944 resultados para Chemical Defense-mechanism


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One of the hallmarks of progressive renal disease is the development of tubulointerstitial fibrosis. This is frequently preceded by macrophage infiltration, raising the possibility that macrophages relay fibrogenic signals to resident tubulointerstitial cells. The aim of this study was to investigate the potentially fibrogenic role of interleukin-1beta (IL-1beta), a macrophage-derived inflammatory cytokine, on cortical fibroblasts (CFs). Primary cultures of human renal CFs were established and incubated for 24 hours in the presence or absence of IL-1beta. We found that IL-1beta significantly stimulated DNA synthesis (356.7% +/- 39% of control, P <.003), fibronectin secretion (261.8 +/- 11% of control, P <.005), collagen type 1 production, (release of procollagen type 1 C-terminal-peptide, 152.4% +/- 26% of control, P <.005), transforming growth factor-beta (TGF-beta) secretion (211% +/- 37% of control, P <.01), and nitric oxide (NO) production (342.8% +/- 69% of control, P <.002). TGF-beta (1 ng/mL) and the phorbol ester phorbol 12-myristate 13-acetate (PMA, 25 nmol/L) produced fibrogenic effects similar to those of IL-1beta. Neither a NO synthase inhibitor (N(G)-methyl-l-arginine, 1 mmol/L) nor a protein kinase C (PKC) inhibitor (bis-indolylmaleimide 1, 1 micromol/L) altered the enhanced level of fibronectin secretion or DNA synthesis seen in response to IL-1beta treatment. However, addition of a TGF-beta-neutralizing antibody significantly reduced IL-1beta-induced fibronectin secretion (IL-1beta + IgG, 262% +/- 72% vs IL-1beta + alphaTGF-beta 156% +/- 14%, P <.02), collagen type 1 production (IL-1beta + IgG, 176% +/- 28% vs IL-1beta + alphaTGF-beta, 120% +/- 14%, P <.005) and abrogated IL-1beta-induced DNA synthesis (245% +/- 49% vs 105% +/- 21%, P <.005). IL-1beta significantly stimulated CF DNA synthesis and production of fibronectin, collagen type 1, TGFbeta, and NO. The fibrogenic and proliferative action of IL-1beta on CF appears not to involve activation of PKC or production of NO but is at least partly TGFbeta-dependent.

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Purpose The purpose of this paper is to determine whether greenhouse gas (GHG) tradeable instruments will be classified as financial products within the scope of the World Trade Organization (WTO) law and to explore the implications of this finding. Design/methodology/approach This purpose is achieved through examination of the units of the Australian Carbon Pricing Mechanism (CPM), namely eligible emissions units. These units are analysed through the lens of the definition of financial products provided in the General Agreement for Trade in Services (the GATS). Findings This paper finds that eligible emissions units will be classified as financial instruments, and therefore the provisions that govern their trade will be regulated by the GATS. Considering this, this paper explores the limitations that are introduced by the Australian legislation on the trade of eligible emissions units. Research limitations/implications This paper is limited in its analysis to the Australian CPM. In order to draw conclusions on the issues raised by this analysis it is necessary to consider the WTO requirements against an operating emissions trading scheme. The Australian CPM presents a contemporary model of an appropriate scheme. Originality/value The findings in this paper are crucial in a GHG constrained society. This is because emissions trading schemes are becoming popular measures for pricing GHG emissions, and for this reason the units that are traded and surrendered for emissions liabilities must be classified appropriately on a global scale. Failing to do this could result in differential treatment that may be contrary to the intentions of important global agreements, such as the WTO covered agreements.

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Studies of the optical properties and catalytic capabilities of noble metal nanoparticles (NPs), such as gold (Au) and silver (Ag), have formed the basis for the very recent fast expansion of the field of green photocatalysis: photocatalysis utilizing visible and ultraviolet light, a major part of the solar spectrum. The reason for this growth is the recognition that the localised surface plasmon resonance (LSPR) effect of Au NPs and Ag NPs can couple the light flux to the conduction electrons of metal NPs, and the excited electrons and enhanced electric fields in close proximity to the NPs can contribute to converting the solar energy to chemical energy by photon-driven photocatalytic reactions. Previously the LSPR effect of noble metal NPs was utilized almost exclusively to improve the performance of semiconductor photocatalysts (for example, TiO2 and Ag halides), but recently, a conceptual breakthrough was made: studies on light driven reactions catalysed by NPs of Au or Ag on photocatalytically inactive supports (insulating solids with a very wide band gap) have demonstrated that these materials are a class of efficient photocatalysts working by mechanisms distinct from those of semiconducting photocatalysts. There are several reasons for the significant photocatalytic activity of Au and Ag NPs. (1) The conduction electrons of the particles gain the irradiation energy, resulting in high energy electrons at the NP surface which is desirable for activating molecules on the particles for chemical reactions. (2) In such a photocatalysis system, both light harvesting and the catalysing reaction take place on the nanoparticle, and so charge transfer between the NPs and support is not a prerequisite. (3) The density of the conduction electrons at the NP surface is much higher than that at the surface of any semiconductor, and these electrons can drive the reactions on the catalysts. (4) The metal NPs have much better affinity than semiconductors to many reactants, especially organic molecules. Recent progress in photocatalysis using Au and Ag NPs on insulator supports is reviewed. We focus on the mechanism differences between insulator and semiconductor-supported Au and Ag NPs when applied in photocatalytic processes, and the influence of important factors, light intensity and wavelength, in particular estimations of light irradiation contribution, by calculating the apparent activation energies of photo reactions and thermal reactions.

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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.

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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.

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Synaptic changes at sensory inputs to the dorsal nucleus of the lateral amygdala (LAd) play a key role in the acquisition and storage of associative fear memory. However, neither the temporal nor spatial architecture of the LAd network response to sensory signals is understood. We developed a method for the elucidation of network behavior. Using this approach, temporally patterned polysynaptic recurrent network responses were found in LAd (intra-LA), both in vitro and in vivo, in response to activation of thalamic sensory afferents. Potentiation of thalamic afferents resulted in a depression of intra-LA synaptic activity, indicating a homeostatic response to changes in synaptic strength within the LAd network. Additionally, the latencies of thalamic afferent triggered recurrent network activity within the LAd overlap with known later occurring cortical afferent latencies. Thus, this recurrent network may facilitate temporal coincidence of sensory afferents within LAd during associative learning.

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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.

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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.

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Many model-based investigation techniques, such as sensitivity analysis, optimization, and statistical inference, require a large number of model evaluations to be performed at different input and/or parameter values. This limits the application of these techniques to models that can be implemented in computationally efficient computer codes. Emulators, by providing efficient interpolation between outputs of deterministic simulation models, can considerably extend the field of applicability of such computationally demanding techniques. So far, the dominant techniques for developing emulators have been priors in the form of Gaussian stochastic processes (GASP) that were conditioned with a design data set of inputs and corresponding model outputs. In the context of dynamic models, this approach has two essential disadvantages: (i) these emulators do not consider our knowledge of the structure of the model, and (ii) they run into numerical difficulties if there are a large number of closely spaced input points as is often the case in the time dimension of dynamic models. To address both of these problems, a new concept of developing emulators for dynamic models is proposed. This concept is based on a prior that combines a simplified linear state space model of the temporal evolution of the dynamic model with Gaussian stochastic processes for the innovation terms as functions of model parameters and/or inputs. These innovation terms are intended to correct the error of the linear model at each output step. Conditioning this prior to the design data set is done by Kalman smoothing. This leads to an efficient emulator that, due to the consideration of our knowledge about dominant mechanisms built into the simulation model, can be expected to outperform purely statistical emulators at least in cases in which the design data set is small. The feasibility and potential difficulties of the proposed approach are demonstrated by the application to a simple hydrological model.

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The ultraviolet photodissociation of gas-phase N-methylpyridinium ions is studied at room temperature using laser photodissociation mass spectrometry and structurally diagnostic ion-molecule reaction kinetics. The C5H5N-CH3+ (m/z 94), C5H5N-CD3+ (m/z 97), and C5D5N-CH3+(m/z 99) isotopologues are investigated, and it is shown that the N-methylpyridinium ion photodissociates by the loss of methane in the 36 000 - 43 000 cm(-1) (280 - 230 nm) region. The dissociation likely occurs on the ground state surface following internal conversion from the SI state. For each isotopologue, by monitoring the photofragmentation yield as a function of photon wavenumber, a broad vibronically featured band is recorded with origin (0-0) transitions assigned at 38 130, 38 140 and 38 320 cm(-1) for C5H5N-CH3+ C5H5N-CD3+ and C5D5N-CH3+, respectively. With the aid of quantum chemical calculations (CASSCF(6,6)/aug-cc-pVDZ), most of the observed vibronic detail is assigned to two in-plane ring deformation modes. Finally, using ion-molecule reactions, the methane coproduct at m/z 78 is confirmed as a 2-pyridinylium ion.

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Nitrogen dioxide is used as a "radical scavenger" to probe the position of carbon-centered radicals within complex radical ions in the gas phase. As with analogous neutral radical reactions, this addition results in formation of an \[M + NO2](+) adduct, but the structural identity of this species remains ambiguous. Specifically, the question remains: do such adducts have a nitro-(RNO2) or nitrosoxy-(RONO) moiety, or are both isomers present in the adduct population? In order to elucidate the products of such reactions, we have prepared and isolated three distonic phenyl radical cations and observed their reactions with nitrogen dioxide in the gas phase by ion-trap mass spectrometry. In each case, stabilized \[M + NO2](+) adduct ions are observed and isolated. The structure of these adducts is probed by collision-induced dissociation and ultraviolet photodissociation action spectroscopy and a comparison made to the analogous spectra of authentic nitro-and nitrosoxy-benzenes. We demonstrate unequivocally that for the phenyl radical cations studied here, all stabilized \[M + NO2](+) adducts are exclusively nitrobenzenes. Electronic structure calculations support these mass spectrometric observations and suggest that, under low-pressure conditions, the nitrosoxy-isomer is unlikely to be isolated from the reaction of an alkyl or aryl radical with NO2. The combined experimental and theoretical results lead to the prediction that stabilization of the nitrosoxy-isomer will only be possible for systems wherein the energy required for dissociation of the RO-NO bond (or other low energy fragmentation channels) rises close to, or above, the energy of the separated reactants.

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Much of what we currently understand about the structure and energetics of multiply charged anions in the gas phase is derived from the measurement of photoelectron spectra of simple dicarboxylate dianions. Here we have employed a modified linear ion-trap mass spectrometer to undertake complementary investigations of the ionic products resulting from laser-initiated electron photodetachment of two model dianions. Electron photodetachment (ePD) of the \[M-2H](2-) dianions formed from glutaric and adipic acid were found to result in a significant loss of ion signal overall, which is consistent with photoelectron studies that report the emission of slow secondary electrons (Xing et al., 2010 \[201). The ePD mass spectra reveal no signals corresponding to the intact \[M-2H](center dot-) radical anions, but rather \[M-2H-CO2](center dot-) ions are identified as the only abundant ionic products indicating that spontaneous decarboxylation follows ejection of the first electron. Interestingly however, investigations of the structure and energetics of the \[M-2H-CO2](center dot-) photoproducts by ion-molecule reaction and electronic structure calculation indicate that (i) these ions are stable with respect to secondary electron detachment and (ii) most of the ion population retains a distonic radical anion structure where the radical remains localised at the position of the departed carboxylate moiety. These observations lead to the conclusion that the mechanism for loss of ion signal involves unimolecular rearrangement reactions of the nascent \[M-2H](center dot-) carbonyloxyl radical anions that compete favourably with direct decarboxylation. Several possible rearrangement pathways that facilitate electron detachment from the radical anion are identified and are computed to be energetically accessible. Such pathways provide an explanation for prior observations of slow secondary electron features in the photoelectron spectra of the same dicaboxylate dianions. (C) 2013 Elsevier B.V. All rights reserved.

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Gas phase peroxyl radicals are central to our chemical understanding of combustion and atmospheric processes and are typically characterized by strong absorption in the UV (lambda(max) approximate to 240 nm). The analogous maximum absorption feature for arylperoxyl radicals is predicted to shift to the visible but has not previously been characterized nor have any photoproducts arising from this transition been identified. Here we describe the controlled synthesis and isolation in vacuo of an array of charge-substituted phenylperoxyl radicals at room temperature, including the 4-(N,N,N-trimethylammonium)methyl phenylperoxyl radical cation (4-Me3N[+]CH2-C6H4OO center dot), using linear ion-trap mass spectrometry. Photodissociation mass spectra obtained at wavelengths ranging from 310 to 500 nm reveal two major photoproduct channels corresponding to homolysis of aryl-OO and arylO-O bonds resulting in loss of O-2 and O, respectively. Combining the photodissociation yields across this spectral window produces a broad (FWHM approximate to 60 nm) but clearly resolved feature centered at lambda(max) = 403 nm (3.08 eV). The influence of the charge-tag identity and its proximity to the radical site are investigated and demonstrate no effect on the identity of the two dominant photoproduct channels. Electronic structure calculations have located the vertical (B) over tilde <- (X) over tilde transition of these substituted phenylperoxyl radicals within the experimental uncertainty and further predict the analogous transition for unsubstituted phenylperoxyl radical (C6H5OO center dot) to be 457 nm (2.71 eV), nearly 45 nm shorter than previous estimates and in good agreement with recent computational values.

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The use of hindered amine light stabilizers (HALS) to retard thermo- and photo-degradation of polymers has become increasingly common. Proposed mechanisms of polymer stabilisation involve significant changes to the HALS chemical structure; however, reports of the characterisation of these modified chemical species are limited. To better understand the fate of HALS and determine their in situ modifications, desorption electrospray ionisation mass spectrometry (DESI-MS) was employed to characterise ten commercially available HALS present in polyester-based coil coatings. TINUVIN® 770, 292, 144, 123, 152, and NOR371; HOSTAVIN® 3052, 3055, 3050, and 3058 were separately formulated with a pigmented, thermosetting polyester resin, cured on metal at 262 C and analysed directly by DESI-MS. High-level ab initio molecular orbital theory calculations were also undertaken to aid the mechanistic interpretation of the results. For HALS containing N-substituted piperidines (i.e., N-CH3, N-C(O)CH3, and N-OR) a secondary piperidine (N-H) analogue was detected in all cases. The formation of these intermediates can be explained either through hydrogen abstraction based mechanisms or direct N-OR homolysis with the former dominant under normal service temperatures (ca. 25-80 C), and the latter potentially becoming competitive under the high temperatures associated with curing (ca. 230-260 C). © 2013 Elsevier Ltd. All rights reserved.

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The reactions of distonic 4-(N, N, N-trimethylammonium)-2-methylphenyl and 5-(N, N, N-trimethylammonium)-2-methylphenyl radical cations (m/z 149) with O-2 are studied in the gas phase using ion-trap mass spectrometry. Photodissociation (PD) of halogenated precursors gives rise to the target distonic charge-tagged methylphenyl radical whereas collision-induced dissociation (CID) is found to produce unreactive radical ions. The PD generated distonic radicals, however, react rapidly with O-2 to form \[M + O2](center dot+) and \[M + O-2 - OH](center dot+) ions, detected at m/z 181 and m/z 164, respectively. Quantum chemical calculations using G3SX(MP3) and M06-2X theories are deployed to examine key decomposition pathways of the 5-(N, N, N-trimethylammonium)-2-methylphenylperoxyl radical and rationalise the observed product ions. The prevailing product mechanism involves a 1,5- H shift in the peroxyl radical forming a QOOH-type intermediate that subsequently eliminates (OH)-O-center dot to yield charge-tagged 2-quinone methide. Our study suggests that the analogous process should occur for the neutral methylphenyl + O-2 reaction, thus serving as a plausible source of (OH)-O-center dot radicals in combustion environments. Grants: ARC/DP0986738, ARC/DP130100862