Three-dimensional cohesive fracture modeling of non-planar crack growth using adaptive FE technique

AbstractIn this paper, the three-dimensional adaptive finite element modeling is presented for cohesive fracture analysis of non-planer crack growth. The technique is performed based on the Zienkiewicz–Zhu error estimator by employing the modified superconvergent patch recovery procedure for the stress recovery. The Espinosa–Zavattieri bilinear constitutive equation is used to describe the cohesive tractions and displacement jumps. The 3D cohesive fracture element is employed to simulate the crack growth in a non-planar curved pattern. The crack growth criterion is proposed in terms of the principal stress and its direction. Finally, several numerical examples are analyzed to demonstrate the validity and capability of proposed computational algorithm. The predicted crack growth simulation and corresponding load-displacement curves are compared with the experimental and other numerical results reported in literature

Reduced DNA damage in tumor spheroids compared to monolayer cultures exposed to ionizing radiation

Background: Several cell lines when cultured under proper condition can form three dimensional structures called multicellular tumor spheroids. Tumor spheroids are valuable in vitro models for studying physical and biological behavior of real tumors. A number of previous studies using a variety of techniques have shown no relationship between radiosensitivity and DNA strand breaks in monolayer and spheroid model of cell culture. Materials and Methods: In the present study, the radiosensitivity of cells grown as monolayer and spheroid were measured with colony assay and the role of DNA strand breaks in this sensitivity was examined using single cell gel electrophoresis assay also known as Comet assay. Results: In the present experiment, spheroids showed more radioresistance than monolayers asjudged by the number of colonies which they produced after radiation. Under the same experimental conditions, less level of DNA damage was detected in spheroids using "comet assay" technique. Conclusion: It was concluded that the loss of radioresistance which was observed in monolayer cultures might have been attributed to the higher level of DNA damage occurred in the cells

Metformin attenuates streptozotocin-induced diabetic nephropathy in rats through activation of AMPK signaling pathway

Background: Nephropathy is the main problem of diabetes and can be classified into several phases according to the presence of albuminuria. Adenosine monophosphate-activated protein kinase (AMPK) operates as a sensor of energy charge. Objectives: The aim of our study was to evaluate the reno-protective properties of AMPK signaling pathway against streptozotocin (STZ)-induced nephropathy in the rat. Materials and Methods: Forty male Wistar rats were randomly distributed into four groups. Group 1 was normal rats (N group); group 2 was diabetic rats (D group); group 3 received diabetic rats + metformin (DM group), and group 4 received giabetic rats + metformin + dorsomorphin (DMD group). Serum albumin, uric acid, total protein and creatinine for estimation of renal injury were measured. Finally, the histological study was evaluated. Results: Reduction of body weight, albumin and total protein in the diabetic rat was reversed by metformin administration. Our results showed that serum uric acid and creatinine were significantly increased in diabetic rats and decreased after treatment with metformin in diabetic rats. AMPK improved the histopathology and morphological changes in STZ-induced diabetic rats. Administration of dorsomorphin (AMPK inhibitor) with metformin can reverse the beneficial effects of AMPK. Conclusions: AMPK signaling pathway ameliorates diabetic nephropathy by modifications of serum albumin, uric acid, total protein, creatinine and attenuation of kidney damage

Lithium attenuated the depressant and anxiogenic effect of juvenile social stress through mitigating the negative impact of interlukin-1β and nitric oxide on hypothala...

Abstract—The neuroimmune-endocrine dysfunction has been accepted as one of fundamental mechanisms contributing to the pathophysiology of psychiatric disorders including depression and anxiety. In this study, we aimed to evaluate the involvement of hypothalamic–pituitary–adre nal (HPA) axis, interleukin-1b, and nitrergic system in mediating the negative behavioral impacts of juvenile social isolation stress (SIS) in male mice. We also investigated the possible protective effects of lithium on behavioral and neurochemical changes in socially isolated animals. Results showed that experiencing 4-weeks of juvenile SIS provoked depressive and anxiety-like behaviors that were associated with hyper responsiveness of HPA axis, upregulation of interleukin-1b, and nitric oxide (NO) overproduction in the pre-frontal cortex and hippocampus. Administration of lithium (10 mg/kg) significantly attenuated the depressant and anxiogenic effects of SIS in behavioral tests. Lithium also restored the negative effects of SIS on cortical and hippocampal interleukin-1b and NO as well as HPA axis deregulation. Unlike the neutralizing effects of L-arginine (NO precursor), administration of L-NAME (3 mg/kg) and aminoguanidine (20 mg/kg) potentiated the positive effects of lithium on the behavioral and neurochemical profile of isolated mice. In conclusion, our results revealed that juvenile SIS-induced behavioral deficits are associated with abnormalities in HPA-immune function. Also, we suggest that alleviating effects of lithium on behavioral profile of isolated mice may be partly mediated by mitigating the negative impact of NO on HPA-immune function. � 2015 IBRO. Published by Elsevier Ltd. All rights reserve

A hierarchical hyperelastic-based approach for multi-scale analysis of defective nano-materials

In this paper, a continuum-atomistic multi-scale method is presented in modeling the nonlinear behavior of nano-materials under large deformation. In order to identify an appropriate strain energy function for crystalline nano-structures with different percentages of spherical voids, the hyperelastic method is employed for specimen whose behavior is determined based on the molecular dynamics analyses. In the atomistic level, the EAM manybody potential is employed to model the interactions between the atoms of Al RVEs. The atomistic strain energy density curves and surfaces are generated by applying the uniaxial, biaxial and simple shear deformations to the boundaries of RVEs. The material parameters of hyperelastic model are computed by fitting the proposed functions to atomistic reference data obtained from the molecular statics simulations. Explicit relations for the stress and elasticity tensors are provided for the proposed hyperelastic models. The robustness and accuracy of the proposed technique is presented in modeling of mechanical behavior of Al material. Finally, several numerical examples are performed to illustrate the applicability of the proposed multi-scale technique

Mechanical behavior of multilayer graphene reinforced epoxy nano-composites via a hierarchical multi-scale technique

In this paper, a multi-scale technique is presented to study the mechanical behavior of nano-composites by linking the atomistic information from lower scale to the continuum model in upper scale. Molecular dynamics simulations are employed to compute the material properties of graphene/epoxy nano-composites using the COMPASS interatomic force field. In order to obtain the atomistic stress surfaces used to evaluate the mechanical properties of material in upper scale, the biaxial loading is applied to different representative volume elements. On the continuum level, the hyperelastic strain energy functions are utilized to calculate the material parameters using the hyperelastic functions from atomistic data. The stress and elasticity tensors are obtained by computing the first and second order derivatives of hyperelastic functions with reference to the components of the right Cauchy–Green deformation tensor. The stress–strain surfaces of hyperelastic functions in lower scale are used to calculate the properties of nano-composite material in upper scale. The efficiency and applicability of the proposed technique is presented through various numerical examples. It is shown that the proposed multi-scale technique is able to solve large problems within acceptable computational time, which is not possible using conventional molecular dynamics approaches