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PubMed1992

Elastomechanical characterization of brain tissues.

The fluid-induced changes in the intracranial pressure which have important clinical implications are believed to be largely determined by the elastomechanical properties of the brain tissues. To define and evaluate the elastomechanical characteristics of the brain tissues a nonlinear hyperelastic hollow spherical shell has been employed to model the craniospinal complex for its fluid-induced intracranial pressure volume changes. The strain energy function proposed by Hart-Smith has been used to derive the constitutive equations. In 10 dogs, fluid has been infused in the lateral ventricle of the brain. The resulting changes in the ventricular fluid pressure (VFP) and the epidural pressure (EDP) have been recorded. The plot of pressure as a function of volume increases first, reaches a maximum, decreases, reaches a minimum and increases monotonously. The values of maximum and minimum pressures (pv max and pv min) due to fluid infusion are found to be, respectively, 42.4 +/- 15.4 mmHg and 33.1 +/- 12.2 mmHg. The pressure achieved the maximum and minimum values with infusion of 0.19 +/- 0.09 ml and 0.51 +/- 0.15 ml of fluid, respectively. The elastomechanical parameters of the Hart-Smith function that characterize the brain tissues have been evaluated by matching the experimentally obtained pressure-volume curves with the corresponding model generated curves. It is found that the agreement between the experimentally obtained pressure-volume curves and the corresponding Hart-Smith profile is satisfactory at a high inflation level but less so at the lower inflation level.

Animals↗
PubMed2003

Coupled prediction of protein secondary and tertiary structure.

The strong coupling between secondary and tertiary structure formation in protein folding is neglected in most structure prediction methods. In this work we investigate the extent to which nonlocal interactions in predicted tertiary structures can be used to improve secondary structure prediction. The architecture of a neural network for secondary structure prediction that utilizes multiple sequence alignments was extended to accept low-resolution nonlocal tertiary structure information as an additional input. By using this modified network, together with tertiary structure information from native structures, the Q3-prediction accuracy is increased by 7-10% on average and by up to 35% in individual cases for independent test data. By using tertiary structure information from models generated with the ROSETTA de novo tertiary structure prediction method, the Q3-prediction accuracy is improved by 4-5% on average for small and medium-sized single-domain proteins. Analysis of proteins with particularly large improvements in secondary structure prediction using tertiary structure information provides insight into the feedback from tertiary to secondary structure.

Computer Simulation↗
PubMed1995

Immune responses in MHC class II-deficient mice.

Major histocompatibility complex (MHC) class II molecules are heterodimeric cell surface proteins that are critically important for the development and function of cells in the immune system. In particular, the maturation of CD4+ T cells is dependent on the expression of MHC class II molecules on thymic epithelium, while the activation of these cells requires the expression of class II molecules on specialized antigen-presenting cells in the periphery. The importance of class II molecules is especially evident in humans who are afflicted with MHC class II-deficient combined immunodeficiency, as these individuals die at an early age unless provided with a bone marrow transplant. Here we discuss the functional consequences of MHC class II deficiency in a mouse model generated by gene targeting in embryonic stem (ES) cells. These mice have proved to be valuable reagents for dissecting the mechanisms by which MHC class II molecules control the maturation and activation of lymphocytes as well as for elucidating the role of these cells in various immune responses.

Animals↗
PubMed1993

An automated method for modeling proteins on known templates using distance geometry.

We present an automated method incorporated into a software package, FOLDER, to fold a protein sequence on a given three-dimensional (3D) template. Starting with the sequence alignment of a family of homologous proteins, tertiary structures are modeled using the known 3D structure of one member of the family as a template. Homologous interatomic distances from the template are used as constraints. For nonhomologous regions in the model protein, the lower and the upper bounds for the interatomic distances are imposed by steric constraints and the globular dimensions of the template, respectively. Distance geometry is used to embed an ensemble of structures consistent with these distance bounds. Structures are selected from this ensemble based on minimal distance error criteria, after a penalty function optimization step. These structures are then refined using energy optimization methods. The method is tested by simulating the alpha-chain of horse hemoglobin using the alpha-chain of human hemoglobin as the template and by comparing the generated models with the crystal structure of the alpha-chain of horse hemoglobin. We also test the packing efficiency of this method by reconstructing the atomic positions of the interior side chains beyond C beta atoms of a protein domain from a known 3D structure. In both test cases, models retain the template constraints and any additionally imposed constraints while the packing of the interior residues is optimized with no short contacts or bond deformations. To demonstrate the use of this method in simulating structures of proteins with nonhomologous disulfides, we construct a model of murine interleukin (IL)-4 using the NMR structure of human IL-4 as the template. The resulting geometry of the nonhomologous disulfide in the model structure for murine IL-4 is consistent with standard disulfide geometry.

Algorithms↗
PubMed2004

QSAR modeling of HIV-1 reverse transcriptase inhibitor 2-amino-6-arylsulfonylbenzonitriles and congeners using molecular connectivity and E-state parameters.

Anti-HIV-1 activity (assayed in MT-4 cell line) and HIV-1 reverse transcriptase (RT) binding affinity of 2-amino-6-arylsulfonylbenzonitriles and their thio and sulfinyl congeners (Chan et al., J. Med. Chem., 2001, 44, 1866) have been modeled using E-state index along with molecular connectivity and indicator parameters in an attempt to explore the different fragments of the molecules contributing significantly to the activities. Stepwise multiple regression procedure was adopted to develop the topological models. The models generated were of acceptable statistical quality and predictive potential. The results show that for both the response variables, first order fragmental valence molecular connectivity of the meta substituents of the aryl ring plays a significant role: second meta substituents show supraadditive action on the activities probably due to enhanced binding (presumably through dispersion interaction) of the ligand with the binding site. Again, presence of sulfone moiety contributes significantly to the activities. Further, presence of meta-trifluoromethyl group at the aryl ring is detrimental for both the activity parameters. Additionally, the anti-HIV-1 model shows specific contributions of the E-state values of different atoms and positive contribution of the ortho-methoxy group present on the aryl ring.

Amination↗
PubMed1999

Systematic search for disease loci for complex genetic traits: a study based on simulated population data.

Simulated family data were analyzed using one- and two-locus disease models to detect linkage. Regions of interest, found on chromosomes 3 and 5, were then further analyzed to look for evidence of locus interaction and/or genetic heterogeneity. Methods described by Falk [1993] were used to separate families into subsets likely to be genetically homogeneous. Based on the results, it was concluded that there were at least two distinct disease loci, one on chromosome 3 and one on chromosome 5, and that these loci were probably not interacting but were expressing two distinct forms of the disease. The identification of these loci was in agreement with the generating model. However, the analysis did not show any indication of a two-locus form of the disease or detect a disease locus on chromosome 1. This could be due to lack of power and/or too small a sample size for the method of analysis.

Chromosome Mapping↗
PubMed2006

Angiotensinogen promoter sequence variants in essential hypertension.

BACKGROUND: Essential hypertension is a complex multifactorial disease caused by ill-defined genetic factors. The angiotensinogen (AGT) gene has been implicated as a risk factor in essential hypertension. METHODS: To assess the role of AGT in hypertension, we evaluated two polymorphisms (A-6G and C-20A) in the 5' region of the gene that have been shown to have a role in transcriptional regulation. A total of 463 subjects were studied: 243 African Americans (26 male and 34 female normotensives, 66 male and 117 female hypertensives) and 220 whites (35 male and 60 female normotensives, 55 male and 70 female hypertensives). African American and white subjects were examined individually, as significant differences in allele and genotype frequencies were observed between these two cohorts. RESULTS: White female hypertensives and normotensives differed significantly in genotype frequency at C-20A (P = .02). No other single site comparisons were significantly different between hypertensives and normotensives in either the white or African American samples. Haplotype frequencies in white males also differed significantly between phenotypic classes (P = .05). To evaluate the data further, we assessed all polymorphic sites simultaneously by the examination of multisite interaction and determined the single best genetic model for each population. A model that included both sites and gender correctly predicted hypertension status in the white population 59.1% of the time (P = .039). The model generated for the African American population was not significant. CONCLUSIONS: Our results suggest that a complex set of genetic factors interact with gender to predispose whites to hypertension.

Adenine↗
PubMed2003

The hive bee to forager transition in honeybee colonies: the double repressor hypothesis.

In summer, the honeybee (Apis mellifera) worker population consists of two temporal castes, a hive bee group performing a multitude of tasks including nursing inside the nest, and a forager group specialized on collecting nectar, pollen, water and propolis. Elucidation of the regulatory mechanisms responsible for the hive bee to forager transition holds a prominent position within present day sociobiology. Here we suggest a new explanation dubbed the "double repressor hypothesis" aimed to account for the substantial amount of empirical data in this field. This is the first time where both the regular transition and starvation-induced precocious transition are explained within the same regulatory framework. We suggest that the transition is under regulatory control by an internal and an external repressor of the allatoregulatory central nervous system, where these two repressors modulate a positive regulatory feedback loop involving juvenile hormone (JH) and the lipoprotein vitellogenin. The concepts of age-neutrality, fixed and variable response thresholds and reinforcement are integral parts of our explanation, and in addition they are given explicit physiological content. The hypothesis is represented by a differential equations model at the level of the individual bee, and by a discrete individual-based colony model. The two models generate predictions in accordance with empirical data concerning the cumulative probability of becoming a forager, mean age at onset of foraging, reversal of foragers, time window of reversal, relationship between JH titre and onset of foraging, relative representations of genotypic groups, and effects of forager depletion and confinement.

Aging↗
PubMed2005

Glycyrrhizae Radix attenuates peroxynitrite-induced renal oxidative damage through inhibition of protein nitration.

We investigated the protective effects of Glycyrrhizae Radix extract against peroxynitrite (ONOO-)-induced oxidative stress under in vivo as well as in vitro conditions. The extract showed strong ONOO- and nitric oxide (NO) scavenging effects under in vitro system, in particular higher activity against ONOO-. Furthermore, elevations of plasma 3-nitrotyrosine levels, indicative of in vivo ONOO- generation and NO production, were shown using a rat in vivo ONOO(-)-generation model of lipopolysaccharide injection plus ischemia-reperfusion. The administration of Glycyrrhizae Radix extract at doses of 30 and 60 mg/kg body weight/day for 30 days significantly reduced the concentrations of 3-nitrotyrosine and NO and decreased inducible NO synthase activity. In addition, the nitrated tyrosine protein level and myeloperoxidase activity in the kidney were significantly lower in rats given Glycyrrhizae Radix extract than in control rats. However, the administration of Glycyrrhizae Radix extract did not result in either significant elevation of glutathione levels or reduction of lipid peroxidation in renal mitochondria. Moreover, the in vivo ONOO- generation system resulted in renal functional impairment, reflected by increased plasma levels of urea nitrogen and creatinine, whereas the administration of Glycyrrhizae Radix extract reduced these levels significantly, implying that the renal dysfunction induced by ONOO- was ameliorated. The present study suggests that Glycyrrhizae Radix extract could protect the kidneys against ONOO- through scavenging ONOO- and/or its precursor NO, inhibiting protein nitration and improving renal dysfunction caused by ONOO-.

Animals↗
PubMed2005

Differential kinetic behavior and distribution for pteroylglutamic acid and reduced folates: a revised hypothesis of the primary site of PteGlu metabolism in humans.

Single (13)C(6)-labeled doses of pteroylmonoglutamic acid (PteGlu: 634 nmol; n = 14), (6S-)5-formyltetrahydrofolic acid (431-569 nmol; n = 16), or [(15)N(1-7)]-intrinsically labeled spinach (mainly 5-methyltetrahydrofolate) (588 nmol; n = 14) were fed to fasting adult volunteers. Plasma-labeled 5-methyltetrahydrofolic acid responses were monitored for 8 h. There was a slower rate of increase in plasma-labeled 5-methyltetrahydrofolic acid and longer time to peak (171 +/- 9 min; mean +/- SEM) following an oral dose of [(13)C(6)]PteGlu than either [(13)C(6)]5-formyltetrahydrofolic acid (54 +/- 10 min) or [(15)N(1-7)]spinach folate (60 +/- 13 min) suggesting saturated metabolic capacity for the biotransformation of PteGlu. Mathematical modeling generated a significantly higher mean "apparent absorption" for 5-formyltetrahydrofolic acid (38%) and spinach folate (44%) than for PteGlu (24%). The high "relative absorption" of reduced folates to PteGlu was unexpected given that PteGlu itself, from (14)C-tracer mass balance experiments, is almost completely absorbed. Although it is ubiquitously accepted that a physiological dose of PteGlu is reduced and methylated in the epithelial cells of the small intestine, and that essentially only 5-methyltetrahydrofolic acid is exported into the hepatic portal vein (HPV), as is the case for absorbed reduced 1-carbon-substituted folates, modeling indicated greater liver sequestration when PteGlu was used as the test dose, suggesting that PteGlu enters the HPV unaltered and that the liver is the primary site of initial metabolism. Because of the observed differential plasma response and the hypothesized difference in the site of initial metabolism, the historical use of PteGlu as a "reference folate" in studies of folate bioavailability is seriously questioned.

Erythrocytes↗
PubMed2006

Pharmacophore-based discovery of ligands for drug transporters.

The ability to identify ligands for drug transporters is an important step in drug discovery and development. It can both improve accurate profiling of lead pharmacokinetic properties and assist in the discovery of new chemical entities targeting transporters. In silico approaches, especially pharmacophore-based database screening methods have great potential in improving the throughput of current transporter ligand identification assays, leading to a higher hit rate by focusing in vitro testing to the most promising hits. In this review, the potential of different in silico methods in transporter ligand identification studies are compared and summarized with an emphasis on pharmacophore modeling. Various implementations of pharmacophore model generation, database compilation and flexible screening algorithms are also introduced. Recent successful utilization of database searching with pharmacophores to identify novel ligands for the pharmaceutically significant transporters hPepT1, P-gp, BCRP, MRP1 and DAT are reviewed and the challenges encountered with current approaches are discussed.

Algorithms↗
PubMed2004

Simple statistical models predict C-to-U edited sites in plant mitochondrial RNA.

BACKGROUND: RNA editing is the process whereby an RNA sequence is modified from the sequence of the corresponding DNA template. In the mitochondria of land plants, some cytidines are converted to uridines before translation. Despite substantial study, the molecular biological mechanism by which C-to-U RNA editing proceeds remains relatively obscure, although several experimental studies have implicated a role for cis-recognition. A highly non-random distribution of nucleotides is observed in the immediate vicinity of edited sites (within 20 nucleotides 5' and 3'), but no precise consensus motif has been identified. RESULTS: Data for analysis were derived from the the complete mitochondrial genomes of Arabidopsis thaliana, Brassica napus, and Oryza sativa; additionally, a combined data set of observations across all three genomes was generated. We selected datasets based on the 20 nucleotides 5' and the 20 nucleotides 3' of edited sites and an equivalently sized and appropriately constructed null-set of non-edited sites. We used tree-based statistical methods and random forests to generate models of C-to-U RNA editing based on the nucleotides surrounding the edited/non-edited sites and on the estimated folding energies of those regions. Tree-based statistical methods based on primary sequence data surrounding edited/non-edited sites and estimates of free energy of folding yield models with optimistic re-substitution-based estimates of approximately 0.71 accuracy, approximately 0.64 sensitivity, and approximately 0.88 specificity. Random forest analysis yielded better models and more exact performance estimates with approximately 0.74 accuracy, approximately 0.72 sensitivity, and approximately 0.81 specificity for the combined observations. CONCLUSIONS: Simple models do moderately well in predicting which cytidines will be edited to uridines, and provide the first quantitative predictive models for RNA edited sites in plant mitochondria. Our analysis shows that the identity of the nucleotide -1 to the edited C and the estimated free energy of folding for a 41 nt region surrounding the edited C are the most important variables that distinguish most edited from non-edited sites. However, the results suggest that primary sequence data and simple free energy of folding calculations alone are insufficient to make highly accurate predictions.

Arabidopsis↗
PubMed2006

Cultural coevolution of norm adoption and enforcement when punishers are rewarded or non-punishers are punished.

A number of studies have shown that social norms can be maintained at a high frequency when norm-violators are punished. However, there remains the problem of how norm-adopters and punishers coevolve within a single group. We develop a recursive system to examine the coevolution of norm-adopters and punishers where the viability of punishers is enhanced by one of two "metanorms": (1) Norm-observers reward punishers for punishing norm-violators (Reward Model); (2) Punishers punish non-punishers (Punishment Model). Both models generate a bistable system and each is characterized in phenotype frequency space by a distinct region of attraction to the equilibrium consisting of only norm-adopting punishers. Using a Monte Carlo simulation, we find that cultural drift may allow norm-adopters and punishers to coevolve from invasion into this region of attraction, resulting in their fixation. This coevolution typically occurs across a wider range of conditions under the reward- than the punishment-based metanorm. We also show that, under appropriate conditions, a large negative statistical association between the two traits may evolve only under the Reward Model. Furthermore, for each metanorm, a population of norm-adopters who always observe the norm can be locally stable over a continuum of punishment frequencies.

Cultural Evolution↗
PubMed1987

Immunological discrimination between self and non-self by precursor depletion and memory accumulation.

We study processes by which T-lymphocytes "learn" to discriminate "self" from "non-self". We show that intrinsic features of the T cell activation and proliferation process are sufficient to tolerize (self) reactive T-lymphocyte clones. Self vs non-self discrimination therefore develops without any down-regulatory (e.g. suppressive) interactions. T-lymphocyte clones will expand by proliferation only if the IL2 concentration is high enough to induce a proliferation rate larger than the rate of cell decay. This concentration is the proliferation threshold. Because effector T cells are short-lived the proliferation threshold must be quite high. Such high numbers of cells producing IL2 are achieved only when sufficient (memory) precursors are activated. Self and non-self antigens differ with respect the number of (memory) precursor cells they accumulate, as a result of two processes, i.e. precursor depletion and memory accumulation, and can thus be discriminated. Precursor depletion: the dynamics of long-lived precursors can cause tolerization. In neonatal circumstances precursor influx is still low, newborn cells reacting with self antigens are immediately activated, generating (few), i.e. fewer than the proliferation threshold, effectors that decay rapidly. Thus total lymphocyte numbers remain low, yielding self tolerance. Conversely, large doses of similar antigens introduced in mature systems push "their" lymphocyte clone over the proliferation threshold because a large (accumulated) precursor population is rapidly activated. Small doses are however low zone tolerized. Memory accumulation: peripheral T-lymphocyte populations in fact consist of a mixture of virgin precursors and memory cells. If the formation process of (long-lived) memory cells is taken into account and virgin precursors are made short-lived, the proliferation threshold again accounts for self non-self discrimination. Memory cells accumulate when antigenic restimulation is low; it is low when the antigen concentration and/or the antigen affinity is low. Therefore self antigens, which are present in relatively high concentrations, fail to accumulate high affinity memory cells, and are hence tolerated. Memory cells crossreacting to self antigens with low affinity, however accumulate neonatally, pushing those clones over the proliferation threshold whenever "their" high affinity antigen enters the immune system. Thus the model generates differences in the antigenicity (i.e. memory precursor frequency) of self and non-self.(ABSTRACT TRUNCATED AT 400 WORDS)

Antigens↗
PubMed2003

Reconsidering the role of private health funds in Australia: a dynamic model.

In recent years the private sector has played a more important role in the funding and provision of Australian hospital care as a consequence of federal government policies aimed at increasing participation in private health insurance (health funds). These policies include tax incentives, a 30% rebate on premiums and lifetime community rating (premiums set by age). While these policies have improved the short-term profitability of the private sector, its long-term success is not certain. This is because negotiations between health funds and private hospitals are often myopic, the nature of the insurance product may be inefficient, and there is a general lack of academic research on the private sector. This paper highlights the importance of the relationship between health funds and private hospitals in ensuring the long-term viability of the industry. It uses a simple overlapping generations model to demonstrate that it is not only the price that health funds pay that impacts on the capital value of hospitals, but also it is important how they structure their policies and attract individuals. The model demonstrates the potential benefits of implementing health insurance based on intertemporal transfers of funds rather than the current cross-subsidization. Such a policy would see health funds become an important store of capital. Also highlighted are the difficulties of discussing fundamental changes to the health care system. While recent health care reforms have been described as driven by ideology rather than evidence, in the Australian context there is little evidence on which to base policy. Researchers need to be more proactive in their consideration and evaluation of alternative health care policies. Through quality research on the private sector, academics can better guide policy makers at the national and institutional level.

Aged↗
PubMed2005

Evaluation of a generalized regression artificial neural network for extending cadmium's working calibration range in graphite furnace atomic absorption spectrometry.

A generalized regression artificial neural network (GRANN) was developed and evaluated for modeling cadmium's nonlinear calibration curve in order to extend its upper concentration limit from 4.0 microg L-1 up to 22.0 microg L-1. This type of neural network presents important advantages over the more popular backpropagation counterpart which are worth exploiting in analytical applications, namely, (1) a smaller number of variables have to be optimized, with the subsequent reduction in "development hassle"; and, (2) shorter development times, thanks to the fact that the adjustment of the weights (the artificial synapses) is a non-iterative, one-pass process. A backpropagation artificial neural network (BPANN), a second-order polynomial, and some less frequently employed polynomial and exponential functions (e.g., Gaussian, Lorentzian, and Boltzmann), were also evaluated for comparison purposes. The quality of the fit of the various models, assessed by calculating the root mean square of the percentage deviations, was as follows: GRANN>Boltzmann>second-order polynomial>BPANN>Gauss>Lorentz. The accuracy and precision of the models were further estimated through the determination of cadmium in the certified reference material "Trace Metals in Drinking Water" (High Purity Standards, Lot No. 490915), which has a cadmium certified concentration (12.00+/-0.06 microg L-1) that lies in the nonlinear regime of the calibration curve. Only the models generated by the GRANN and BPANN accurately predicted the concentrations of a series of solutions, prepared by serial dilution of the CRM, with cadmium concentrations below and above the maximum linear calibration limit (4.0 microg L-1). Extension of the working range by using the proposed methodology represents an attractive alternative from the analytical point of view, since it results in less specimen manipulation and consequently reduced contamination risks without compromising either the accuracy or the precision of the analyses. The implementation of artificial neural networks also helps to reduce the trial-and-error task of looking for the right mathematical model from among the many possibilities currently available in the various scientific and statistic software packages.

Journal Article↗
PubMed1998

Refinement of a limit cycle oscillator model of the effects of light on the human circadian pacemaker.

In 1990, Kronauer proposed a mathematical model of the effects of light on the human circadian pacemaker. Although this model predicted many general features of the response of the human circadian pacemaker to light exposure, additional data now available enable us to refine the original model. We first refined the original model by incorporating the results of a dose response curve to light into the model's predicted relationship between light intensity and the strength of the drive onto the pacemaker. Data from three bright light phase resetting experiments were then used to refine the amplitude recovery characteristics of the model. Finally, the model was tested and further refined using data from an extensive phase resetting experiment in which a 3-cycle bright light stimulus was presented against a background of dim light. In order to describe the results of the four resetting experiments, the following major refinements to the original model were necessary: (i) the relationship between light intensity (I) and drive onto the pacemaker was reduced from I1/3 to I0.23 for light levels between 150 and 10,000 lux; (ii) the van der Pol oscillator from the original model was replaced with a higher-order limit cycle oscillator so that amplitude recovery is slower near the singularity and faster near the limit cycle; (iii) a direct effect of light on circadian period (tau x) was incorporated into the model such that as I increases, tau x decreases, which is in accordance with "Aschoff's rule". This refined model generates the following testable predictions: it should be difficult to enhance normal circadian amplitude via bright light; near the critical point of a type 0 phase response curve (PRC) the slope should be steeper than it is in a type 1 PRC; and circadian period measured during forced desynchrony should be directly affected by ambient light intensity.

Circadian Rhythm↗
PubMed2003

ATP-mediated conformational changes in the RecA filament.

The crystal structure of the E. coli RecA protein was solved more than 10 years ago, but it has provided limited insight into the mechanism of homologous genetic recombination. Using electron microscopy, we have reconstructed five different states of RecA-DNA filaments. The C-terminal lobe of the RecA protein is modulated by the state of the distantly bound nucleotide, and this allosteric coupling can explain how mutations and truncations of this C-terminal lobe enhance RecA's activity. A model generated from these reconstructions shows that the nucleotide binding core is substantially rotated from its position in the RecA crystal filament, resulting in ATP binding between subunits. This simple rotation can explain the large cooperativity in ATP hydrolysis observed for RecA-DNA filaments.

Adenosine Triphosphate↗