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.

Algebraic Bethe ansatz for integrable extended Hubbard models arising from supersymmetric group solutions

Integrable extended Hubbard models arising from symmetric group solutions are examined in the framework of the graded quantum inverse scattering method. The Bethe ansatz equations for all these models are derived by using the algebraic Bethe ansatz method.

Integrable extended hubbard models with boundary Kondo impurities

Three kinds of integrable Kondo impurity additions to one-dimensional q-deformed extended Hubbard models are studied by means of the boundary Z(2)-graded quantum inverse scattering method. The boundary K matrices depending on the local magnetic moments of the impurities are presented as nontrivial realisations of the reflection equation algebras in an impurity Hilbert space. The models are solved by using the algebraic Bethe ansatz method, and the Bethe ansatz equations are obtained.

Robust parameter settings of evolutionary algorithms for the optimisation of agricultural systems models

Numerical optimisation methods are being more commonly applied to agricultural systems models, to identify the most profitable management strategies. The available optimisation algorithms are reviewed and compared, with literature and our studies identifying evolutionary algorithms (including genetic algorithms) as superior in this regard to simulated annealing, tabu search, hill-climbing, and direct-search methods. Results of a complex beef property optimisation, using a real-value genetic algorithm, are presented. The relative contributions of the range of operational options and parameters of this method are discussed, and general recommendations listed to assist practitioners applying evolutionary algorithms to the solution of agricultural systems. (C) 2001 Elsevier Science Ltd. All rights reserved.