72 resultados para pelvis lymph node
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MicroRNAs (miRNAs) are small non-coding RNAs of 20 nt in length that are capable of modulating gene expression post-transcriptionally. Although miRNAs have been implicated in cancer, including breast cancer, the regulation of miRNA transcription and the role of defects in this process in cancer is not well understood. In this study we have mapped the promoters of 93 breast cancer-associated miRNAs, and then looked for associations between DNA methylation of 15 of these promoters and miRNA expression in breast cancer cells. The miRNA promoters with clearest association between DNA methylation and expression included a previously described and a novel promoter of the Hsa-mir-200b cluster. The novel promoter of the Hsa-mir-200b cluster, denoted P2, is located 2 kb upstream of the 5′ stemloop and maps within a CpG island. P2 has comparable promoter activity to the previously reported promoter (P1), and is able to drive the expression of miR-200b in its endogenous genomic context. DNA methylation of both P1 and P2 was inversely associated with miR-200b expression in eight out of nine breast cancer cell lines, and in vitro methylation of both promoters repressed their activity in reporter assays. In clinical samples, P1 and P2 were differentially methylated with methylation inversely associated with miR-200b expression. P1 was hypermethylated in metastatic lymph nodes compared with matched primary breast tumours whereas P2 hypermethylation was associated with loss of either oestrogen receptor or progesterone receptor. Hypomethylation of P2 was associated with gain of HER2 and androgen receptor expression. These data suggest an association between miR-200b regulation and breast cancer subtype and a potential use of DNA methylation of miRNA promoters as a component of a suite of breast cancer biomarkers.
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In this study, we investigated the expression profiles and clinicopathological significance of miR-126 in large cohort of patients with colorectal cancers as well the cellular repercussions of miR-126 in colon cancer cells along with its targets in-vitro. Down regulation of miR-126 expression was associated with histological subtypes, peri-neural tumour infiltration, microsatellite instability and pathological staging of colorectal cancers (p<0.05). Low miR-126 expression was also associated with poorer survival in patients with colorectal cancer. Analysis of matched tissues from the same patient revealed that approximately 70% of the tested patients had similar levels of expression of miR-126 in primary cancer and cancer metastases in both lymph node and distant metastases. In addition, induced overexpression of miR-126 showed reduced cell proliferation, increased apoptosis and decreased accumulation of cells in the G0-G1 phase of the colon cancer cells. Furthermore, SW480(+miR-126) cells showed reduced BCL-2 and increased P53 protein expression. To conclude, deregulation of miR-126 in colorectal cancer at the tissue and cellular levels as well as its correlation with various clinicopathological parameters confirm the cancer suppressive role of miR-126 in colorectal cancer.
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The Node-based Local Mesh Generation (NLMG) algorithm, which is free of mesh inconsistency, is one of core algorithms in the Node-based Local Finite Element Method (NLFEM) to achieve the seamless link between mesh generation and stiffness matrix calculation, and the seamless link helps to improve the parallel efficiency of FEM. Furthermore, the key to ensure the efficiency and reliability of NLMG is to determine the candidate satellite-node set of a central node quickly and accurately. This paper develops a Fast Local Search Method based on Uniform Bucket (FLSMUB) and a Fast Local Search Method based on Multilayer Bucket (FLSMMB), and applies them successfully to the decisive problems, i.e. presenting the candidate satellite-node set of any central node in NLMG algorithm. Using FLSMUB or FLSMMB, the NLMG algorithm becomes a practical tool to reduce the parallel computation cost of FEM. Parallel numerical experiments validate that either FLSMUB or FLSMMB is fast, reliable and efficient for their suitable problems and that they are especially effective for computing the large-scale parallel problems.
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It is known that adenosine 5'-triphosphate (ATP) is a cotransmitter in the heart. Additionally, ATP is released from ischemic and hypoxic myocytes. Therefore, cardiac-derived sources of ATP have the potential to modify cardiac function. ATP activates P2X(1-7) and P2Y(1-14) receptors; however, the presence of P2X and P2Y receptor subtypes in strategic cardiac locations such as the sinoatrial node has not been determined. An understanding of P2X and P2Y receptor localization would facilitate investigation of purine receptor function in the heart. Therefore, we used quantitative PCR and in situ hybridization to measure the expression of mRNA of all known purine receptors in rat left ventricle, right atrium and sinoatrial node (SAN), and human right atrium and SAN. Expression of mRNA for all the cloned P2 receptors was observed in the ventricles, atria, and SAN of the rat. However, their abundance varied in different regions of the heart. P2X(5) was the most abundant of the P2X receptors in all three regions of the rat heart. In rat left ventricle, P2Y(1), P2Y(2), and P2Y(14) mRNA levels were highest for P2Y receptors, while in right atrium and SAN, P2Y(2) and P2Y(14) levels were highest, respectively. We extended these studies to investigate P2X(4) receptor mRNA in heart from rats with coronary artery ligation-induced heart failure. P2X(4) receptor mRNA was upregulated by 93% in SAN (P < 0.05), while a trend towards an increase was also observed in the right atrium and left ventricle (not significant). Thus, P2X(4)-mediated effects might be modulated in heart failure. mRNA for P2X(4-7) and P2Y(1,2,4,6,12-14), but not P2X(2,3) and P2Y(11), was detected in human right atrium and SAN. In addition, mRNA for P2X(1) was detected in human SAN but not human right atrium. In human right atrium and SAN, P2X(4) and P2X(7) mRNA was the highest for P2X receptors. P2Y(1) and P2Y(2) mRNA were the most abundant for P2Y receptors in the right atrium, while P2Y(1), P2Y(2), and P2Y(14) were the most abundant P2Y receptor subtypes in human SAN. This study shows a widespread distribution of P2 receptor mRNA in rat heart tissues but a more restricted presence and distribution of P2 receptor mRNA in human atrium and SAN. This study provides further direction for the elucidation of P2 receptor modulation of heart rate and contractility.
Molecular architecture of the human sinus node: insights into the function of the cardiac pacemaker.
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BACKGROUND: Although we know much about the molecular makeup of the sinus node (SN) in small mammals, little is known about it in humans. The aims of the present study were to investigate the expression of ion channels in the human SN and to use the data to predict electrical activity. METHODS AND RESULTS: Quantitative polymerase chain reaction, in situ hybridization, and immunofluorescence were used to analyze 6 human tissue samples. Messenger RNA (mRNA) for 120 ion channels (and some related proteins) was measured in the SN, a novel paranodal area, and the right atrium (RA). The results showed, for example, that in the SN compared with the RA, there was a lower expression of Na(v)1.5, K(v)4.3, K(v)1.5, ERG, K(ir)2.1, K(ir)6.2, RyR2, SERCA2a, Cx40, and Cx43 mRNAs but a higher expression of Ca(v)1.3, Ca(v)3.1, HCN1, and HCN4 mRNAs. The expression pattern of many ion channels in the paranodal area was intermediate between that of the SN and RA; however, compared with the SN and RA, the paranodal area showed greater expression of K(v)4.2, K(ir)6.1, TASK1, SK2, and MiRP2. Expression of ion channel proteins was in agreement with expression of the corresponding mRNAs. The levels of mRNA in the SN, as a percentage of those in the RA, were used to estimate conductances of key ionic currents as a percentage of those in a mathematical model of human atrial action potential. The resulting SN model successfully produced pacemaking. CONCLUSIONS: Ion channels show a complex and heterogeneous pattern of expression in the SN, paranodal area, and RA in humans, and the expression pattern is appropriate to explain pacemaking.
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This paper formulates a node-based smoothed conforming point interpolation method (NS-CPIM) for solid mechanics. In the proposed NS-CPIM, the higher order conforming PIM shape functions (CPIM) have been constructed to produce a continuous and piecewise quadratic displacement field over the whole problem domain, whereby the smoothed strain field was obtained through smoothing operation over each smoothing domain associated with domain nodes. The smoothed Galerkin weak form was then developed to create the discretized system equations. Numerical studies have demonstrated the following good properties: NS-CPIM (1) can pass both standard and quadratic patch test; (2) provides an upper bound of strain energy; (3) avoid the volumetric locking; (4) provides the higher accuracy than those in the node-based smoothed schemes of the original PIMs.
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Finite Element Modeling (FEM) has become a vital tool in the automotive design and development processes. FEM of the human body is a technique capable of estimating parameters that are difficult to measure in experimental studies with the human body segments being modeled as complex and dynamic entities. Several studies have been dedicated to attain close-to-real FEMs of the human body (Pankoke and Siefert 2007; Amann, Huschenbeth et al. 2009; ESI 2010). The aim of this paper is to identify and appraise the state of-the art models of the human body which incorporate detailed pelvis and/or lower extremity models. Six databases and search engines were used to obtain literature, and the search was limited to studies published in English since 2000. The initial search results identified 636 pelvis-related papers, 834 buttocks-related papers, 505 thigh-related papers, 927 femur-related papers, 2039 knee-related papers, 655 shank-related papers, 292 tibia-related papers, 110 fibula-related papers, 644 ankle related papers, and 5660 foot-related papers. A refined search returned 100 pelvis-related papers, 45 buttocks related papers, 65 thigh-related papers, 162 femur-related papers, 195 kneerelated papers, 37 shank-related papers, 80 tibia-related papers, 30 fibula-related papers and 102 ankle-related papers and 246 foot-related papers. The refined literature list was further restricted by appraisal against a modified LOW appraisal criteria. Studies with unclear methodologies, with a focus on populations with pathology or with sport related dynamic motion modeling were excluded. The final literature list included fifteen models and each was assessed against the percentile the model represents, the gender the model was based on, the human body segment/segments included in the model, the sample size used to develop the model, the source of geometric/anthropometric values used to develop the model, the posture the model represents and the finite element solver used for the model. The results of this literature review provide indication of bias in the available models towards 50th percentile male modeling with a notable concentration on the pelvis, femur and buttocks segments.
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This work focuses on the development of a stand-alone gas nanosensor node, powered by solar energy to track concentration of polluted gases such as NO2, N2O, and NH3. Gas sensor networks have been widely developed over recent years, but the rise of nanotechnology is allowing the creation of a new range of gas sensors [1] with higher performance, smaller size and an inexpensive manufacturing process. This work has created a gas nanosensor node prototype to evaluate future field performance of this new generation of sensors. The sensor node has four main parts: (i) solar cells; (ii) control electronics; (iii) gas sensor and sensor board interface [2-4]; and (iv) data transmission. The station is remotely monitored through wired (ethernet cable) or wireless connection (radio transmitter) [5, 6] in order to evaluate, in real time, the performance of the solar cells and sensor node under different weather conditions. The energy source of the node is a module of polycrystalline silicon solar cells with 410cm2 of active surface. The prototype is equipped with a Resistance-To-Period circuit [2-4] to measure the wide range of resistances (KΩ to GΩ) from the sensor in a simple and accurate way. The system shows high performance on (i) managing the energy from the solar panel, (ii) powering the system load and (iii) recharging the battery. The results show that the prototype is suitable to work with any kind of resistive gas nanosensor and provide useful data for future nanosensor networks.
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Network reconfiguration after complete blackout of a power system is an essential step for power system restoration. A new node importance evaluation method is presented based on the concept of regret, and maximisation of the average importance of a path is employed as the objective of finding the optimal restoration path. Then, a two-stage method is presented to optimise the network reconfiguration strategy. Specifically, the restoration sequence of generating units is first optimised so as to maximise the restored generation capacity, then the optimal restoration path is selected to restore the generating nodes concerned and the issues of selecting a serial or parallel restoration mode and the reconnecting failure of a transmission line are next considered. Both the restoration path selection and skeleton-network determination are implemented together in the proposed method, which overcomes the shortcoming of separate decision-making in the existing methods. Finally, the New England 10-unit 39-bus power system and the Guangzhou power system in South China are employed to demonstrate the basic features of the proposed method.
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This paper discusses a framework in which catalog service communities are built, linked for interaction, and constantly monitored and adapted over time. A catalog service community (represented as a peer node in a peer-to-peer network) in our system can be viewed as domain specific data integration mediators representing the domain knowledge and the registry information. The query routing among communities is performed to identify a set of data sources that are relevant to answering a given query. The system monitors the interactions between the communities to discover patterns that may lead to restructuring of the network (e.g., irrelevant peers removed, new relationships created, etc.).
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Air pollution levels were monitored continuously over a period of 4 weeks at four sampling sites along a busy urban corridor in Brisbane. The selected sites were representative of industrial and residential types of urban environment affected by vehicular traffic emissions. The concentration levels of submicrometer particle number, PM2.5, PM10, CO, and NOx were measured 5-10 meters from the road. Meteorological parameters and traffic flow rates were also monitored. The data were analysed in terms of the relationship between monitored pollutants and existing ambient air quality standards. The results indicate that the concentration levels of all pollutants exceeded the ambient air background levels, in certain cases by up to an order of magnitude. While the 24-hr average concentration levels did not exceed the standard, estimates for the annual averages were close to, or even higher than the annual standard levels.
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The occurrence and levels of airborne polycyclic aromatic hydrocarbons and volatile organic compounds in selected non-industrial environments in Brisbane have been investigated as part of an integrated indoor air quality assessment program. The most abundant and most frequently encountered compounds include, nonanal, decanal, texanol, phenol, 2-ethyl-1-hexanol, ethanal, naphthalene, 2,6-tert-butyl-4-methyl-phenol (BHT), salicylaldehyde, toluene, hexanal, benzaldehyde, styrene, ethyl benzene, o-, m- and pxylenes, benzene, n-butanol, 1,2-propandiol, and n-butylacetate. Many of the 64 compounds usually included in the European Collaborative Action method of TVOC analysis were below detection limits in the samples analysed. In order to extract maximum amount of information from the data collected, multivariate data projection methods have been employed. The implications of the information extracted on source identification and exposure control are discussed.
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Bayesian Belief Networks (BBNs) are emerging as valuable tools for investigating complex ecological problems. In a BBN, the important variables in a problem are identified and causal relationships are represented graphically. Underpinning this is the probabilistic framework in which variables can take on a finite range of mutually exclusive states. Associated with each variable is a conditional probability table (CPT), showing the probability of a variable attaining each of its possible states conditioned on all possible combinations of it parents. Whilst the variables (nodes) are connected, the CPT attached to each node can be quantified independently. This allows each variable to be populated with the best data available, including expert opinion, simulation results or observed data. It also allows the information to be easily updated as better data become available ----- ----- This paper reports on the process of developing a BBN to better understand the initial rapid growth phase (initiation) of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay, Queensland. Anecdotal evidence suggests that Lyngbya blooms in this region have increased in severity and extent over the past decade. Lyngbya has been associated with acute dermatitis and a range of other health problems in humans. Blooms have been linked to ecosystem degradation and have also damaged commercial and recreational fisheries. However, the causes of blooms are as yet poorly understood.
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Some polycyclic aromatic hydrocarbons (PAHs) are ubiquitous in air and have been implicated as carcinogenic materials. Therefore, literature is replete with studies that are focused on their occurrence and profiles in indoor and outdoor air samples. However, because the relative potency of individual PAHs vary widely, health risks associated with the presence of PAHs in a particular environment cannot be extrapolated directly from the concentrations of individual PAHs in that environment. In addition, database on the potency of PAH mixtures is currently limited. In this paper, we have utilized multi-criteria decision making methods (MCDMs) to simultaneously correlate PAH-related health risk in some microenvironments to the concentration levels, ethoxyresorufin-O-deethylase (EROD) activity induction equivalency factors and toxic equivalency factors (TEFs) of PAHs found in those microenvironments. The results showed that the relative risk associated with PAHs in different air samples depends on the index used. Nevertheless, this approach offers a promising tool that could help identify microenvironments of concern and assist the prioritisation of control strategies.