A combined scanning electron micrograph and electrochemical study of the effect of chemical interaction on the cyclability of lithium electrodes in an ionic liquid electrolyte

The effect of storage time on the cyclability of lithium electrodes in an ionic liquid electrolyte, namely 0.5 m LiBF4 in N-methyl-N-propyl pyrrolidinium bis(fluorosulfonyl)imide, [C3mpyr+][FSI–], was investigated. A chemical interaction was observed which is time dependent and results in a morphology change of the Li surface due to build up of passivation products over a 12-day period. The formation of this layer significantly impacts on the Li electrode resistance before cycling and the charging/discharging process for symmetrical Li|0.5 m LiBF4 in [C3mpyr+][FSI–]|Li coin cells. Indeed it was found that introducing a rest period between cycling, and thereby allowing the chemical interaction between the Li electrode and electrolyte to take place, also impacted on the charging/discharging process. For all Li surface treatments the electrode resistance decreased after cycling and was due to significant structural rearrangement of the surface layer. These results suggest that careful electrode pretreatment in a real battery system will be required before operation.

Histone deacetylase inhibitors target diabetes via chromatin remodeling or as chemical chaperones?

Globally, obesity and diabetes (particularly type 2 diabetes) represents a major challenge to world health. Despite decades of intense research efforts, the genetic basis involved in diabetes pathogenesis & conditions associated with obesity are still poorly understood. Recent advances have led to exciting new developments implicating epigenetics as an important mechanism underpinning diabetes and obesity related disease. One epigenetic mechanism known as the "histone code" describes the idea that specific patterns of post-translational modifications to histones act like a molecular "code" recognised and used by non-histone proteins to regulate specific chromatin functions. One modification which has received significant attention is that of histone acetylation. The enzymes which regulate this modification are described as lysine acetyltransferases or KATs and histone deacetylases or HDACs. Due to their conserved catalytic domain HDACs have been actively targeted as a therapeutic target. Some of the known inhibitors of HDACs (HDACi) have also been shown to act as "chemical chaperones" to alleviate diabetic symptoms. In this review, we discuss the available evidence concerning the roles of HDACs in regulating chaperone function and how this may have implications in the management of diabetes. © 2009 Bentham Science Publishers Ltd.

The relationship between angiogenesis and the immune response in carcinogenesis and the progression of malignant disease

Recent studies have demonstrated that angiogenesis and suppressed cell- mediated immunity (CMI) play a central role in the pathogenesis of malignant disease facilitating tumour growth, invasion and metastasis. In the majority of tumours, the malignant process is preceded by a pathological condition or exposure to an irritant which itself is associated with the induction of angiogenesis and/or suppressed CMI. These include: cigarette smoking, chronic bronchitis and lung cancer; chronic oesophagitis and oesophageal cancer; chronic viral infections such as human papilloma virus and ano-genital cancers, chronic hepatitis B and C and hepatocellular carcinoma, and Epstein- Barr virus (EBV) and lymphomas; chronic inflammatory conditions such as Crohn's disease and ulcerative colitis and colorectal cancer; asbestos exposure and mesothelioma and excessive sunlight exposure/sunburn and malignant melanoma. Chronic exposure to growth factors (insulin-like growth factor-I in acromegaly), mutations in tumour suppressor genes (TP53 in Li Fraumeni syndrome) and long-term exposure to immunosuppressive agents (cyclosporin A) may also give rise to similar environments and are associated with the development of a range of solid tumours. The increased blood supply would facilitate the development and proliferation of an abnormal clone or clones of cells arising as the result of: (a) an inherited genetic abnormality; and/or (b) acquired somatic mutations, the latter due to local production and/or enhanced delivery of carcinogens and mutagenic growth factors. With progressive detrimental mutations and growth-induced tumour hypoxia, the transformed cell, to a lesser or greater extent, may amplify the angiogenic process and CMI suppression, thereby facilitating further tumour growth and metastasis. There is accumulating evidence that long-term treatment with cyclo-oxygenase inhibitors (aspirin and indomethacin), cytokines such as interferon-α, anti-oestrogens (tamoxifen and raloxifene) and captopril significantly reduces the incidence of solid tumours such as breast and colorectal cancer. These agents are anti-angiogenic and, in the case of aspirin, indomethacin and interferon-α have proven immunomodulatory effects. Collectively these observations indicate that angiogenesis and suppressed CMI play a central role in the development and progression of malignant disease. (C) 2000 Elsevier Science Ltd.

Investigations of the physical and chemical properties of ambient fine particles in urban schools

This thesis reports a comprehensive study on the physical and chemical properties of airborne particles in Brisbane, especially around schools. The sources and potential toxicity of the particles were identified, enabling an assessment of the contributing factors to children's exposure at school. The results from this thesis give a quantitative estimate of the range of airborne particles that children are exposed to at urban schools with different traffic conditions.

High-temperature growth of graphene films on copper foils by ethanol chemical vapour deposition

Chemical vapor deposition (CVD) is widely utilized to synthesize graphene with controlled properties for many applications, especially when continuous films over large areas are required. Although hydrocarbons such as methane are quite efficient precursors for CVD at high temperature (∼1000 °C), finding less explosive and safer carbon sources is considered beneficial for the transition to large-scale production. In this work, we investigated the CVD growth of graphene using ethanol, which is a harmless and readily processable carbon feedstock that is expected to provide favorable kinetics. We tested a wide range of synthesis conditions (i.e., temperature, time, gas ratios), and on the basis of systematic analysis by Raman spectroscopy, we identified the optimal parameters for producing highly crystalline graphene with different numbers of layers. Our results demonstrate the importance of high temperature (1070 °C) for ethanol CVD and emphasize the significant effects that hydrogen and water vapor, coming from the thermal decomposition of ethanol, have on the crystal quality of the synthesized graphene.

A Near-Infrared Reflectance Spectroscopy Method for Direct Analysis of Several Chemical Components and Properties of Fruit, for Example, Chinese Hawthorn

Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of Chinese hawthorn (Crataegus pinnatifida Bge. var. major) fruit from three geographical regions as well as for the estimation of the total sugar, total acid, total phenolic content, and total antioxidant activity. Principal component analysis (PCA) was used for the discrimination of the fruit on the basis of their geographical origin. Three pattern recognition methods, linear discriminant analysis, partial least-squares-discriminant analysis, and back-propagation artificial neural networks, were applied to classify and compare these samples. Furthermore, three multivariate calibration models based on the first derivative NIR spectroscopy, partial least-squares regression, back-propagation artificial neural networks, and least-squares-support vector machines, were constructed for quantitative analysis of the four analytes, total sugar, total acid, total phenolic content, and total antioxidant activity, and validated by prediction data sets.

Effect of chemical conjugation of L-leucine to chitosan on the dispersibility and drug release of a dry powder inhaler nanoparticle formulation

Purpose: This study investigated the effect of chemical conjugation of the amino acid L-leucine to the polysaccharide chitosan on the dispersibility and drug release pattern of a polymeric nanoparticle (NP)-based controlled release dry powder inhaler (DPI) formulation. Methods: A chemical conjugate of L-leucine with chitosan was synthesized and characterized by Infrared (IR) Spectroscopy, Nuclear Magnetic Resonance (NMR) Spectroscopy, Elemental Analysis and X-ray Photoelectron Spectroscopy (XPS). Nanoparticles of both chitosan and its conjugate were prepared by a water-in-oil emulsification – glutaraldehyde cross-linking method using the antihypertensive agent, diltiazem (Dz) hydrochloride as the model drug. The surface morphology and particle size distribution of the nanoparticles were determined by Scanning Electron Microscopy (SEM) and Dynamic Light Scattering (DLS). The dispersibility of the nanoparticle formulation was analysed by a Twin Stage Impinger (TSI) with a Rotahaler as the DPI device. Deposition of the particles in the different stages was determined by gravimetry and the amount of drug released was analysed by UV spectrophotometry. The release profile of the drug was studied in phosphate buffered saline at 37 ⁰C and analyzed by UV spectrophotometry. Results: The TSI study revealed that the fine particle fractions (FPF), as determined gravimetrically, for empty and drug-loaded conjugate nanoparticles were significantly higher than for the corresponding chitosan nanoparticles (24±1.2% and 21±0.7% vs 19±1.2% and 15±1.5% respectively; n=3, p<0.05). The FPF of drug-loaded chitosan and conjugate nanoparticles, in terms of the amount of drug determined spectrophotometrically, had similar values (21±0.7% vs 16±1.6%). After an initial burst, both chitosan and conjugate nanoparticles showed controlled release that lasted about 8 to 10 days, but conjugate nanoparticles showed twice as much total drug release compared to chitosan nanoparticles (~50% vs ~25%). Conjugate nanoparticles also showed significantly higher dug loading and entrapment efficiency than chitosan nanoparticles (conjugate: 20±1% & 46±1%, chitosan: 16±1% & 38±1%, n=3, p<0.05). Conclusion: Although L-leucine conjugation to chitosan increased dispersibility of formulated nanoparticles, the FPF values are still far from optimum. The particles showed a high level of initial burst release (chitosan, 16% and conjugate, 31%) that also will need further optimization.

Design, synthesis and spectroscopic characterisation of a focused library based on the polyandrocarpamine natural product scaffold

A focused library based on the marine natural products polyandrocarpamines A (1) and B (2) has been designed and synthesised using parallel solution-phase chemistry. In silico physicochemical property calculations were performed on synthetic candidates in order to optimise the library for drug discovery and chemical biology. A library of ten 2-aminoimidazolone products (3–12) was prepared by coupling glycocyamidine and a variety of aldehydes using a one-step stereoselective aldol condensation reaction under microwave conditions. All analogues were characterised by NMR, UV, IR and MS. The library was evaluated for cytotoxicity towards the prostate cancer cell lines, LNCaP, PC-3 and 22Rv1.

Inflammation in lung carcinogenesis

It was Dvorak in 1986 that postulated 'tumours are wounds that do not heal' as they share common cellular and molecular mechanisms, which are active in both wounds and in cancer tissue. Inflammation is a crucial part of the innate immune system that protects against pathogens and initiates adaptive immunity. Acute inflammation is usually a rapid and self-limiting process, however it does not always resolve. This leads to the establishment of a chronic inflammatory state and provides the perfect environment for carcinogenesis. Inflammation and cancer have long had an association, going back as far as Virchow in 1863, when leucocytes were noted in neoplastic tissue. It has been estimated that approximately 25% of all malignancies are initiated or exacerbated by inflammation caused by infectious agents. Furthermore, inflammation is linked to all of the six hallmarks of cancer (evasion of apoptosis, insensitivity to anti-growth signals, unlimited replicative potential, angiogenesis, increase in survival factors and invasion and metastasis). It is thought that inflammation may play a critical role in lung carcinogenesis given that individuals with inflammatory lung conditions have an increased risk of lung cancer development. Cigarette smoking can also induce inflammation in the lung and smokers are at a higher risk of developing lung cancer than non-smokers. However, exposure to a number of environmental agents such as radon, have also been demonstrated as a causative factor in this disease. This chapter will focus on inflammation as a contributory factor in non small cell lung cancer (NSCLC), concentrating primarily on the pathological involvement of the pro-inflammatory cytokines, TNF-α, IL-1β, and the CXC (ELR+) chemokine family. Targeting of inflammatory mediators will also be discussed as a therapeutic strategy in this disease. © 2013 by Nova Science Publishers, Inc. All rights reserved.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Strain engineering of selective chemical adsorption on monolayer MoS2

Nanomaterials are prone to influence by chemical adsorption because of their large surface to volume ratios. This enables sensitive detection of adsorbed chemical species which, in turn, can tune the property of the host material. Recent studies discovered that single and multi-layer molybdenum disulfide (MoS2) films are ultra-sensitive to several important environmental molecules. Here we report new findings from ab inito calculations that reveal substantially enhanced adsorption of NO and NH3 on strained monolayer MoS2 with significant impact on the properties of the adsorbates and the MoS2 layer. The magnetic moment of adsorbed NO can be tuned between 0 and 1 μB; strain also induces an electronic phase transition between half-metal and metal. Adsorption of NH3 weakens the MoS2 layer considerably, which explains the large discrepancy between the experimentally measured strength and breaking strain of MoS2 films and previous theoretical predictions. On the other hand, adsorption of NO2, CO, and CO2 is insensitive to the strain condition in the MoS2 layer. This contrasting behavior allows sensitive strain engineering of selective chemical adsorption on MoS2 with effective tuning of mechanical, electronic, and magnetic properties. These results suggest new design strategies for constructing MoS2-based ultrahigh-sensitivity nanoscale sensors and electromechanical devices.

Toxic state–corporate crimes, Neo-liberalism and green criminology : the hazards and legacies of the oil, chemical and mineral industries

This paper uses examples from the history and practices of multi-national and large companies in the oil, chemical and asbestos industries to examine their legal and illegal despoiling and destruction of the environment and impact on human and non-human life. The discussion draws on the literature on green criminology and state-corporate crime and considers measures and arrangements that might mitigate or prevent such damaging acts. This paper is part of ongoing work on green criminology and crimes of the economy. It places these actions and crimes in the context of a global neo-liberal economic system and considers and critiques the distorting impact of the GDP model of ‘economic health’ and its consequences for the environment.

Estimation of biodiesel properties from chemical composition – An artificial neural network (ANN) approach

Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Gelatine methacrylamide-based hydrogels : an alternative three-dimensional cancer cell culture system

Modern cancer research requires physiological, three-dimensional (3-D) cell culture platforms, wherein the physical and chemical characteristics of the extracellular matrix (ECM) can be modified. In this study, gelatine methacrylamide (GelMA)-based hydrogels were characterized and established as in vitro and in vivo spheroid-based models for ovarian cancer, reflecting the advanced disease stage of patients, with accumulation of multicellular spheroids in the tumour fluid (ascites). Polymer concentration (2.5-7% w/v) strongly influenced hydrogel stiffness (0.5±0.2kPa to 9.0±1.8kPa) but had little effect on solute diffusion. The diffusion coefficient of 70kDa fluorescein isothiocyanate (FITC)-labelled dextran in 7% GelMA-based hydrogels was only 2.3 times slower compared to water. Hydrogels of medium concentration (5% w/v GelMA) and stiffness (3.4kPa) allowed spheroid formation and high proliferation and metabolic rates. The inhibition of matrix metalloproteinases and consequently ECM degradability reduced spheroid formation and proliferation rates. The incorporation of the ECM components laminin-411 and hyaluronic acid further stimulated spheroid growth within GelMA-based hydrogels. The feasibility of pre-cultured GelMA-based hydrogels as spheroid carriers within an ovarian cancer animal model was proven and led to tumour development and metastasis. These tumours were sensitive to treatment with the anti-cancer drug paclitaxel, but not the integrin antagonist ATN-161. While paclitaxel and its combination with ATN-161 resulted in a treatment response of 33-37.8%, ATN-161 alone had no effect on tumour growth and peritoneal spread. The semi-synthetic biomaterial GelMA combines relevant natural cues with tunable properties, providing an alternative, bioengineered 3-D cancer cell culture in in vitro and in vivo model systems.

The fragmentation pathways of protonated Amiton in the gas phase : towards the structural characterisation of organophosphorus chemical warfare agents by electrospray ionisation tandem mass spectrometry

Amiton (O,O-diethyl-S-[2-(diethylamino)ethyl]phosphorothiolate), otherwise known as VG, is listed in schedule 2 of the Chemical Weapons Convention (CWC) and has a structure closely related to VX (O-ethyl-S-(2-diisopropylamino)ethylmethylphosphonothiolate). Fragmentation of protonated VG in the gas phase was performed using electrospray ionisation ion trap mass spectrometry (ESI-ITMS) and revealed several characteristic product ions. Quantum chemical calculations provide the most probable structures for these ions as well as the likely unimolecular mechanisms by which they are formed. The decomposition pathways predicted by computation are consistent with deuterium-labeling studies. The combination of experimental and theoretical data suggests that the fragmentation pathways of VG and analogous organophosphorus nerve agents, such as VX and Russian VX, are predictable and thus ESI tandem mass spectrometry is a powerful tool for the verification of unknown compounds listed in the CWC. Copyright (c) 2006 Commonwealth of Australia. Published by John Wiley & Sons, Ltd.