83 resultados para decomposition microenvironment


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This study analyzes the management of air pollutant substance in Chinese industrial sectors from 1998 to 2009. Decomposition analysis applying the logarithmic mean divisia index is used to analyze changes in emissions of air pollutants with a focus on the following five factors: coal pollution intensity (CPI), end-of-pipe treatment (EOP), the energy mix (EM), productive efficiency change (EFF), and production scale changes (PSC). Three pollutants are the main focus of this study: sulfur dioxide (SO2), dust, and soot. The novelty of this paper is focusing on the impact of the elimination policy on air pollution management in China by type of industry using the scale merit effect for pollution abatement technology change. First, the increase in SO2 emissions from Chinese industrial sectors because of the increase in the production scale is demonstrated. However, the EOP equipment that induced this change and improvements in energy efficiency has prevented an increase in SO2 emissions that is commensurate with the increase in production. Second, soot emissions were successfully reduced and controlled in all industries except the steel industry between 1998 and 2009, even though the production scale expanded for these industries. This reduction was achieved through improvements in EOP technology and in energy efficiency. Dust emissions decreased by nearly 65% between 1998 and 2009 in the Chinese industrial sectors. This successful reduction in emissions was achieved by implementing EOP technology and pollution prevention activities during the production processes, especially in the cement industry. Finally, pollution prevention in the cement industry is shown to result from production technology development rather than scale merit. © 2013 Elsevier Ltd. All rights reserved.

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This study analyzes toxic chemical substance management in three U.S. manufacturing sectors from 1991 to 2008. Decomposition analysis applying the logarithmic mean Divisia index is used to analyze changes in toxic chemical substance emissions by the following five factors: cleaner production, end-of-pipe treatment, transfer for further management, mixing of intermediate materials, and production scale. Based on our results, the chemical manufacturing sector reduced toxic chemical substance emissions mainly via end-of-pipe treatment. In the meantime, transfer for further management contributed to the reduction of toxic chemical substance emissions in the metal fabrication industry. This occurred because the environmental business market expanded in the 1990s, and the infrastructure for the recycling of metal and other wastes became more efficient. Cleaner production is the main contributor to toxic chemical reduction in the electrical product industry. This implies that the electrical product industry is successful in developing a more environmentally friendly product design and production process.

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This study decomposed the determinants of environmental quality into scale, technique, and composition effects. We applied a semiparametric method of generalized additive models, which enabled us to use flexible functional forms and include several independent variables in the model. The differences in the technique effect were found to play a crucial role in reducing pollution. We found that the technique effect was sufficient to reduce sulfur dioxide emissions. On the other hand, its effect was not enough to reduce carbon dioxide (CO2) emissions and energy use, except for the case of CO2 emissions in high-income countries.

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This project characterised the bone microarchitecture of adult mice lacking the hormone, acyl ghrelin, by high resolution micro-computed tomography; and investigated the expression of the ghrelin axis in cells of human and mouse fetal cartilage. This thesis highlights for the first time the physiological role of the ghrelin axis in the bone microenvironment of aged mice. Furthermore it improves our understanding of the complex expression patterns of the ghrelin axis in cartilage cells of human and mouse fetal skeletons.

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The thermal decomposition process of kaolinite–potassium acetate intercalation complex has been studied using simultaneous thermogravimetry coupled with Fourier-transform infrared spectroscopy and mass spectrometry (TG-FTIR-MS). The results showed that the thermal decomposition of the complex took place in four temperature ranges, namely 50–100, 260–320, 320–550, and 650–780 °C. The maximal mass losses rate for the thermal decomposition of the kaolinite–potassium acetate intercalation complex was observed at 81, 296, 378, 411, 486, and 733 °C, which was attributed to (a) loss of the adsorbed water, (b) thermal decomposition of surface-adsorbed potassium acetate (KAc), (c) the loss of the water coordinated to potassium acetate in the intercalated kaolinite, (d) the thermal decomposition of intercalated KAc in the interlayer of kaolinite and the removal of inner surface hydroxyls, (e) the loss of the inner hydroxyls, and (f) the thermal decomposition of carbonate derived from the decomposition of KAc. The thermal decomposition of intercalated potassium acetate started in the range 320–550 °C accompanied by the release of water, acetone, carbon dioxide, and acetic acid. The identification of pyrolysis fragment ions provided insight into the thermal decomposition mechanism. The results showed that the main decomposition fragment ions of the kaolinite–KAc intercalation complex were water, acetone, carbon dioxide, and acetic acid. TG-FTIR-MS was demonstrated to be a powerful tool for the investigation of kaolinite intercalation complexes. It delivers a detailed insight into the thermal decomposition processes of the kaolinite intercalation complexes characterized by mass loss and the evolved gases.

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One of the hallmarks of cancer is the ability to activate invasion and metastasis (Hanahan et al., 2011). Cancer morbidity and mortality are largely related to the spread of the primary, localised tumour to adjacent and distant sites (Pantel et al., 2004). Appropriate management and treatment decisions of predicting metastatic disease at the time of diagnosis is thus crucial, which supports better understanding of the metastatic process. There are common events that occur during metastasis: dissociation from the primary tumour mass, reorganisation/remodelling of extracellular matrix, cell migration, recognition and transversal of endothelial cells and the vascular circulation and lodgement and proliferation within ectopic stroma (Wells, 2006). One of the key and initial events is the increased capability of cancer cells to move, escaping the regulation of normal physiological control. The cellular cytoskeleton plays an important role in cancer cell motility and active cytoskeletal rearrangement can result in metastatic disease. This active change in cytoskeletal dynamics results in manipulation of plasma membrane and cellular balance between cellular adhesion and motility which in turn determines cancer cell movement. Members of the tetraspanins play important roles in regulation of cancer migration and cancer-endothelial cell interactions, which are critical for cancer invasion and metastasis. Their involvements in active cytoskeletal dynamics, cancer metastasis and potential clinical application will be discussed in this review. In particular, tetraspanin member, CD151, is highlighted for its major role in cancer invasion and metastasis

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In an estuary, mixing and dispersion are the result of the combination of large scale advection and small scale turbulence which are both complex to estimate. A field study was conducted in a small sub-tropical estuary in which high frequency (50 Hz) turbulent data were recorded continuously for about 48 hours. A triple decomposition technique was introduced to isolate the contributions of tides, resonance and turbulence in the flow field. A striking feature of the data set was the slow fluctuations which exhibited large amplitudes up to 50% the tidal amplitude under neap tide conditions. The triple decomposition technique allowed a characterisation of broader temporal scales of high frequency fluctuation data sampled during a number of full tidal cycles.

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The function of a protein can be partially determined by the information contained in its amino acid sequence. It can be assumed that proteins with similar amino acid sequences normally have closer functions. Hence analysing the similarity of proteins has become one of the most important areas of protein study. In this work, a layered comparison method is used to analyze the similarity of proteins. It is based on the empirical mode decomposition (EMD) method, and protein sequences are characterized by the intrinsic mode functions (IMFs). The similarity of proteins is studied with a new cross-correlation formula. It seems that the EMD method can be used to detect the functional relationship of two proteins. This kind of similarity method is a complement of traditional sequence similarity approaches which focus on the alignment of amino acids

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Tumour microenvironment greatly influences the development and metastasis of cancer progression. The development of three dimensional (3D) culture models which mimic that displayed in vivo can improve cancer biology studies and accelerate novel anticancer drug screening. Inspired by a systems biology approach, we have formed 3D in vitro bioengineered tumour angiogenesis microenvironments within a glycosaminoglycan-based hydrogel culture system. This microenvironment model can routinely recreate breast and prostate tumour vascularisation. The multiple cell types cultured within this model were less sensitive to chemotherapy when compared with two dimensional (2D) cultures, and displayed comparative tumour regression to that displayed in vivo. These features highlight the use of our in vitro culture model as a complementary testing platform in conjunction with animal models, addressing key reduction and replacement goals of the future. We anticipate that this biomimetic model will provide a platform for the in-depth analysis of cancer development and the discovery of novel therapeutic targets.

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Two-dimensional (2D) substrates cannot accurately mimic the complex matrix of native TME, whereas 3D models can recapitulate the natural tumour progression in vitro. As part of the tumour stroma, fibroblasts and endothelial cells (ECs) are well-known to not only support tumour growth but also to reduce the efficacy of anti-cancer drugs. Particularly, ECs are involved in the process of tumour vascularisation which represents a crucial step in the progression of cancer. Most of the previous studies are carried out in animal models or 2D cultures; hence, a detailed evaluation of experimental data is poor. To address this issue, we aim to develop a novel 3D in vitro approach, to mimic native tumour angiogenesis in 3D and to quantify the developed vascular network.

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Prostate cancer is a leading cause of male cancer-related death and novel therapies are required that prevent progression to terminal disease. This study identified novel protein targets and cell signalling pathways regulated by the prostate cancer-associated protease, kallikrein-related peptidase 4, highlighting it as a promising target for anti-cancer therapy. Seventy-five novel targets and key signalling pathways were identified to be regulated by the protease, suggesting novel functions in remodelling tumour tissue to enable prostate cancer progression.

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Prostate cancer is the most commonly diagnosed malignancy in men and advanced disease is incurable. Model systems are a fundamental tool for research and many in vitro models of prostate cancer use cancer cell lines in monoculture. Although these have yielded significant insight they are inherently limited by virtue of their two-dimensional (2D) growth and inability to include the influence of tumour microenvironment. These major limitations can be overcome with the development of newer systems that more faithfully recreate and mimic the complex in vivo multi-cellular, three-dimensional (3D) microenvironment. This article presents the current state of in vitro models for prostate cancer, with particular emphasis on 3D systems and the challenges that remain before their potential to advance our understanding of prostate disease and aid in the development and testing of new therapeutic agents can be realised.