In vitro cytotoxicity of biosynthesized titanium dioxide nanoparticles in human prostate cancer cell lines

Purpose: To establish a green method for production of titanium dioxide (TiO2) nanoparticles (NPs) using Cinnamomum tamala (C. tamala) leaf extract, and examine the in vitro cytotoxicity of the product in a human prostate cancer (D145) cell line. Methods: TiO2 NPs were synthesized by mixing 20 mL of C. tamala leaf extract with 0.1 M titanium dioxide (Ti(OH)2) (80 mL) in aqueous solution with stirring for 2 h at room temperature. The TiO2 NPs were characterized using x-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), x-ray photoelectron spectroscopy, dynamic light scattering (DLS), transmission electron microscopy (TEM), selected-area electron diffraction, and energy dispersive x-ray spectroscopy. The in vitro cytotoxicity against D145 cells was determined using a 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide assay. Results: TEM and DLS analyses showed that the NPs were irregularly shaped, with an average particle size of 23 nm. The FT-IR spectrum of C. tamala leaf extract showed that the biomolecules were potentially involved in reduction processes. The negative zeta potential of -14 mV indicated that the NPs were stable and discrete while their crystalline nature was confirmed by XRD. Cytotoxicity analysis showed that the TiO2 NPs exhibit a dose-dependent toxic effect on D145 cells. Conclusion: A facile and less expensive approach for the production of TiO2 NPs using C. tamala leaf extract has been developed. The TiO2 NPs showed dose-dependent cytotoxicity towards D145 cells. Keywords: Anticancer activity, Cinnamomum tamala, Green synthesis, Prostate cancer, TiO2 nanoparticle

Efficient sketch-based creation of detailed character models through data-driven mesh deformations

Creation of detailed character models is a very challenging task in animation production. Sketch-based character model creation from a 3D template provides a promising solution. However, how to quickly find correct correspondences between user's drawn sketches and the 3D template model, how to efficiently deform the 3D template model to exactly match user's drawn sketches, and realize real-time interactive modeling is still an open topic. In this paper, we propose a new approach and develop a user interface to effectively tackle this problem. Our proposed approach includes using user's drawn sketches to retrieve a most similar 3D template model from our dataset and marrying human's perception and interactions with computer's highly efficient computing to extract occluding and silhouette contours of the 3D template model and find correct correspondences quickly. We then combine skeleton-based deformation and mesh editing to deform the 3D template model to fit user's drawn sketches and create new and detailed 3D character models. The results presented in this paper demonstrate the effectiveness and advantages of our proposed approach and usefulness of our developed user interface

AN INNOVATIVE GAS TURBINE CYCLE WITH METHANOL FUELLED CHEMICAL-LOOPING COMBUSTION

ABSTRACT In this paper, a novel gas turbine cycle integrating methanol decomposition and the chemical-looping combustion (CLC) is proposed. The system study on two methanol-fuelled power plants, the new gas turbine cycle with CLC combustion, and a chemically intercooled gas turbine cycle, has been investigated with the aid of the exergy analysis (EUD methodology). In the proposed system, methanol fuel is decomposed into syngas mainly containing H 2 and CO by recovering low-temperature thermal energy from an intercooler of the air compressor. After the decomposition of methanol, the resulting product of syngas is divided into two parts: the most part reacting with Fe 2 O 3 , is sent into the CLC subsystem, and the other part is introduced into a supplement combustor to enhance the inlet temperatures of turbine to 1100-1500 o C. As a result, the new methanol-fuelled gas turbine cycle with CLC had a breakthrough in performance, with at least about 10.7 percentage points higher efficiency compared to the chemically intercooled gas turbine cycle with recovery of CO 2 and is environmentally superior due to the recovery of CO 2 . This new system can achieve 60.6% net thermal efficiency with CO 2 separation. The promising results obtained here indicated that this novel gas turbine cycle with methanol-fuelled chemical looping combustion could provide a promising approach of both effective use of alternative fuel and recovering low-grade waste heat, and offer a technical probability for CLC in applying into the advanced gas turbine with high temperatures above 1300 o C. INTRODUCTION Currently, we face a potentially serious problem of rapid climate change due to anthropogenic emissions of greenhouse gases (e.g. CO 2 ). One of the options to control the greenhouse gas emission is the CO 2 capture technologies from flue gases. In a fossil fuel-fired power plant, CO 2 capture can be carried out mainly through three available technologies: "precombustion," "post-combustion" and "oxy-fuel combustion." The progress in this field has been addressed by Mazen [2] Chemical-looping combustion (CLC) with inherent separation of CO 2 is considered a promising technology proposed by Ishida and Jin in 1994 [4][5] . It is the most attractive energy efficient method for CO 2 capture from fuel conversion in combustion process. Compared to conventional combustion, the chemical-looping combustion involves the use of a metal oxide as an oxygen carrier, which transfers oxygen from the combustion air to the fuel, and the direct contact between fuel and combustion air is avoided. In this way, CO 2 and H 2 O are inherently separated from the other components of flue gases leading to no energy needed for CO 2 separation. It is worthy emphasized that this novel CO 2 capture technology simultaneously resolve both energy and environmental problems in a combustion processes, since the conversion of fuel-based chemical energy into chemical energy in th

Model-assisted validation of a strain-based dense sensor network

Recent advances in sensing are empowering the deployment of inexpensive dense sensor networks (DSNs) to conduct structural health monitoring (SHM) on large-scale structural and mechanical systems. There is a need to develop methodologies to facilitate the validation of these DSNs. Such methodologies could yield better designs of DSNs, enabling faster and more accurate monitoring of states for enhancing SHM. This paper investigates a model-assisted approach to validate a DSN of strain gauges under uncertainty. First, an approximate physical representation of the system, termed the physics-driven surrogate, is created based on the sensor network configuration. The representation consists of a state-space model, coupled with an adaptive mechanism based on sliding mode theory, to update the stiffness matrix to best match the measured responses, assuming knowledge of the mass matrix and damping parameters. Second, the physics-driven surrogate model is used to conduct a series of numerical simulations to map damages of interest to relevant features extracted from the synthetic signals that integrate uncertainties propagating through the physical representation. The capacity of the algorithm at detecting and localizing damages is quantified through probability of detection (POD) maps. It follows that such POD maps provide a direct quantification of the DSNs’ capability at conducting its SHM task. The proposed approach is demonstrated using numerical simulations on a cantilevered plate elastically restrained at the root equipped with strain gauges, where the damage of interest is a change in the root’s bending rigidity

Efficient and Realistic Character Animation through Analytical Physics-based Skin Deformation

Physics-based skin deformation methods can greatly improve the realism of character animation, but require non-trivial training, intensive manual intervention, and heavy numerical calculations. Due to these limitations, it is generally time-consuming to implement them, and difficult to achieve a high runtime efficiency. In order to tackle the above limitations caused by numerical calculations of physics-based skin deformation, we propose a simple and efficient analytical approach for physicsbased skin deformations. Specifically, we (1) employ Fourier series to convert 3D mesh models into continuous parametric representations through a conversion algorithm, which largely reduces data size and computing time but still keeps high realism, (2) introduce a partial differential equation (PDE)-based skin deformation model and successfully obtain the first analytical solution to physics-based skin deformations which overcomes the limitations of numerical calculations. Our approach is easy to use, highly efficient, and capable to create physically realistic skin deformations

MicroRNA-483 amelioration of experimental pulmonary hypertension.

Endothelial dysfunction is critically involved in the pathogenesis of pulmonary arterial hypertension (PAH) and that exogenously administered microRNA may be of therapeutic benefit. Lower levels of miR-483 were found in serum from patients with idiopathic pulmonary arterial hypertension (IPAH), particularly those with more severe disease. RNA-seq and bioinformatics analyses showed that miR-483 targets several PAH-related genes, including transforming growth factor-β (TGF-β), TGF-β receptor 2 (TGFBR2), β-catenin, connective tissue growth factor (CTGF), interleukin-1β (IL-1β), and endothelin-1 (ET-1). Overexpression of miR-483 in ECs inhibited inflammatory and fibrogenic responses, revealed by the decreased expression of TGF-β, TGFBR2, β-catenin, CTGF, IL-1β, and ET-1. In contrast, inhibition of miR-483 increased these genes in ECs. Rats with EC-specific miR-483 overexpression exhibited ameliorated pulmonary hypertension (PH) and reduced right ventricular hypertrophy on challenge with monocrotaline (MCT) or Sugen + hypoxia. A reversal effect was observed in rats that received MCT with inhaled lentivirus overexpressing miR-483. These results indicate that PAH is associated with a reduced level of miR-483 and that miR-483 might reduce experimental PH by inhibition of multiple adverse responses

HPtaa database-potential target genes for clinical diagnosis and immunotherapy of human carcinoma

Tumor-associated antigens (TAAs) have been the most actively employed targets in the clinical diagnosis and treatment of human carcinoma, such as PSA in the diagnosis of prostate cancer and NY-ESO-1 in the immunotherapy of melanoma and other cancers. However, identification of TAAs has often been hampered by the complicated and laborsome laboratory procedures. In order to accelerate the process of tumor antigen discovery, and thereby improve diagnosis and treatment of human carcinoma, we have made an effort to establish a publicly available Human Potential Tumor Associated Antigen database (HPtaa) with potential TAAs identified by in silico computing (). Tumor specificity was chosen as the core of tumor antigen evaluation, together with other relevant clues. Various platforms of gene expression, including microarray, expressed sequence tag and SAGE data, were processed and integrated by several penalty algorithms. A total of 3518 potential TAAs have been included in the database, which is freely available to academic users. As far as we know, this database is the first one addressing human potential TAAs, and the first one integrating various kinds of expression platforms for one purpose

Character Modelling with Sketches and ODE-Based Shape Creation

Character models have enormous applications in industry. Efficient creation of detailed character models is an important topic. This paper proposes a new and easy-to-use technique to quickly create detailed character models from sketches. The proposed technique consists of two main components: primitive deformer and shape generators. With this technique, 2D silhouette contours of a character model are drawn or extracted from an image or sketch. Then, proper geometric primitives are selected and aligned with the corresponding 2D silhouette contours. After that, a primitive deformer is used to create a base mesh and three shape generators are used to add 3D details to the base mesh. The primitive deformer and three shape generators are developed from ODE-driven deformations. The primitive deformer deforms the aligned geometric primitives to exactly match the 2D silhouette contours in one view plane and obtains a base mesh of a character model consisting of deformed primitives. The shape generators are used to add 3D details to the base mesh by creating local 3D models. The experimental results demonstrate that the new technique can quickly create detailed 3D character models from sketches with few manual operations. The new technique is physics-based and easy to learn and use