Cocaine- and amphetamine-regulated transcript promoter regulated by nicotine in nerve growth factor-treated PC12 cells

Nicotine and cocaine- and amphetamine-regulated transcripts (CART) have several overlapping functions, such as the regulation of reward, feeding behavior, stress response, and anxiety. Previous studies showed that nicotine regulates CART expression in various brain regions. However, the molecular mechanisms underlying this regulation are not known. This study investigated the regulatory effect of nicotine on promoter activity of the CART gene in PC12 cells, which were differentiated into a neuronal phenotype by nerve growth factor (NGF) treatment. Two vectors containing reporter genes (Gaussia luciferase or mCherry) and the 1,140-bp upstream of the transcriptional start site of the mouse CART gene are used to analyze the CART promoter activity. Transient transfection of PC12 cells with either vector displayed strong promoter activity in both undifferentiated and differentiated PC12 cells. CART promoter activity in the PC12 cell line is increased by forskolin or NGF treatment. In differentiated PC12 cells, exposure to 50 nM nicotine for 6 h increased CART promoter activity. However, treatment with higher nicotine doses for 6 h and treatment with all nicotine doses for 24 h showed no effect. A nicotine concentration of 50 nM is comparable to brain nicotine levels experienced by chronic smokers over long periods of time. Taken together, these data indicate that nicotine may exert some of its actions through the regulation of CART transcription in the brain

Evidence of a magnetic transition in atomically thin Cr2TiC2Tx MXene

Two-dimensional (2D) transition metal carbides and nitrides known as MXenes have shown attractive functionalities such as high electronic conductivity, a wide range of optical properties, versatile transition metal and surface chemistry, and solution processability. Although extensively studied computationally, the magnetic properties of this large family of 2D materials await experimental exploration. 2D magnetic materials have recently attracted significant interest as model systems to understand low-dimensional magnetism and for potential spintronic applications. Here, we report on synthesis of Cr2TiC2Tx MXene and a detailed study of its magnetic as well as electronic properties. Using a combination of magnetometry, synchrotron X-ray linear dichroism, and field- and angular-dependent magnetoresistance measurements, we find clear evidence of a magnetic transition in Cr2TiC2Tx at approximately 30 K, which is not present in its bulk layered carbide counterpart (Cr2TiAlC2 MAX phase). This work presents the first experimental evidence of a magnetic transition in a MXene material and provides an exciting opportunity to explore magnetism in this large family of 2D materials

From Architectured Materials to Large-Scale Additive Manufacturing

The classical material-by-design approach has been extensively perfected by materials scientists, while engineers have been optimising structures geometrically for centuries. The purpose of architectured materials is to build bridges across themicroscale ofmaterials and themacroscale of engineering structures, to put some geometry in the microstructure. This is a paradigm shift. Materials cannot be considered monolithic anymore. Any set of materials functions, even antagonistic ones, can be envisaged in the future. In this paper, we intend to demonstrate the pertinence of computation for developing architectured materials, and the not-so-incidental outcome which led us to developing large-scale additive manufacturing for architectural applications

Computational Homogenization of Architectured Materials

Architectured materials involve geometrically engineered distributions of microstructural phases at a scale comparable to the scale of the component, thus calling for new models in order to determine the effective properties of materials. The present chapter aims at providing such models, in the case of mechanical properties. As a matter of fact, one engineering challenge is to predict the effective properties of such materials; computational homogenization using finite element analysis is a powerful tool to do so. Homogenized behavior of architectured materials can thus be used in large structural computations, hence enabling the dissemination of architectured materials in the industry. Furthermore, computational homogenization is the basis for computational topology optimization which will give rise to the next generation of architectured materials. This chapter covers the computational homogenization of periodic architectured materials in elasticity and plasticity, as well as the homogenization and representativity of random architectured materials

Optimization of elasticity of unidirectionnal non-overlapping fiber reinforced materials

The aim of this work is to efficiently select samples of non-overlapping parallel fiber reinforced composites with regard to their elasticity and their fiber distribution in the composite cross-section. The samples were built with the help of the simulated annealing technique according to chosen Radial Distribution Functions. For each sample the fields of local stresses were simulated by finite element method, then homogenized by volume averaging in order to investigate their elastic properties. The effect of RDF shape on elastic properties was quantified. The more the fiber distributions deviate from Poisson’s Law the higher the effective elastic moduli are. A method to select samples of real fiber reinforced composites according to their elasticity is proposed