Protective effect of an extract from Ascaris suum in experimental arthritis models

We investigated the effect of an extract from a helminth (Ascaris suum) in zymosan-induced arthritis (ZYA) or collagen-induced arthritis (CIA). Rats and mice, respectively, received 1 mg and 0.1 mg zymosan intra-articularly (i.a.). Test groups received an A. suum extract either per os (p.o.) or intraperitoneally (i.p.) 30 min prior to i.a. zymosan. Controls received saline. Hypernociception was measured using the articular incapacitation test. Cell influx, nitrite, and cytokine levels were assessed in joint exudates. The synovia and distal femoral extremities were used for histopathology. Cartilage damage was assessed through determining glycosaminoglycan (GAG) content. DBA/1J mice were subjected to CIA. The test group received A. suum extract i.p. 1 day after CIA became clinically detectable. Clinical severity and hypernociception were assessed daily. Neutrophil influx was determined using myeloperoxidase activity. The A. suum extract, either i.p. or p.o., significantly and dose-dependently inhibited cell influx and hypernociception in ZYA in addition to reducing GAG loss and ameliorating synovitis. The A. suum extract reduced i.a. levels of NO, interleukin-1 beta (IL-1 beta), and IL-10 but not tumor necrosis factor alpha (TNF-alpha) in rats subjected to ZYA while reducing i.a. IL-10, but not IL-1 beta or TNIT-alpha, levels in mice. Clinically, mice subjected to CIA treated with the A. suum extract had less severe arthritis. Hypernociception, myeloperoxidase activity, and synovitis severity were significantly reduced. These data show that a helminth extract given p.o. protects from arthritis severity in two classical arthritis models. This A. suum effect is species independent and functions orally and parenterally. The results show clinical and structural benefits when A. suum extract is given either prophylactically or therapeutically.

The neuroprotective effect of dental pulp cells in models of Alzheimer`s and Parkinson`s disease

Aim of the present study was to investigate the neuroprotective effect of dental pulp cells (DPCs) in in vitro models of Alzheimer and Parkinson disease. Primary cultures of hippocampal and ventral mesencephalic neurons were treated for 24 h with amyloid beta (A beta(1-42)) peptide 1-42 and 6-OHDA, respectively. DPCs isolated from adult rat incisors were previously cultured in tissue culture inserts and added to the neuron cultures 2 days prior to neurotoxin treatment. Cell viability was assessed by the MTT assay. The co-culture with DPCs significantly attenuated 6-OHDA and A beta(1-42)-induced toxicity in primary cultures of mesencephalic and hippocampal neurons, and lead to an increase in neuronal viability in untreated cultures, suggesting a neurotrophic effect in both models. Furthermore, human dental pulp cells expressed a neuronal phenotype and produced the neurotrophic factors NGF, GDNF, BDNF, and BMP2 shown by microarray screening and antibody staining for the representative proteins. DPCs protected primary neurons in in vitro models of Alzheimer`s and Parkinson`s disease and can be viewed as possible candidates for studies on cell-based therapy.

The suitability of different FEA models for studying root fractures caused by wedge effect

Finite element analysis (FEA) utilizing models with different levels of complexity are found in the literature to study the tendency to vertical root fracture caused by post intrusion (""wedge effect""). The objective of this investigation was to verify if some simplifications used in bi-dimensional FEA models are acceptable regarding the analysis of stresses caused by wedge effect. Three plane strain (PS) and two axisymmtric (Axi) models were studied. One PS model represented the apical third of the root entirely, in dentin (PS-nG). The other models included gutta-percha in the apical third, and differed regarding dentin-post relationship: bonded (PS-B and Axi-B) or nonbonded (PS-nB and Axi-nB). Mesh discretization and material properties were similar for all cases. Maximum principal stress (sigma(max)) was analyzed as a response to a 165 N longitudinal load. Stress magnitude and orientation varied widely (PS-nG: 10.3 MPa; PS-B: 0.8 MPa; PS-nB: 10.4 MPa; Axi-13: 0.2 MPa, Axi-nB: 10.8 MPa). Axi-nB was the only model where all (sigma(max) vectors at the apical third were perpendicular to the model plane. Therefore, it is adequate to demonstrate the tendency to vertical root fractures caused by wedge effect. Axi-13 showed only part of the (sigma(max) perpendicular to the model plane while PS models showed sigma(max) on the model plane. In these models, sigma(max) orientation did not represent a situation where vertical root fracture would occur due to wedge effect. Adhesion between post and dentin significantly reduced (c) 2007 Wiley Periodicals, Inc.

Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits

Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.

A zero-augmented gamma mixed model for longitudinal data with many zeros

In many occupational safety interventions, the objective is to reduce the injury incidence as well as the mean claims cost once injury has occurred. The claims cost data within a period typically contain a large proportion of zero observations (no claim). The distribution thus comprises a point mass at 0 mixed with a non-degenerate parametric component. Essentially, the likelihood function can be factorized into two orthogonal components. These two components relate respectively to the effect of covariates on the incidence of claims and the magnitude of claims, given that claims are made. Furthermore, the longitudinal nature of the intervention inherently imposes some correlation among the observations. This paper introduces a zero-augmented gamma random effects model for analysing longitudinal data with many zeros. Adopting the generalized linear mixed model (GLMM) approach reduces the original problem to the fitting of two independent GLMMs. The method is applied to evaluate the effectiveness of a workplace risk assessment teams program, trialled within the cleaning services of a Western Australian public hospital.

Fitting genetic models to twin data with binary and ordered categorical responses: A comparison of structural equation modelling and Bayesian hierarchical models

We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.

Modelling adhesive joints with cohesive zone models: effect of the cohesive law shape of the adhesive layer

Adhesively-bonded joints are extensively used in several fields of engineering. Cohesive Zone Models (CZM) have been used for the strength prediction of adhesive joints, as an add-in to Finite Element (FE) analyses that allows simulation of damage growth, by consideration of energetic principles. A useful feature of CZM is that different shapes can be developed for the cohesive laws, depending on the nature of the material or interface to be simulated, allowing an accurate strength prediction. This work studies the influence of the CZM shape (triangular, exponential or trapezoidal) used to model a thin adhesive layer in single-lap adhesive joints, for an estimation of its influence on the strength prediction under different material conditions. By performing this study, guidelines are provided on the possibility to use a CZM shape that may not be the most suited for a particular adhesive, but that may be more straightforward to use/implement and have less convergence problems (e.g. triangular shaped CZM), thus attaining the solution faster. The overall results showed that joints bonded with ductile adhesives are highly influenced by the CZM shape, and that the trapezoidal shape fits best the experimental data. Moreover, the smaller is the overlap length (LO), the greater is the influence of the CZM shape. On the other hand, the influence of the CZM shape can be neglected when using brittle adhesives, without compromising too much the accuracy of the strength predictions.

Generalized models from Beta(p,2) densities with strong allee effect: dynamical approach

A dynamical approach to study the behaviour of generalized populational growth models from Bets(p, 2) densities, with strong Allee effect, is presented. The dynamical analysis of the respective unimodal maps is performed using symbolic dynamics techniques. The complexity of the correspondent discrete dynamical systems is measured in terms of topological entropy. Different populational dynamics regimes are obtained when the intrinsic growth rates are modified: extinction, bistability, chaotic semistability and essential extinction.

Layerwise mixed models for analysis of multilayered piezoelectric composite plates using least-squares formulation

This work provides an assessment of layerwise mixed models using least-squares formulation for the coupled electromechanical static analysis of multilayered plates. In agreement with three-dimensional (3D) exact solutions, due to compatibility and equilibrium conditions at the layers interfaces, certain mechanical and electrical variables must fulfill interlaminar C-0 continuity, namely: displacements, in-plane strains, transverse stresses, electric potential, in-plane electric field components and transverse electric displacement (if no potential is imposed between layers). Hence, two layerwise mixed least-squares models are here investigated, with two different sets of chosen independent variables: Model A, developed earlier, fulfills a priori the interiaminar C-0 continuity of all those aforementioned variables, taken as independent variables; Model B, here newly developed, rather reduces the number of independent variables, but also fulfills a priori the interlaminar C-0 continuity of displacements, transverse stresses, electric potential and transverse electric displacement, taken as independent variables. The predictive capabilities of both models are assessed by comparison with 3D exact solutions, considering multilayered piezoelectric composite plates of different aspect ratios, under an applied transverse load or surface potential. It is shown that both models are able to predict an accurate quasi-3D description of the static electromechanical analysis of multilayered plates for all aspect ratios.

Algebraic structure for interaction on mixed models

Binary operations on commutative Jordan algebras, CJA, can be used to study interactions between sets of factors belonging to a pair of models in which one nests the other. It should be noted that from two CJA we can, through these binary operations, build CJA. So when we nest the treatments from one model in each treatment of another model, we can study the interactions between sets of factors of the first and the second models.

From weak Allee effect to no Allee effect in Richards’ growth models

Population dynamics have been attracting interest since many years. Among the considered models, the Richards’ equations remain one of the most popular to describe biological growth processes. On the other hand, Allee effect is currently a major focus of ecological research, which occurs when positive density dependence dominates at low densities. In this chapter, we propose the dynamical study of classes of functions based on Richards’ models describing the existence or not of Allee effect. We investigate bifurcation structures in generalized Richards’ functions and we look for the conditions in the (β, r) parameter plane for the existence of a weak Allee effect region. We show that the existence of this region is related with the existence of a dovetail structure. When the Allee limit varies, the weak Allee effect region disappears when the dovetail structure also disappears. Consequently, we deduce the transition from the weak Allee effect to no Allee effect to this family of functions. To support our analysis, we present fold and flip bifurcation curves and numerical simulations of several bifurcation diagrams.

Explosion birth and extinction: Double big bang bifurcations and Allee effect in Tsoularis-Wallace's growth models

This work concerns dynamics and bifurcations properties of a new class of continuous-defined one-dimensional maps: Tsoularis-Wallace's functions. This family of functions naturally incorporates a major focus of ecological research: the Allee effect. We provide a necessary condition for the occurrence of this phenomenon of extinction. To establish this result we introduce the notions of Allee's functions, Allee's effect region and Allee's bifurcation curve. Another central point of our investigation is the study of bifurcation structures for this class of functions, in a three-dimensional parameter space. We verified that under some sufficient conditions, Tsoularis-Wallace's functions have particular bifurcation structures: the big bang and the double big bang bifurcations of the so-called "box-within-a-box" type. The double big bang bifurcations are related to the existence of flip codimension-2 points. Moreover, it is verified that these bifurcation cascades converge to different big bang bifurcation curves, where for the corresponding parameter values are associated distinct kinds of boxes. This work contributes to clarify the big bang bifurcation analysis for continuous maps and understand their relationship with explosion birth and extinction phenomena.

Experimental design for mixed models with application to population pharmacokinetic studies

experimental design, mixed model, random coefficient regression model, population pharmacokinetics, approximate design

Optimal designs for mixed effects poisson regression models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2010

The effect of antiretroviral treatment of different durations in primary HIV infection.

OBJECTIVES: To compare immunological, virological and clinical outcomes in persons initiating combination antiretroviral therapy (cART of different durations within 6 months of seroconversion (early treated) with those who deferred therapy (deferred group). DESIGN: CD4 cell and HIV-RNA measurements for 'early treated' individuals following treatment cessation were compared with the corresponding ART-free period for the 'deferred' group using piecewise linear mixed models. Individuals identified during primary HIV infection were included if they seroconverted from 1st January 1996 and were at least 15 years of age at seroconversion. Those with at least 2 CD4 less than 350 cells/microl or AIDS within the first 6 months following seroconversion were excluded. RESULTS: Of 348 'early treated' patients, 147 stopped cART following treatment for at least 6 (n = 38), more than 6-12 (n = 40) or more than 12 months (n = 69). CD4 cell loss was steeper for the first 6 months following cART cessation, but subsequent loss rate was similar to the 'deferred' group (n = 675, P = 0.26). Although those treated for more than 12 months appeared to maintain higher CD4 cell counts following cART cessation, those treated for 12 months or less had CD4 cell counts 6 months after cessation comparable to those in the 'deferred' group. There was no difference in HIV-RNA set points between the 'early' and 'deferred' groups (P = 0.57). AIDS rates were similar but death rates, mainly due to non-AIDS causes, were higher in the 'deferred' group (P = 0.05). CONCLUSION: Transient cART, initiated within 6 months of seroconversion, seems to have no effect on viral load set point and limited beneficial effect on CD4 cell levels in individuals treated for more than 12 months. Its long-term effects remain inconclusive and need further investigation.