928 resultados para Mouse Models


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Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an ffective input for travel time prediction. In this paper, the hazard based prediction odels are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS) for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.

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Commodity price modeling is normally approached in terms of structural time-series models, in which the different components (states) have a financial interpretation. The parameters of these models can be estimated using maximum likelihood. This approach results in a non-linear parameter estimation problem and thus a key issue is how to obtain reliable initial estimates. In this paper, we focus on the initial parameter estimation problem for the Schwartz-Smith two-factor model commonly used in asset valuation. We propose the use of a two-step method. The first step considers a univariate model based only on the spot price and uses a transfer function model to obtain initial estimates of the fundamental parameters. The second step uses the estimates obtained in the first step to initialize a re-parameterized state-space-innovations based estimator, which includes information related to future prices. The second step refines the estimates obtained in the first step and also gives estimates of the remaining parameters in the model. This paper is part tutorial in nature and gives an introduction to aspects of commodity price modeling and the associated parameter estimation problem.

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The Construction industry accounts for a tenth of global GDP. Still, challenges such as slow adoption of new work processes, islands of information, and legal disputes, remain frequent, industry-wide occurrences despite various attempts to address them. In response, IT-based approaches have been adopted to explore collaborative ways of executing construction projects. Building Information Modelling (BIM) is an exemplar of integrative technologies whose 3D-visualisation capabilities have fostered collaboration especially between clients and design teams. Yet, the ways in which specification documents are created and used in capturing clients' expectations based on industry standards have remained largely unchanged since the 18th century. As a result, specification-related errors are still common place in an industry where vast amounts of information are consumed as well as produced in the course project implementation in the built environment. By implication, processes such as cost planning which depend on specification-related information remain largely inaccurate even with the use of BIM-based technologies. This paper briefly distinguishes between non-BIM-based and BIM-based specifications and reports on-going efforts geared towards the latter. We review exemplars aimed at extending Building Information Models to specification information embedded within the objects in a product library and explore a viable way of reasoning about a semi-automated process of specification using our product library.

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Bone is a common metastatic site in human breast cancer (HBC). Since bone metastasis occurs very rarely from current spontaneous or experimental metastasis models of HBC cells in nude mice, an arterial seeding model involving the direct injection of the cells into the left ventricle has been developed to better understand the mechanisms involved in this process. We present here a sensitive polymerase chain reaction (PCR) method to detect and quantitate bone and soft organ metastasis in nude mice which have been intracardially inoculated with Lac Z transduced HBC cells. Amplification of genomically incorporated Lac Z sequences in MDA-MB-231-BAG HBC cells enables us to specifically detect these cells in mouse organs and bones. We have also created a competitive template to use as an internal standard in the PCR reactions, allowing us to better quantitate levels of HBC metastasis. The results of this PCR detection method correlate well with cell culture detection from alternate long bones from the same mice, and are more sensitive than gross Lac Z staining with X-gal or routine histology. Comparable qualitative results were obtained with PCR and culture in a titration experiment in which mice were inoculated with increasing numbers of cells, but PCR is more quantifiable, less time consuming, and less expensive. This assay can be employed to study the molecular and cellular aspects of bone metastasis, and could easily be used in conjunction with RT-PCR-based analyses of gene products which may be involved with HBC metastasis.

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We have investigated the gelatinase profiles and invasiveness of clonal tumour sublines derived from a spontaneously arising mammary tumour in a Balb/cfC3H mouse. The 67NR, 66c14 and 4T1.2 sublines have low, intermediate and high metastatic potential respectively. In Boyden chamber studies, Matrigel invasion was seen to be progressively higher in the more metastatic lines 4T1.2>66c14>67NR, consistent with MMP-2 activation potential, MMP-9 secretion, and migration over either type I or IV collagen, which were low in both 67NR and 66c14 cells compared to 4T1.2 cells. These attributes are consistent with those seen in human breast cancer cell lines which appear to have undergone an epithelial-mesenchymal transition (EMT) as indicated by vimentin expression. We were, however, surprised to find vimentin expression, MT1-MMP expression and stellate Matrigel outgrowth in the non-invasive, non-metastatic 67NR cells, indicating that they had undergone an EMT despite not being invasive. We conclude that the EMT is manifested to differing degrees in these three clonal cell lines, and that the 67NR cells have either undergone a partial EMT or have since lost certain important attributes of the EMT-derived phenotype. This model should prove useful in further characterizing the regulation of MT1-MMP mediated MMP-2 activation and delineating the EMT in breast cancer progression.

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The articles collected here in this special edition Epithelial-Mesenchymal (EMT) and Mesenchymal-Epithelial Transitions (MET) in Cancer provide a snapshot of the very rapidly progressing cinemascope of the involvement of these transitions in carcinoma progression. Pubmed analysis of EMT and cancer shows an exponential increase in the last few years in the number of papers and reviews published under these terms (Fig. 1). The last few years have seen these articles appearing in high calibre journals including Nature, Nature Cell Biology, Cancer Cell, PNAS, JNCI, JCI, and Cell, signaling the acceptance and quality of work in this field.

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Electrospray ionisation tandem mass spectrometry has allowed the unambiguous identification and quantification of individual lens phospholipids in human and six animal models. Using this approach ca. 100 unique phospholipids have been characterised. Parallel analysis of the same lens extracts by a novel direct-insertion electron-ionization technique found the cholesterol content of human lenses to be significantly higher (ca. 6 times) than lenses from the other animals. The most abundant phospholipids in all the lenses examined were choline-containing phospholipids. In rat, mouse, sheep, cow, pig and chicken, these were present largely as phosphatidylcholines, in contrast 66% of the total phospholipid in Homo sapiens was sphingomyelin, with the most abundant being dihydrosphingomyelins, in particular SM(d18:0/16:0) and SM(d18:0/24:1). The abundant glycerophospholipids within human lenses were found to be predominantly phosphatidylethanolamines and phosphatidylserines with surprisingly high concentrations of ether-linked alkyl chains identified in both classes. This study is the first to identify the phospholipid class (head-group) and assign the constituent fatty acid(s) for each lipid molecule and to quantify individual lens phospholipids using internal standards. These data clearly indicate marked differences in the membrane lipid composition of the human lens compared to commonly used animal models and thus predict a significant variation in the membrane properties of human lens fibre cells compared to those of other animals. © 2008 Elsevier B.V. All rights reserved.

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We investigated the effects of handling and fixation processes on the two-photon fluorescence spectroscopy of endogenous fluorophors in mouse skeletal muscle. The skeletal muscle was handled in one of two ways: either sectioned without storage or sectioned following storage in a freezer. The two-photon fluorescence spectra measured for different storage or fixation periods show a differential among those samples that were stored in water or were fixed either in formalin or methanol. The spectroscopic results indicate that formalin was the least disruptive fixative, having only a weak effect on the two-photon fluorescence spectroscopy of muscle tissue, whereas methanol had a significant influence on one of the autofluorescence peaks. The two handling processes yielded similar spectral information, indicating no different effects between them.

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We construct a two-scale mathematical model for modern, high-rate LiFePO4cathodes. We attempt to validate against experimental data using two forms of the phase-field model developed recently to represent the concentration of Li+ in nano-sized LiFePO4crystals. We also compare this with the shrinking-core based model we developed previously. Validating against high-rate experimental data, in which electronic and electrolytic resistances have been reduced is an excellent test of the validity of the crystal-scale model used to represent the phase-change that may occur in LiFePO4material. We obtain poor fits with the shrinking-core based model, even with fitting based on “effective” parameter values. Surprisingly, using the more sophisticated phase-field models on the crystal-scale results in poorer fits, though a significant parameter regime could not be investigated due to numerical difficulties. Separate to the fits obtained, using phase-field based models embedded in a two-scale cathodic model results in “many-particle” effects consistent with those reported recently.

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In this paper, we present fully Bayesian experimental designs for nonlinear mixed effects models, in which we develop simulation-based optimal design methods to search over both continuous and discrete design spaces. Although Bayesian inference has commonly been performed on nonlinear mixed effects models, there is a lack of research into performing Bayesian optimal design for nonlinear mixed effects models that require searches to be performed over several design variables. This is likely due to the fact that it is much more computationally intensive to perform optimal experimental design for nonlinear mixed effects models than it is to perform inference in the Bayesian framework. In this paper, the design problem is to determine the optimal number of subjects and samples per subject, as well as the (near) optimal urine sampling times for a population pharmacokinetic study in horses, so that the population pharmacokinetic parameters can be precisely estimated, subject to cost constraints. The optimal sampling strategies, in terms of the number of subjects and the number of samples per subject, were found to be substantially different between the examples considered in this work, which highlights the fact that the designs are rather problem-dependent and require optimisation using the methods presented in this paper.

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Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.

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Existing techniques for automated discovery of process models from event logs largely focus on extracting flat process models. In other words, they fail to exploit the notion of subprocess, as well as structured error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of BPMN models containing subprocesses, interrupting and non-interrupting boundary events, and loop and multi-instance markers. The technique analyzes dependencies between data attributes associated with events, in order to identify subprocesses and to extract their associated logs. Parent process and subprocess models are then discovered separately using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. A validation with one synthetic and two real-life logs shows that process models derived using the proposed technique are more accurate and less complex than those derived with flat process model discovery techniques.

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Laminin has been shown to promote the malignant phenotype and the level of the 32/67 Kd laminin receptor has been found to correlate with Dukes' staging of colon cancer. A biopsy of a Dukes' stage B2 human colon carcinoma formed a tumor in a nude mouse after coinjection with Matrigel. The parental tumor and the murine tumor appeared identical at the histological level. A cell line LCC-C1 was established from the murine tumor. The cell line appeared moderately differentiated although it did not produce mucin in vitro; however, the xenograft in vivo did produce low levels of mucin. Laminin adherent and non-adherent cell lines were selected. The parental and the laminin-selected cell subclones adhered equally well to plastic and to fibronectin and showed similar growth rates on plastic. When injected subcutaneously into nude mice, the laminin-adherent cells formed relatively undifferentiated tumors that were twice as large as the parental cell tumors whereas the laminin non adherent cells formed very small, but highly differentiated tumors. These data demonstrate that subpopulations of tumor cells which differ in their tumorigenic properties can be selected based on their adhesion to laminin and thus provide models for studying the mechanisms of tumor growth.

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Invasion of extracellular matrices is crucial to a number of physiological and pathophysiological states, including tumor cell metastasis, arthritis, embryo implantation, wound healing, and early development. To isolate invasion from the additional complexities of these scenarios a number of in vitro invasion assays have been developed over the years. Early studies employed intact tissues, like denuded amniotic membrane (1) or embryonic chick heart fragments (2), however recently, purified matrix components or complex matrix extracts have been used to provide more uniform and often more rapid analyses (for examples, see the following integrin studies). Of course, the more holistic view of invasion offered in the earlier assays is valuable and cannot be fully reproduced in these more rapid assays, but advantages of reproducibility among replicates, ease of preparation and analysis, and overall high throughput favor the newer assays. In this chapter, we will focus on providing detailed protocols for Matrigel-based assays (Matrigel=reconstituted basement membrane; reviewed in ref. (3)). Matrigel is an extract from the transplantable Engelbreth-Holm-Swarm murine sarcoma that deposits a multilammelar basement membrane. Matrigel is available commercially (Becton Dickinson, Bedford, MA), and can be manipulated as a liquid at 4°C into a variety of different formats. Alternatively, cell culture inserts precoated with Matrigel can be purchased for even greater simplicity.

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The role of vascularization in 3-D tissue engineering was studied. Mouse fat, angiogenic growth factors, adult human stem cells and fat tissue have been inserted and subsequent tissue growth was monitored. Human fat grafts or human lipoaspirates in SCID mouse chambers induced mouse fat generation at 6 weeks. Tissue engineering models utilizing intrinsic vascularization have major advantages including rapid and appropriate vascularization of new tissues.