990 resultados para Chemical affinity.
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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.
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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.
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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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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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Background and Purpose The β1-adrenoceptor has at least two binding sites, high and low affinity sites (β1H and β1L, respectively), which mediate cardiostimulation. While β1H-adrenoceptor can be blocked by all clinically used β-blockers, β1L-adrenoceptor is relatively resistant to blockade. Thus, chronic β1L-adrenoceptor activation may mediate persistent cardiostimulation, despite the concurrent blockade of β1H-adrenoceptors. Hence, it is important to determine the potential significance of β1L-adrenoceptors in vivo, particularly in pathological situations. Experimental Approach C57Bl/6 male mice were used. Chronic (4 or 8 weeks) β1L-adrenoceptor activation was achieved by treatment, via osmotic mini pumps, with (-)-CGP12177 (10 mg·kg−1·day−1). Cardiac function was assessed by echocardiography and micromanometry. Key Results (-)-CGP12177 treatment of healthy mice increased heart rate and left ventricular (LV) contractility. (-)-CGP12177 treatment of mice subjected to transverse aorta constriction (TAC), during weeks 4–8 or 4–12 after TAC, led to a positive inotropic effect and exacerbated fibrogenic signalling while cardiac hypertrophy tended to be more severe. (-)-CGP12177 treatment of mice with TAC also exacerbated the myocardial expression of hypertrophic, fibrogenic and inflammatory genes compared to untreated TAC mice. Washout of (-)-CGP12177 revealed a more pronounced cardiac dysfunction after 12 weeks of TAC. Conclusions and Implications β1L-adrenoceptor activation provides functional support to the heart, in both normal and pathological (pressure overload) situations. Sustained β1L-adrenoceptor activation in the diseased heart exacerbates LV remodelling and therefore may promote disease progression from compensatory hypertrophy to heart failure.
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Poly(l-lactide) (PLLA), a versatile biodegradable polymer, is one of the most commonly-used materials for tissue engineering applications. To improve cell affinity for PLLA, poly(ethylene glycol) (PEG) was used to develop diblock copolymers. Human bone marrow stromal cells (hBMSCs) were cultured on MPEG-b-PLLA copolymer films to determine the effects of modification on the attachment and proliferation of hBMSC. The mRNA expression of 84 human extracellular matrix (ECM) and adhesion molecules was analyzed using RT-qPCR to understand the underlying mechanisms. It was found that MPEG-b-PLLA copolymer films significantly improved cell adhesion, extension, and proliferation.This was found to be related to the significant upregulation of two adhesion genes, CDH1 and CTNND2, which encode 1-cadherin and delta-2-catenin, respectively, two key components for the cadherin-catenin complex. In summary, MPEG-b-PLLA copolymer surfaces improved initial cell adhesion by stimulation of adhesion molecule gene expression.
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Frondosins A−E, 1−5 (Figure 1), are a family of related marine sesquiterpenoids first isolated in their dextro-rotatory form from the sponge Dysidea frondosa.(1a) Additionally, levo-rotatory frondosins A and D were isolated from an unidentified Eurospongia species.(1b) Frondosins A−E are compounds of interest due to their promising interleukin-8 (IL-8) affinity and protein kinase C inhibition.(1a) IL-8 antagonists are of particular interest in view of their antiinflammatory,(2a) anti-HIV,(1b, 2b) and antitumor(2c-2f) properties. To date, frondosins A, B, and C have been synthesized.(3) Notwithstanding these successes, the frondosins have proved quite a formidable synthetic challenge, and as of yet, there has been no synthesis of frondosin D or E. In this report, we describe our approaches to the molecular scaffold of frondosins D. This work has culminated in a very effective means of producing the trimethylbicyclo[5.4.0]undecane ring system common to all frondosins (shown in bold, Figure 1).
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The ion (C6CH2)(.-) is formed in the gas phase by the process -C=C-C=C-C=CH2OEt --> (C6CH2)(.-) + EtO., and charge stripping of the product radical anion yields the carbenoid neutral C6CH2; this can be either a singlet (the ground state), which is best represented as the carbene :C=C=C=C=C=C=CH2, or a triplet; the adiabatic electron affinity and the dipole moment of the carbenoid neutral are calculated to be 2.82 eV and 7.33 D respectively.
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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.
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We present a determination of Delta(f)H(298)(HOO) based upon a negative. ion thermodynamic cycle. The photoelectron spectra of HOO- and DOO- were used to measure the molecular electron affinities (EAs). In a separate experiment, a tandem flowing afterglow-selected ion flow tube (FA-SIFT) was used to measure the forward and reverse rate constants for HOO- + HCdropCH reversible arrow HOOH + HCdropC(-) at 298 K, which gave a value for Delta(acid)H(298)(HOO-H). The experiments yield the following values: EA(HOO) = 1.078 +/- 0.006 eV; T-0((X) over tilde HOO - (A) over tilde HOO) = 0.872 +/- 0.007 eV; EA(DOO) = 1.077 +/- 0.005 eV; T-0((X) over tilde DOO - (A) over tilde DOO) = 0.874 +/- 0.007 eV; Delta(acid)G(298)(HOO-H) = 369.5 +/- 0.4 kcal mol(-1); and Delta(acid)H(298)(HOO-H) = 376.5 +/- 0.4 kcal mol(-1). The acidity/EA thermochemical cycle yields values for the bond enthalpies of DH298(HOO-H) = 87.8 +/- 0.5 kcal mol(-1) and Do(HOO-H) = 86.6 +/- 0.5 kcal mol(-1). We recommend the following values for the heats of formation of the hydroperoxyl radical: Delta(f)H(298)(HOO) = 3.2 +/- 0.5 kcal mol(-1) and Delta(f)H(0)(HOO) = 3.9 +/- 0.5 kcal mol(-1); we recommend that these values supersede those listed in the current NIST-JANAF thermochemical tables.
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Budbreak in kiwifruit (Actinidia deliciosa) can be poor in locations that have warm winters with insufficient winter chilling. Kiwifruit vines are often treated with the dormancy-breaking chemical hydrogen cyanamide (HC) to increase and synchronize budbreak. This treatment also offers a tool to understand the processes involved in budbreak. A genomics approach is presented here to increase our understanding of budbreak in kiwifruit. Most genes identified following HC application appear to be associated with responses to stress, but a number of genes appear to be associated with the reactivation of growth. Three patterns of gene expression were identified: Profile 1, an HC-induced transient activation; Profile 2, an HC-induced transient activation followed by a growth-related activation; and Profile 3, HC- and growth-repressed. One group of genes that was rapidly up-regulated in response to HC was the glutathione S-transferase (GST) class of genes, which have been associated with stress and signalling. Previous budbreak studies, in three other species, also report up-regulated GST expression. Phylogenetic analysis of these GSTs showed that they clustered into two sub-clades, suggesting a strong correlation between their expression and budbreak across species.
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Methyl, methyl-d(3), and ethyl hydroperoxide anions (CH3OO-, CD3OO-, and CH3CH2OO-) have been prepared by deprotonation of their respective hydroperoxides in a stream of helium buffer, gas. Photodetachment with 364 nm (3.408 eV) radiation was used to measure the adiabatic electron affinities: EA[CH3OO, (X) over tilde (2)A"] = 1.161 +/- 0.005 eV, EA[CD3OO, (X) over tilde (2)A"] = 1.154 +/- 0.004 eV, and EA[CH3CH2OO, (X) over tilde (2)A"] = 1.186 +/- 0.004 eV. The photoelectron spectra yield values for the term energies: DeltaE((X) over tilde 2A"-(A) over tilde 2A')[CH3OO] = 0.914 +/- 0.005 eV, DeltaE((X) over tilde (2)A"-(A) over tilde 2A') [CD3OO] = 0.913 +/- 0.004 eV, and DeltaE((X) over tilde (2)A"-(A) over tilde (2)A')[CH3CH2OO] = 0.938 +/- 0.004 eV. A localized RO-O stretching mode was observed near 1100 cm(-1) for the ground state of all three radicals, and low-frequency R-O-O bending modes are also reported. Proton-transfer kinetics of the hydroperoxides have been measured in a tandem flowing afterglow-selected ion flow tube k(FA-SIFT) to determine the gas-phase acidity of the parent hydroperoxides: Delta (acid)G(298)(CH3OOH) = 367.6 +/- 0.7 kcal mol(-1), Delta (acid)G(298)(CD3OOH) = 367.9 +/- 0.9 kcal mol(-1), and Delta (acid)G(298)(CH3CH2OOH) = 363.9 +/- 2.0 kcal mol(-1). From these acidities we have derived the enthalpies of deprotonation: Delta H-acid(298)(CH3OOH) = 374.6 +/- 1.0 kcal mol(-1), Delta H-acid(298)(CD3OOH) = 374.9 +/- 1.1 kcal mol(-1), and Delta H-acid(298)(CH2CH3OOH) = 371.0 +/- 2.2 kcal mol(-1). Use of the negative-ion acidity/EA cycle provides the ROO-H bond enthalpies: DH298(CH3OO-H) 87.8 +/- 1.0 kcal mol(-1), DH298(CD3OO-H) = 87.9 +/- 1.1 kcal mol(-1), and DH298(CH3CH2OO-H) = 84.8 +/- 2.2 kcal mol(-1). We review the thermochemistry of the peroxyl radicals, CH3OO and CH3CH2OO. Using experimental bond enthalpies, DH298(ROO-H), and CBS/APNO ab initio electronic structure calculations for the energies of the corresponding hydroperoxides, we derive the heats of formation of the peroxyl radicals. The "electron affinity/acidity/CBS" cycle yields Delta H-f(298)[CH3OO] = 4.8 +/- 1.2 kcal mol(-1) and Delta H-f(298)[CH3CH2OO] = -6.8 +/- 2.3 kcal mol(-1).