with its balance between description and explanation, may be a useful theoretical and empirical tool for investigating the complex and heterogeneous process of firm internationalisation whilst creating opportunities for further theory building.

Optimal design of a regenerative dynamic dynamometer using genetic algorithms

This paper presents an approach for optimal design of a fully regenerative dynamic dynamometer using genetic algorithms. The proposed dynamometer system includes an energy storage mechanism to adaptively absorb the energy variations following the dynamometer transients. This allows the minimum power electronics requirement at the mains power supply grid to compensate for the losses. The overall dynamometer system is a dynamic complex system and design of the system is a multi-objective problem, which requires advanced optimisation techniques such as genetic algorithms. The case study of designing and simulation of the dynamometer system indicates that the genetic algorithm based approach is able to locate a best available solution in view of system performance and computational costs.