TOXICITY ASSESSMENT OF CARBON NANOTUBES ON ERYTHROCYTE MORPHOLOGY AND LYMPHOCYTES IN VITRO

ABSTRACTObjectives: Carbon nanomaterials have been used in many biomedical applications due to its unique physical properties. Functionalization of carbonnanotubes (CNT) could improve the physical properties, but pharmacokinetics and toxic effects of pristine and functionalized CNTs, are not welldefined. In this study, the toxicity of the pristine and hydroxyl group functionalized Multi‑Walled CNT (MWCNT) compared.Methods: MWCNTs was interacted with human blood. The induced morphological changes in the erythrocytes and cytotoxicity were observed atdifferent concentrations. A thin blood smear was prepared, and the erythrocyte images were obtained using a digital microscope. MTT assay used toassess the cytotoxicity.Results: The result indicate that the pristine MWCNT caused more toxic effects than –OH functionalized MWCNT, which was assessed in terms ofchanges in the morphology of the erythrocytes and cytotoxicity caused to the lymphocyte cells.Conclusion: The functionalization of MWCNT could reduce the hemotoxicity and improves the biocompatibility.Keywords: Carbon nanotubes, Cytotoxicity, Echinocytes, Erythrocyte, Multi‑walled carbon nanotubes, Lymphocyte

Preparation and evaluation of ciprofloxacin loaded chitosan-gelatin composite films for wound healing activity

Natural polymers are used as lead compounds for design of drugs in treatment of different ailments. Chitosan and gelatin have proven wound healing properties individually. As both have wound healing property, the combination of these two polymers and incorporation of drugs into the composite films may show improvement in wound healing activity. Thus, the composite films and drug loaded films were evaluated for various in vitro evaluation tests to ascertain the applicability of prepared combination for wound healing activity. The composite films were prepared with increase in gelatin concentration and the drug loaded films were prepared with increased concentrations of drug in optimized composite film. These films were evaluated for thickness, folding endurance, water absorption capacity, antibacterial activity, tensile strength, drug load, content uniformity, in vitro drug release by diffusion studies and in vivo wound healing studies by excision wound model using albino rats. The drug loaded films shown significant difference in folding endurance, water absorption capacity, antibacterial activity when compared to optimized blank composite film. There was no significant difference in thickness and tensile strength of drug loaded films when compared to blank composite films. Percentage of wound contraction was more for wounds treated with ciprofloxacin loaded composite film than blank composite film. With the above results, it was concluded that ciprofloxacin loaded chitosan-gelatin composite films had shown more wound healing property than chitosan-gelatin blank composite film and blank chitosan film without interfering in strength of film.Keywords: Ciprofloxacin; Chitosan; Gelatin; Drug loaded films; Wound healing; Tensile strength

Living biointerfaces based on non-pathogenic bacteria to direct cell differentiation

Genetically modified Lactococcus lactis, non-pathogenic bacteria expressing the FNIII7-10 fibronectin fragment as a protein membrane have been used to create a living biointerface between synthetic materials and mammalian cells. This FNIII7-10 fragment comprises the RGD and PHSRN sequences of fibronectin to bind α5β1 integrins and triggers signalling for cell adhesion, spreading and differentiation. We used L. lactis strain to colonize material surfaces and produce stable biofilms presenting the FNIII7-10 fragment readily available to cells. Biofilm density is easily tunable and remains stable for several days. Murine C2C12 myoblasts seeded over mature biofilms undergo bipolar alignment and form differentiated myotubes, a process triggered by the FNIII7-10 fragment. This biointerface based on living bacteria can be further modified to express any desired biochemical signal, establishing a new paradigm in biomaterial surface functionalisation for biomedical applications

Classification of fracture and non-fracture groups by analysis of coherent X-ray scatter

Osteoporotic fractures present a significant social and economic burden, which is set to rise commensurately with the aging population. Greater understanding of the physicochemical differences between osteoporotic and normal conditions will facilitate the development of diagnostic technologies with increased performance and treatments with increased efficacy. Using coherent X-ray scattering we have evaluated a population of 108 ex vivo human bone samples comprised of non-fracture and fracture groups. Principal component fed linear discriminant analysis was used to develop a classification model to discern each condition resulting in a sensitivity and specificity of 93% and 91%, respectively. Evaluating the coherent X-ray scatter differences from each condition supports the hypothesis that a causal physicochemical change has occurred in the fracture group. This work is a critical step along the path towards developing an in vivo diagnostic tool for fracture risk prediction

Hydroxyapatite Mineralization on the Calcium Chloride Blended Polyurethane Nanofiber via Biomimetic Method

Polyurethane nanofibers containing calcium chloride (CaCl2) were prepared via an electrospinning technique for the biomedical applications. Polyurethane nanofibers with different concentration of CaCl2 were electrospun, and their bioactivity evaluation was conducted by incubating in biomimetic simulated body fluid (SBF) solution. The morphology, structure and thermal properties of the polyurethane/CaCl2 composite nanofibers were characterized by means of scanning electron microscopy (SEM), field-emission scanning electron microscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, Fourier transform infrared spectroscopy and thermogravimetry. SEM images revealed that the CaCl2 salt incorporated homogeneously to form well-oriented nanofibers with smooth surface and uniform diameters along their lengths. The SBF incubation test confirmed the formation of apatite-like materials, exhibiting enhanced bioactive behavior of the polyurethane/CaCl2 composite nanofibers. This study demonstrated that the electrospun polyurethane containing CaCl2 composite nanofibers enhanced the in vitro bioactivity and supports the growth of apatite-like materials

A New Reinforcement Learning based Automatic Generation Controller for Hydro-Thermal Power Systems

Recently, we have proposed [1] a Reinforcement Learning (RL) based approach for designing an Automatic Generation Controller for a two area power system, where we have demonstrated the efficacy of the approach on an identical, simple, two area model. The aim of this paper is to demonstrate an alternative RL-AGC design which is simpler. Its effectiveness is demonstrated by considering a hydro-thermal system whose dynamics are more complicated than the system considered in [1]

Reinforcement learning controllers for automatic generation control in power systems having re-heat units with GRC and dead-band

A new automatic generation controller (AGC) design approach, adopting reinforcement learning (RL) techniques, was recently pro- posed [1]. In this paper we demonstrate the design and performance of controllers based on this RL approach for automatic generation control of systems consisting of units having complex dynamics—the reheat type of thermal units. For such systems, we also assess the capabilities of RL approach in handling realistic system features such as network changes, parameter variations, generation rate constraint (GRC), and governor deadband

A neural network based automatic generation control design through reinforcement learning

This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated

Qualitative toxicity assessment of silver nanoparticles on the fresh water bacterial isolates and consortium at low level of exposure concentration

Silver nanoparticles (AgNPs) pose a high risk of exposure to the natural environment owing to their extensive usage in various consumer products. In the present study we attempted to understand the harmful effect of AgNPs at environmentally relevant low concentration levels (<= 1 ppm) towards two different freshwater bacterial isolates and their consortium. The standard plate count assay suggested that the AgNPs were toxic towards the fresh water bacterial isolates as well as the consortium, though toxicity was significantly reduced for the cells in the consortium. The oxidative stress assessment and membrane permeability studies corroborated with the toxicity data. The detailed electron microscopic studies suggested the cell degrading potential of the AgNPs, and the FT-IR studies confirmed the involvement of the surface groups in the toxic effects. No significant ion leaching from the AgNPs was observed at the applied concentration levels signifying the dominant role of the particle size, and size distribution in bacterial toxicity. The reduced toxicity for the cells in the consortium than the individual isolates has major significance in further studies on the ecotoxicity of the AgNPs. (C) 2014 Elsevier Inc. All rights reserved