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An experimental and theoretical model for solar UVA-irradiation of soluble eumelanin: towards modelling UVA-photoreactions in the melanosome?

A model is developed for the UVA-irradiation of soluble eumelanin exposed to levels of irradiation comparable to sunlight. Radical production was determined in soluble dl- and l-dopa melanins exposed to solar levels of UVA, using electron spin resonance spectroscopy and the spin trap 5,5-dimethyl-1-pyrroline N-oxide (DMPO). Steady-state concentrations of DMPO-O(2)H(.-), which increased up to 0.3 mg/ml melanin, and then declined above 0.3 mg/ml, were detected at pH 4.5. The kinetic model incorporated the photosensitizing and radical-scavenging reactions of eumelanin, and assumed semiquinone radical reduction of oxygen to be fast compared to disproportionation. The model is consistent with experimental data for melanin concentrations <0.1 mg/ml; but >0.1 mg/ml melanin is consistent only with data at raised oxygen tension. The rate-constant for reaction of the melanin semiquinone-radical and oxygen is estimated to be 10(3) mol(-1)dm(3)s(-1). In this model, where DMPO competes with melanin for HO(2)(.-), at ambient oxygen levels, eumelanin exposed to solar levels of UVA photosensitizes superoxide at concentrations <0.3 mg/ml melanin, and is increasingly stable towards oxidation when >0.3 mg/ml concentration. Eumelanin could have a negligible screening effect <0.1 mg/ml and very strong screening >1 mg/ml. This model would be biologically relevant if soluble forms of eumelanin were shown to exist in vivo, and is potentially useful for studies of the photochemistry and photophysics of eumelanin and phaeomelanin and to explore the effects of metal-ions, proteins and lipids in a model system.

Cyclic N-Oxides↗

3D-QSAR and receptor modeling of tyrosine kinase inhibitors with flexible atom receptor model (FLARM).

A set of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors was investigated with the aim of developing 3D-QSAR models using the Flexible Atom Receptor Model (FLARM) method. Some 3D-QSAR models were built with high correlation coefficients, and the FLARM method predicted the biological activities of compounds in test set well. The FLARM method also gave the pseudoreceptor model, which indicates the possible interactions between the receptor and the ligand. The possible interactions include two hydrogen bonds, one hydrophobic interaction, and one sulfur-aromatic interaction, which are in accord with those in the pharmacophore model given by the scientists at Novartis. This shows that the FLARM method can bridge 3D-QSAR and receptor modeling in computer-aided drug design. Pharmacophore can be obtained according to these results, and 3D searching can then be done with databases to find the lead compound of EGFR tyrosine kinase inhibitors.

Binding Sites↗

Quantitative structure--activity relationships. 7. The bilinear model, a new model for nonlinear dependence of biological activity on hydrophobic character.

The bilinear model, log 1/C =a log P-b log (betaP+1) +C, a new model for nonlinear dependence of biological activity on hydrophobic character, is applied to 57 data sets of biological activity values in homologous series. From a comparison of the statistical parameters and the residuals obtained with the bilinear model and the parabolic model, the superiority of the bilinear model for a precise quantitative description of both linear and nonlinear parts of sturcture-activity relationships can be derived; the bilinear model explains the particular effect that in homologous series the relationship between biological activity and hydrophobic character is strictly linear for the lower members, while for higher members this relationship is nonlinear.

Animals↗

Mutual enhancements of CFD modeling and experimental data: a case study of 1-mum particle deposition in a branching airway model.

In order to better understand aerosol dynamics and deposition in the complex flow field of the respiratory tract, both in vitro experiments and numerical modeling techniques have widely been employed. Computational fluid dynamics (CFD) modeling offers the flexibility of easily modifying system parameters such as flow rates, particle sizes, system geometry, and heterogeneous outlet conditions. However, a number of numerical errors and artifacts can lead to nonphysical CFD results. Experimental methods offer the advantage of physical realism; however, parameter variation is often difficult. The objective of this study is to illustrate the use of CFD to enhance the understanding of experimental results. In parallel, the selected experimental results have been used to partially validate the CFD predictions. A specific case study has been considered focusing on 1-mum particle depositions in a physiologically realistic bifurcation (PRB) model of respiratory generations 3-5. Previous experiments in this system report a deposition rate of approximately 0.01%. An in-depth CFD analysis has been employed to evaluate two cases of the empirical model. The first case consists of only the PRB double bifurcation geometry. The second case includes a portion of the experimental particle delivery system, which may influence the entering velocity and particle profiles. To assess the influence of upstream transition and turbulence, each of the two cases considered has been evaluated using laminar and low Reynolds number k-omega approximations. Results indicate that both upstream flow effects and turbulent or transitional flow play a significant role in determining the deposition of 1-mum particles in the model considered. Simulating upstream flow effects and laminar flow was required to match the empirically reported deposition fraction and provided a two orders of magnitude improvement over initial CFD estimates. This study highlights the need to consider the effects of experimental particle generation systems on velocity and particle profiles entering respiratory models. Future work is necessary to investigate the mechanisms responsible for the experimentally observed local deposition patterns.

Aerosols↗

Animal models for the study of childhood leukemia: considerations for model identification and optimization to identify potential risk factors.

Leukemias are the most common pediatric malignancies diagnosed in western industrialized societies. In spite of the substantial incidence of childhood leukemia in the United States and other countries, neither epidemiology studies conducted in human populations nor hazard identification studies conducted using traditional animal models have identified environmental or other factors that are directly linked to increased risk of disease. Molecular biology data and mathematical modeling of incidence patterns suggest that pediatric leukemogenesis may occur through a multistage or "multihit" mechanism that involves both in utero and postnatal events. The authors propose that pediatric leukemias can be modeled experimentally using a "multihit" paradigm analogous to the "initiation-promotion" and "complete carcinogenesis" models developed for tumor induction in mouse skin and rat liver. In this model for childhood leukemia, an initial genetic alteration occurs during in utero or early postnatal development, but clinical disease develops only upon additional genetic or nongenetic events that occur during the postnatal period. Application of this multistage or "multihit" model to hazard assessment studies conducted in transgenic or knockout mice carrying relevant molecular lesions may provide a sensitive approach to the identification of environmental agents that are important risk factors for childhood leukemia.

Animals↗

On models of quantitative genetic variability: a stabilizing selection-balance model.

A model of stabilizing selection on a multilocus character is proposed that allows the maintenance of stable allelic polymorphism and linkage disequilibrium. The model is a generalization of Lerner's model of homeostasis in which heterozygotes are less susceptible to environmental variation and hence are superior to homozygotes under phenotypic stabilizing selection. The analysis is carried out for weak selection with a quadratic-deviation model for the stabilizing selection. The stationary state is characterized by unequal allele frequencies, unequal proportions of complementary gametes, and a reduction of the genetic (and phenotypic) variance by the linkage disequilibrium. The model is compared with Mather's polygenic balance theory, with models that include mutation-selection balance, and others that have been proposed to study the role of linkage disequilibrium in quantitative inheritance.

Alleles↗

The hormetic dose-response model is more common than the threshold model in toxicology.

The threshold dose-response model is widely viewed as the most dominant model in toxicology. The present study was designed to test the validity of the threshold model by assessing the responses of doses below the toxicological NOAEL (no observed adverse effect level) in relationship to the control response (i.e., unexposed group). Nearly 1,800 doses below the NOAEL, from 664 dose-response relationships derived from a previously published database that satisfied a priori entry criteria, were evaluated. While the threshold model predicts a 1:1 ratio of responses "greater than" to "less than" the control response (i.e., a random distribution), a 2.5:1 ratio (i.e., 1171:464) was observed, reflecting 31% more responses above the control value than expected (p < 0.0001). The mean response (calculated as % control response) of doses below the NOAEL was 115.0% +/- 1.5 standard error of the mean (SEM). These findings challenge the long-standing belief in the primacy of the threshold model in toxicology (and other areas of biology involving dose-response relationships) and provide strong support for the hormetic-like biphasic dose-response model characterized by a low-dose stimulation and a high-dose inhibition. These findings may affect numerous aspects of toxicological and biological/biomedical research related to dose-response relationships, including study design, risk assessment, as well as chemotherapeutic strategies.

Animals↗

Nonlinear statistical modeling and model discovery for cardiorespiratory data.

We present a Bayesian dynamical inference method for characterizing cardiorespiratory (CR) dynamics in humans by inverse modeling from blood pressure time-series data. The technique is applicable to a broad range of stochastic dynamical models and can be implemented without severe computational demands. A simple nonlinear dynamical model is found that describes a measured blood pressure time series in the primary frequency band of the CR dynamics. The accuracy of the method is investigated using model-generated data with parameters close to the parameters inferred in the experiment. The connection of the inferred model to a well-known beat-to-beat model of the baroreflex is discussed.

Algorithms↗

Analysis of the plant architecture via tree-structured statistical models: the hidden Markov tree models.

Plant architecture is the result of repetitions that occur through growth and branching processes. During plant ontogeny, changes in the morphological characteristics of plant entities are interpreted as the indirect translation of different physiological states of the meristems. Thus connected entities can exhibit either similar or very contrasted characteristics. We propose a statistical model to reveal and characterize homogeneous zones and transitions between zones within tree-structured data: the hidden Markov tree (HMT) model. This model leads to a clustering of the entities into classes sharing the same 'hidden state'. The application of the HMT model to two plant sets (apple trees and bush willows), measured at annual shoot scale, highlights ordered states defined by different morphological characteristics. The model provides a synthetic overview of state locations, pointing out homogeneous zones or ruptures. It also illustrates where within branching structures, and when during plant ontogeny, morphological changes occur. However, the labelling exhibits some patterns that cannot be described by the model parameters. Some of these limitations are addressed by two alternative HMT families.

Combretaceae↗

Experimental determination of the anisotropy function for the model 200 103Pd "light seed" and derivation of the anisotropy constant based upon the linear quadratic model.

Since the publication of the AAPM Task Group 43 report in 1995, Model 200 103Pd seed, which has been widely used in prostate seed implants and other brachytherapy procedures, has undergone some changes in its internal geometry resulting from the manufacturer's transition from lower specific activity reactor-produced 103Pd ("heavy seeds") to higher specific activity accelerator-produced radioactive material ("light seeds"). Based on previously reported theoretical calculations and measurements, the dose rate constants and the radial dose functions of the two types of seeds are nearly the same and have already been reported. In this work, the anisotropy function of the "light seed" was experimentally measured and an averaging method for the determination of the anisotropy constant from distance-dependent values of anisotropy factors is presented based upon the continuous low dose rate irradiation linear quadratic model for cell killing. The anisotropy function of Model 200 103Pd "light seeds" was measured in a Solid Water phantom using 1 X 1 x 1 mm micro LiF TLD chips at radial distances of 1, 2, 3, 4, 5, and 6 cm and at angles from 0 to 90 degrees with respect to the longitudinal axis of the seeds. At a radial distance of 1 cm, the measured anisotropy function of the 103Pd "light seed" is considerably lower than that of the 103Pd "heavy seed" reported in the TG 43 report. Our measured values at all radial distances are in excellent agreement with the results of a Monte Carlo simulation reported by Weaver, except for points along and near the seed longitudinal axis. The anisotropy constant of the 103Pd "light seed" was calculated using the linear quadratic biological model for cell killing in 30 clinical implants. For the model 200 "light seed," it has a value of 0.865. However, our biological model calculations lead us to conclude that if the anisotropy factors of an interstitial brachytherapy seed vary significantly over radial distances anisotropy constant should not be used as an approximation for anisotropy characteristics of a brachytherapy seed.

Anisotropy↗

A mathematical model for the quantification of mitral regurgitation. Experimental validation in the canine model using contrast echocardiography.

BACKGROUND: Because the clearance of contrast from the left atrium (LA) relative to the left ventricle (LV) depends on the degree of mitral regurgitation (MR), we hypothesized that a mathematical model can be developed that would provide a quantitative estimation of MR from the washout of contrast from these chambers. METHODS AND RESULTS: After mathematically developing the model, we performed experiments in two groups of dogs with the use of contrast echocardiography. Group 1 consisted of nine dogs in which different degrees of MR were produced by creating ischemic LV dysfunction. Contrast was injected into the LV, and MR was graded visually on a scale of from 0 to 4+. Videointensity plots generated from the LA and LV were provided to the model. There was excellent correlation between visual assessment of MR and model-derived regurgitant fraction in the 33 stages: y = 0.16x + 0.002 (r = 0.97, p less than 0.001, SEE = 0.06). To obtain a more quantitative validation, we placed electromagnetic flow probes on the aorta and just cephalad to the mitral annulus in six dogs (group 2) during cardiopulmonary bypass. Different degrees of MR were produced by chordal traction and/or myocardial ischemia. Regurgitant fraction was calculated at each stage from the flow probe and videointensity data. There was excellent correlation between flow probe and model-derived regurgitant fraction (y = 0.90x + 0.03; r = 0.96, p less than 0.001, SEE = 0.06), and close interobserver and intraobserver correlations were noted using flow probe and contrast echocardiographic data. CONCLUSIONS: A mathematical model that uses the clearance of contrast from the LA relative to the LV can be used to accurately measure the severity of MR. These findings may have important practical implications for the quantification of MR.

Animals↗

A general approach to mixed effects modeling of residual variances in generalized linear mixed models.

We propose a general Bayesian approach to heteroskedastic error modeling for generalized linear mixed models (GLMM) in which linked functions of conditional means and residual variances are specified as separate linear combinations of fixed and random effects. We focus on the linear mixed model (LMM) analysis of birth weight (BW) and the cumulative probit mixed model (CPMM) analysis of calving ease (CE). The deviance information criterion (DIC) was demonstrated to be useful in correctly choosing between homoskedastic and heteroskedastic error GLMM for both traits when data was generated according to a mixed model specification for both location parameters and residual variances. Heteroskedastic error LMM and CPMM were fitted, respectively, to BW and CE data on 8847 Italian Piemontese first parity dams in which residual variances were modeled as functions of fixed calf sex and random herd effects. The posterior mean residual variance for male calves was over 40% greater than that for female calves for both traits. Also, the posterior means of the standard deviation of the herd-specific variance ratios (relative to a unitary baseline) were estimated to be 0.60 +/- 0.09 for BW and 0.74 +/- 0.14 for CE. For both traits, the heteroskedastic error LMM and CPMM were chosen over their homoskedastic error counterparts based on DIC values.

Analysis of Variance↗

Modelling the action of caloric stimulation of the vestibule. II. The mechanical model of the semi-circular canal considered as an inflatable structure.

In order to explain the mechanical effects that arise when a semi-circular canal is thermally stimulated in the horizontal position (i.e. in the absence of gravity effects) a physical model was used. The duct (corresponding to the canal) is deformable, the pressure transducer (corresponding to the ampulla) is not deformable. There is no thermal similarity but a dynamical similarity has been respected, so the mechanical phenomena occurring in the semi-circular canal and in the model are identical. The time scale is close to one. The physical model showed that the relative volume variations (fluid/duct) due to caloric stimulation lead to a pressure variation measured by the pressure transducer at the place of the ampulla and the cupula. The time history and the value of this pressure depend on the mechanical and thermal properties of the duct and the fluid. The qualitative responses of the physical model and of the vestibulo-ocular reflex after caloric stimulation were coherent. A numerical model simulating the same mechanisms yielded a quantitative estimation of the transcupular pressure arising in a horizontal semi-circular canal (i.e. without gravity dependent effects) during caloric stimulation. The physical model and the numerical simulation take no account of the inflating pressure variation.

Caloric Tests↗

Modeling and analyzing biomedical processes using workflow/Petri Net models and tools.

Computer simulation enables system developers to execute a model of an actual or theoretical system on a computer and analyze the execution output. We have been exploring the use of Petri Net (PN) tools to study the behavior of systems that are represented using three kinds of biomedical models: a biological workflow model used to represent biological processes, and two different computer-interpretable models of health care processes that are derived from clinical guidelines. We developed and implemented software that maps the three models into a single underlying process model (workflow), which is then converted into PNs in formats that are readable by several PN simulation and analysis tools. These analysis tools enabled us to simulate and study the behavior of two biomedical systems: a Malaria parasite invading a host cell, and patients undergoing management of chronic cough.

Algorithms↗

[Models of arterial pressure using a Windkessel type model: role of the functional arterial properties].

UNLABELLED: The Windkessel model is a linear model which does not take into account the structural and functional variations of the arteries related to the pulsatility of the blood pressure (BP) and its variations between systole and diastole. OBJECTIVE: To analyse the performance of a BP modelisation where the parameters of AC are adjusted in a dynamic fashion according to a curvilinear relationship of the arterial properties (compliance) in relationship to the BP between systole and diastole. DESIGN AND METHODS: 9 control subjects (age 25 +/- 3). The non invasive measures of the radial BP waveform (Millar tonometry) was compared to that constructed by an electric simulator reproducing the model in a sysmetrical network subdivised into 121 segments where we introduced for each subject: at cardiac level, the aortic stroke volume (Doppler echocardiography), and at the radial level, the dynamic values of compliance and diameter according to an arc-tangent model (measured by arterial echography NiUS02). RESULTS: The BP obtained by the adjusted model, where the AC parameter follows the curvilinear, relationship dV/dP measured experimentally, was not significantly different from the experimental, while in the constant model (AC at mean BP level) the systolic BP was different. CONCLUSION: This work shows in an experimental way the limits inherent in simplification in the Windkessel modelisation of the vascular system with constant parameters. It shows in a conduction artery the influence of the functional properties of the arterial wall on the level of systolic and diastolic BP.

Adult↗

Modeling evaluation of the fluid-dynamic microenvironment in tissue-engineered constructs: a micro-CT based model.

Natural cartilage remodels both in vivo and in vitro in response to mechanical stresses, hence mechanical stimulation is believed to be a potential tool to modulate extra-cellular matrix synthesis in tissue-engineered cartilage. Fluid-induced shear is known to enhance chondrogenesis in engineered cartilage constructs. The quantification of the hydrodynamic environment is a condition required to study the biochemical response to shear of 3D engineered cell systems. We developed a computational model of culture medium flow through the microstructure of a porous scaffold, during direct- perfused culture. The 3D solid model of the scaffold micro-geometry was reconstructed from 250 micro-computed tomography (micro-CT) images. The results of the fluid dynamic simulations were analyzed at the central portions of the fluid domain, to avoid boundary effects. The average, median and mode shear stress values calculated at the scaffold walls were 3.48, 2.90, and 2.45 mPa respectively, at a flow rate of 0.5 cm(3)/min, perfused through a 15 mm diameter scaffold, at an inlet fluid velocity of 53 microm/s. These results were compared to results estimated using a simplified micro-scale model and to results estimated using an analytical macro-scale porous model. The predictions given by the CT-based model are being used in conjunction with an experimental bioreactor model, in order to quantify the effects of fluid-dynamic shear on the growth modulation of tissue-engineered cartilage constructs, to potentially enhance tissue growth in vitro.

Bioreactors↗

Empirical support for a model of dieting: findings from structural equations modeling.

OBJECTIVE: This paper presents the results of an evaluation of a model of dieting (Huon, G.F., & Strong, K.G., International Journal of Eating Disorders, 23, 361-370, 1998). It represents the culmination of a large-scale time-extended study of dieting among adolescent girls. METHODS: Data were collected from approximately 1,000 girls. A battery of questionnaires assessed dieting status, social influence, vulnerability (conformity) disposition, protective social skills, and aspects of the familial context as core components of the model. RESULTS: When the data were subjected to analyses within structural equations modeling, all specific hypotheses within the model found strong support. Moreover, multiple indices revealed that the model had a very good fit with the data and accounted for 89% of the variance in commitment to dieting. CONCLUSION: This study provides strong support for the validity of Huon and Strong's model of dieting among Australian girls. Its generality among girls in other cultures remains to be established.

Adaptation, Psychological↗

AGBNP: an analytic implicit solvent model suitable for molecular dynamics simulations and high-resolution modeling.

We have developed an implicit solvent effective potential (AGBNP) that is suitable for molecular dynamics simulations and high-resolution modeling. It is based on a novel implementation of the pairwise descreening Generalized Born model for the electrostatic component and a new nonpolar hydration free energy estimator. The nonpolar term consists of an estimator for the solute-solvent van der Waals dispersion energy designed to mimic the continuum solvent solute-solvent van der Waals interaction energy, in addition to a surface area term corresponding to the work of cavity formation. AGBNP makes use of a new parameter-free algorithm to calculate the scaling coefficients used in the pairwise descreening scheme to take into account atomic overlaps. The same algorithm is also used to calculate atomic surface areas. We show that excellent agreement is achieved for the GB self-energies and surface areas in comparison to accurate, but much more expensive, numerical evaluations. The parameter-free approach used in AGBNP and the sensitivity of the AGBNP model with respect to large and small conformational changes makes the model suitable for high-resolution modeling of protein loops and receptor sites as well as high-resolution prediction of the structure and thermodynamics of protein-ligand complexes. We present illustrative results for these kinds of benchmarks. The model is fully analytical with first derivatives and is computationally efficient. It has been incorporated into the IMPACT molecular simulation program.

Algorithms↗