Designing supramolecular structures from models of cyclic peptide scaffolds with heterocyclic constraints

Cyclic peptides containing oxazole and thiazole heterocycles have been examined for their capacity to be used as scaffolds in larger, more complex, protein-like structures. Both the macrocyclic scaffolds and the supramolecular structures derived therefrom have been visualised by molecular modelling techniques. These molecules are too symmetrical to examine structurally by NMR spectroscopy. The cyclic hexapeptide ([Aaa-Thz](3), [Aaa-Oxz](3)) and cyclic octapeptide ([Aaa-Thz](4), [Aaa-Oxz](4)) analogues are composed of dipeptide surrogates (Aaa: amino acid, Thz: thiazole, Oxz: oxazole) derived from intramolecular condensation of cysteine or serine/threonine side chains in dipeptides like Aaa-Cys, Aaa-Ser and Aaa-Thr. The five-membered heterocyclic rings, like thiazole, oxazole and reduced analogues like thiazoline, thiazolidine and oxazoline have profound influences on the structures and bioactivities of cyclic peptides derived therefrom. This work suggests that such constrained cyclic peptides can be used as scaffolds to create a range of novel protein-like supramolecular structures (e.g. cylinders, troughs, cones, multi-loop structures, helix bundles) that are comparable in size, shape and composition to bioactive surfaces of proteins. They may therefore represent interesting starting points for the design of novel artificial proteins and artificial enzymes. (C) 2002 Elsevier Science Inc. All rights reserved.

Increased mononuclear cell activation and apoptosis early after human liver transplantation is associated with a reduced frequency of acute rejection

Experimental models of orthotopic liver transplantation (OLT) have shown that the very early events post-OLT are critical in distinguishing immunogenic and tolerogenic reactions. In rodents, increased leukocyte apoptosis and cytokine expression have been demonstrated in tolerogenic strain combinations. Information from human OLT recipients is less abundant. The aim of this study was to determine the amount of early leukocyte activation and apoptosis following human OLT, and to correlate this with subsequent rejection status. Peripheral blood mononuclear cells (PBMC) were isolated from 76 patients undergoing OLT - on the day prior, 5 hrs after reperfusion (day 0), and 18-24 hrs post-OLT (day 1). The mean level of apoptotic PBMCs on post OLT day 1 was higher than healthy recipients (0.9% +/- 0.2 vs. 0.2% +/- 0.1, p = 0.013). Apoptosis was greater in nonrejecting (NR) (1.1% +/- 0.3) compared with acutely-rejecting (R) (0.3% +/- 0.1, p = 0.021) patients. On day 1, PBMC from NR patients had increased expression of IFN-gamma (p = 0.006), IL-10 (p = 0.016), and CD40 ligand (p = 0.02) compared with R. Donor cell chimerism on day 1 did not differ between the groups indicating that this was unlikely to account for increased PBMC apoptosis in the NR group. Interestingly, the level of chimerism on day 0 was significantly higher in NR (3.8% +/- 0.6) compared with R (1.2% +/- 0.4, p = 0.004) patients and there was a close correlation between chimerism on day 0 and cytokine expression on day 1. These results imply that similar mechanisms are occurring in the human liver to promote graft acceptance as in the experimental models of liver transplantation and suggest that strategies that promote liver transplant acceptance in rodents might be applicable to humans.

Quantitative justification for target concentration intervention - parameter variability and predictive performance using population pharmacokinetic models for aminoglycosides

Aims [1] To quantify the random and predictable components of variability for aminoglycoside clearance and volume of distribution [2] To investigate models for predicting aminoglycoside clearance in patients with low serum creatinine concentrations [3] To evaluate the predictive performance of initial dosing strategies for achieving an aminoglycoside target concentration. Methods Aminoglycoside demographic, dosing and concentration data were collected from 697 adult patients (>=20 years old) as part of standard clinical care using a target concentration intervention approach for dose individualization. It was assumed that aminoglycoside clearance had a renal and a nonrenal component, with the renal component being linearly related to predicted creatinine clearance. Results A two compartment pharmacokinetic model best described the aminoglycoside data. The addition of weight, age, sex and serum creatinine as covariates reduced the random component of between subject variability (BSVR) in clearance (CL) from 94% to 36% of population parameter variability (PPV). The final pharmacokinetic parameter estimates for the model with the best predictive performance were: CL, 4.7 l h(-1) 70 kg(-1); intercompartmental clearance (CLic), 1 l h(-1) 70 kg(-1); volume of central compartment (V-1), 19.5 l 70 kg(-1); volume of peripheral compartment (V-2) 11.2 l 70 kg(-1). Conclusions Using a fixed dose of aminoglycoside will achieve 35% of typical patients within 80-125% of a required dose. Covariate guided predictions increase this up to 61%. However, because we have shown that random within subject variability (WSVR) in clearance is less than safe and effective variability (SEV), target concentration intervention can potentially achieve safe and effective doses in 90% of patients.

On dendrites in Down syndrome and DS murine models: a spiny way to learn

Since the discovery in the 1970s that dendritic abnormalities in cortical pyramidal neurons are the most consistent pathologic correlate of mental retardation, research has focused on how dendritic alterations are related to reduced intellectual ability. Due in part to obvious ethical problems and in part to the lack of fruitful methods to study neuronal circuitry in the human cortex, there is little data about the microanatomical contribution to mental retardation. The recent identification of the genetic bases of some mental retardation associated alterations, coupled with the technology to create transgenic animal models and the introduction of powerful sophisticated tools in the field of microanatomy, has led to a growth in the studies of the alterations of pyramidal cell morphology in these disorders. Studies of individuals with Down syndrome, the most frequent genetic disorder leading to mental retardation, allow the analysis of the relationships between cognition, genotype and brain microanatomy. In Down syndrome the crucial question is to define the mechanisms by which an excess of normal gene products, in interaction with the environment, directs and constrains neural maturation, and how this abnormal development translates into cognition and behaviour. In the present article we discuss mainly Down syndrome-associated dendritic abnormalities and plasticity and the role of animal models in these studies. We believe that through the further development of such approaches, the study of the microanatomical substrates of mental retardation will contribute significantly to our understanding of the mechanisms underlying human brain disorders associated with mental retardation. (C) 2004 Elsevier Ltd. All rights reserved.

Effects of potential models in the vapor-liquid equilibria and adsorption of simple gases on graphitized thermal carbon black

In this paper, we investigate the effects of various potential models in the description of vapor–liquid equilibria (VLE) and adsorption of simple gases on highly graphitized thermal carbon black. It is found that some potential models proposed in the literature are not suitable for the description of VLE (saturated gas and liquid densities and the vapor pressure with temperature). Simple gases, such as neon, argon, krypton, xenon, nitrogen, and methane are studied in this paper. To describe the isotherms on graphitized thermal carbon black correctly, the surface mediation damping factor introduced in our recent publication should be used to calculate correctly the fluid–fluid interaction energy between particles close to the surface. It is found that the damping constant for the noble gases family is linearly dependent on the polarizability, suggesting that the electric field of the graphite surface has a direct induction effect on the induced dipole of these molecules. As a result of this polarization by the graphite surface, the fluid–fluid interaction energy is reduced whenever two particles are near the surface. In the case of methane, we found that the damping constant is less than that of a noble gas having the similar polarizability, while in the case of nitrogen the damping factor is much greater and this could most likely be due to the quadrupolar nature of nitrogen.

Adsorption of carbon tetrachloride on graphitized thermal carbon black and in slit graphitic pores: Five-site versus one-site potential models

The performance of intermolecular potential models on the adsorption of carbon tetrachloride on graphitized thermal carbon black at various temperatures is investigated. This is made possible with the extensive experimental data of Machin and Ross(1), Avgul et al.,(2) and Pierce(3) that cover a wide range of temperatures. The description of all experimental data is only possible with the allowance for the surface mediation. If this were ignored, the grand canonical Monte Carlo (GCMC) simulation results would predict a two-dimensional (2D) transition even at high temperatures, while experimental data shows gradual change in adsorption density with pressure. In general, we find that the intermolecular interaction has to be reduced by 4% whenever particles are within the first layer close to the surface. We also find that this degree of surface mediation is independent of temperature. To understand the packing of carbon tetrachloride in slit pores, we compared the performance of the potential models that model carbon tetrachloride as either five interaction sites or one site. It was found that the five-site model performs better and describes the imperfect packing in small pores better. This is so because most of the strength of fluid-fluid interaction between two carbon tetrachloride molecules comes from the interactions among chlorine atoms. Methane, although having tetrahedral shape as carbon tetrachloride, can be effectively modeled as a pseudospherical particle because most of the interactions come from carbon-carbon interaction and hydrogen negligibly contributes to this.

Trans-cis Isomerism and acylimine formation in DsRed chromophore models: Intrinsic rotation barriers

The chromophore of the red fluorescent protein DsRed contains an acylimine substituent to a GFP-like chromophore structure. The acylimine is formed from the trans peptide linkage between residues F65 and Q66 in immature DsRed, but has a cis configuration in the mature protein. The relationship between acylimine formation and trans–cis isomerization is unresolved. We have calculated bond rotation profiles for models of mature and immature DsRed chromophores using B3LYP DFT. The isomerization barrier is substantially reduced in acylimine-substituted models, providing prima facie evidence that acylimine formation precedes trans–cis isomerization in DsRed chromophores.

Stirring in 3-d spherical models of convection in the Earth's mantle

On a global scale basalts from mid-ocean ridges are strikingly more homogeneous than basalts from intraplate volcanism. The observed geochemical heterogeneity argues strongly for the existence of distinct reservoirs in the Earth's mantle. It is an unresolved problem of Geodynamics as to how these findings can be reconciled with large-scale convection. We review observational constraints, and investigate stirring properties of numerical models of mantle convection. Conditions in the early Earth may have supported layered convection with rapid stirring in the upper layers. Material that has been altered near the surface is transported downwards by small-scale convection. Thereby a layer of homogeneous depleted material develops above pristine mantle. As the mantle cools over Earth history, the effects leading to layering become reduced and models show the large-scale convection favoured for the Earth today. Laterally averaged, the upper mantle below the lithosphere is least affected by material that has experienced near-surface differentiation. The geochemical signature obtained during the previous episode of small-scale convection may be preserved there for the longest time. Additionally, stirring is less effective in the high viscosity layer of the central lower mantle [1, 2], supporting the survival of medium-scale heterogeneities there. These models are the first, using 3-d spherical geometry and mostly Earth-like parameters, to address the suggested change of convective style. Although the models are still far from reproducing our planet, we find that proposal might be helpful towards reconciling geochemical and geophysical constraints.

Instantiating deformable models with a neural net

Deformable models are an attractive approach to recognizing objects which have considerable within-class variability such as handwritten characters. However, there are severe search problems associated with fitting the models to data which could be reduced if a better starting point for the search were available. We show that by training a neural network to predict how a deformable model should be instantiated from an input image, such improved starting points can be obtained. This method has been implemented for a system that recognizes handwritten digits using deformable models, and the results show that the search time can be significantly reduced without compromising recognition performance. © 1997 Academic Press.

Forecasting exchange rates with linear and nonlinear models

In this paper, the exchange rate forecasting performance of neural network models are evaluated against the random walk, autoregressive moving average and generalised autoregressive conditional heteroskedasticity models. There are no guidelines available that can be used to choose the parameters of neural network models and therefore, the parameters are chosen according to what the researcher considers to be the best. Such an approach, however,implies that the risk of making bad decisions is extremely high, which could explain why in many studies, neural network models do not consistently perform better than their time series counterparts. In this paper, through extensive experimentation, the level of subjectivity in building neural network models is considerably reduced and therefore giving them a better chance of Forecasting exchange rates with linear and nonlinear models 415 performing well. The results show that in general, neural network models perform better than the traditionally used time series models in forecasting exchange rates.

Added luminance ramp alters perceived edge blur and contrast:A critical test for derivative-based models of edge coding

In many models of edge analysis in biological vision, the initial stage is a linear 2nd derivative operation. Such models predict that adding a linear luminance ramp to an edge will have no effect on the edge's appearance, since the ramp has no effect on the 2nd derivative. Our experiments did not support this prediction: adding a negative-going ramp to a positive-going edge (or vice-versa) greatly reduced the perceived blur and contrast of the edge. The effects on a fairly sharp edge were accurately predicted by a nonlinear multi-scale model of edge processing [Georgeson, M. A., May, K. A., Freeman, T. C. A., & Hesse, G. S. (in press). From filters to features: Scale-space analysis of edge and blur coding in human vision. Journal of Vision], in which a half-wave rectifier comes after the 1st derivative filter. But we also found that the ramp affected perceived blur more profoundly when the edge blur was large, and this greater effect was not predicted by the existing model. The model's fit to these data was much improved when the simple half-wave rectifier was replaced by a threshold-like transducer [May, K. A. & Georgeson, M. A. (2007). Blurred edges look faint, and faint edges look sharp: The effect of a gradient threshold in a multi-scale edge coding model. Vision Research, 47, 1705-1720.]. This modified model correctly predicted that the interaction between ramp gradient and edge scale would be much larger for blur perception than for contrast perception. In our model, the ramp narrows an internal representation of the gradient profile, leading to a reduction in perceived blur. This in turn reduces perceived contrast because estimated blur plays a role in the model's estimation of contrast. Interestingly, the model predicts that analogous effects should occur when the width of the window containing the edge is made narrower. This has already been confirmed for blur perception; here, we further support the model by showing a similar effect for contrast perception. © 2007 Elsevier Ltd. All rights reserved.

Updating finite element models using measured vibration data

The modelling of mechanical structures using finite element analysis has become an indispensable stage in the design of new components and products. Once the theoretical design has been optimised a prototype may be constructed and tested. What can the engineer do if the measured and theoretically predicted vibration characteristics of the structure are significantly different? This thesis considers the problems of changing the parameters of the finite element model to improve the correlation between a physical structure and its mathematical model. Two new methods are introduced to perform the systematic parameter updating. The first uses the measured modal model to derive the parameter values with the minimum variance. The user must provide estimates for the variance of the theoretical parameter values and the measured data. Previous authors using similar methods have assumed that the estimated parameters and measured modal properties are statistically independent. This will generally be the case during the first iteration but will not be the case subsequently. The second method updates the parameters directly from the frequency response functions. The order of the finite element model of the structure is reduced as a function of the unknown parameters. A method related to a weighted equation error algorithm is used to update the parameters. After each iteration the weighting changes so that on convergence the output error is minimised. The suggested methods are extensively tested using simulated data. An H frame is then used to demonstrate the algorithms on a physical structure.

Forecasting exchange rates with linear and nonlinear models

In this paper the exchange rate forecasting performance of neural network models are evaluated against random walk and a range of time series models. There are no guidelines available that can be used to choose the parameters of neural network models and therefore the parameters are chosen according to what the researcher considers to be the best. Such an approach, however, implies that the risk of making bad decisions is extremely high which could explain why in many studies neural network models do not consistently perform better than their time series counterparts. In this paper through extensive experimentation the level of subjectivity in building neural network models is considerably reduced and therefore giving them a better chance of performing well. Our results show that in general neural network models perform better than traditionally used time series models in forecasting exchange rates.

Effects of some 5-hydroxytryptamine and related ligands in anxiety models

Drugs acting at 5-HT receptors were evaluated on three animal models of anxiety. On the elevated X-maze test the majority of 5-HT1 agonists were found to be anxiogenic. However, ipsapirone was anxiolytic and buspirone and gepirone were inactive. The 5-HT2 agonist DOI and the 5-HT2 antagonist ritanserin were anxiolytic while ICI 169,369, a 5-HT2 antagonist was inactive. All 5-HT3 antagonists tested were inactive in this test, while the indirect serotomimetics zimeldine and fenfluramine were anxiogenic. Neither beta-adrenoceptor agonists nor antagonists had reproducible effects on anxiety in this model. Combined beta-1/beta-2 adrenoceptor antagonists reversed the anxiogenic effects of 8-OH-DPAT while selective beta-1 or beta-2 antagonists did not. On the social interaction model the 5-HT1 agonists 8-OH-DPAT, RU 24969 and 5-MeODMT were anxiogenic and ipsapirone was anxiolytic. The 5-HT2 agonist DOI and the beta-adrenoceptor- and 5-HT- antagonist pindolol were anxiolytic, while the 5-HT2 and 5-HT3 antagonists were inactive. In the marble burying test, the 5-HT upake inhibitors zimeldine, fluvoxamine, indalpine and citalopram, the 5-HT1B/5-HT1C agonists mCPP and TFMPP and the 5-HT2/5-HT1C agonist DOI reduced marble burying without affecting locomotor activity. 5-HT1A agonists and the 5-HT2 and 5-HT3 antagonists were without effect. Lesions of the dorsal raphe nucleus reversed the anxiogenic effects of 8-OH-DPAT in the X-maze model. The implication of these results for the understanding of the pharmacology of 5-HT in anxiety is discussed.

Comparison of the anticatabolic effects of leucine and Ca-β-hydroxy-β-methylbutyrate in experimental models of cancer cachexia

Objective: Loss of skeletal muscle is the most debilitating feature of cancer cachexia, and there are few treatments available. The aim of this study was to compare the anticatabolic efficacy of L-leucine and the leucine metabolite β-hydroxy-β-methylbutyrate (Ca-HMB) on muscle protein metabolism, both invitro and invivo. Methods: Studies were conducted in mice bearing the cachexia-inducing murine adenocarcinoma 16 tumor, and in murine C2 C12 myotubes exposed to proteolysis-inducing factor, lipopolysaccharide, and angiotensin II. Results: Both leucine and HMB were found to attenuate the increase in protein degradation and the decrease in protein synthesis in murine myotubes induced by proteolysis-inducing factor, lipopolysaccharide, and angiotensin II. However, HMB was more potent than leucine, because HMB at 50 μM produced essentially the same effect as leucine at 1 mM. Both leucine and HMB reduced the activity of the ubiquitin-proteasome pathway as measured by the functional (chymotrypsin-like) enzyme activity of the proteasome in muscle lysates, as well as Western blot quantitation of protein levels of the structural/enzymatic proteasome subunits (20 S and 19 S) and the ubiquitin ligases (MuRF1 and MAFbx). Invivo studies in mice bearing the murine adenocarcinoma 16 tumor showed a low dose of Ca-HMB (0.25 g/kg) tobe 60% more effective than leucine (1 g/kg) in attenuating loss of body weight over a 4-d period. Conclusion: These results favor the clinical feasibility of using Ca-HMB over high doses of leucine for the treatment of cancer cachexia. © 2014 Elsevier Inc.