123 resultados para dynamic factor models


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Intrinsic or acquired resistance to chemotherapeutic agents is a common phenomenon and a major challenge in the treatment of cancer patients. Chemoresistance is defined by a complex network of factors including multi-drug resistance proteins, reduced cellular uptake of the drug, enhanced DNA repair, intracellular drug inactivation, and evasion of apoptosis. Pre-clinical models have demonstrated that many chemotherapy drugs, such as platinum-based agents, antracyclines, and taxanes, promote the activation of the NF-κB pathway. NF-κB is a key transcription factor, playing a role in the development and progression of cancer and chemoresistance through the activation of a multitude of mediators including anti-apoptotic genes. Consequently, NF-κB has emerged as a promising anti-cancer target. Here, we describe the role of NF-κB in cancer and in the development of resistance, particularly cisplatin. Additionally, the potential benefits and disadvantages of targeting NF-κB signaling by pharmacological intervention will be addressed.

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Many newspapers and magazines have added “social media features” to their web-based information services in order to allow users to participate in the production of content. This study examines the specific impact of the firm’s investment in social media features on their online business models. We make a comparative case study of four Scandinavian print media firms that have added social media features to their online services. We show how social media features lead to online business model innovation, particularly linked to the firms’ value propositions. The paper discusses the repercussions of this transformation on firms’ relationship with consumers and with traditional content contributors. The modified value proposition also requires firms to acquire new competences in order to reap full benefit of their social media investments. We show that the firms have been unable to do so since they have not allowed the social media features to affect their online revenue models.

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This paper presents a study done into the effectiveness of using local acceleration measurements vs. remote angle measurements in providing stabilising control via SVCs following large disturbances. The system studied was an analogue of the Queensland-New South Wales Interconnection (QNI) and involved the control of an existing Static Var Compensators (SVC) at Sydney West. This study is placed in the context of wide area controls for large systems using aggregated models for groups of machines.

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A predictive model of terrorist activity is developed by examining the daily number of terrorist attacks in Indonesia from 1994 through 2007. The dynamic model employs a shot noise process to explain the self-exciting nature of the terrorist activities. This estimates the probability of future attacks as a function of the times since the past attacks. In addition, the excess of nonattack days coupled with the presence of multiple coordinated attacks on the same day compelled the use of hurdle models to jointly model the probability of an attack day and corresponding number of attacks. A power law distribution with a shot noise driven parameter best modeled the number of attacks on an attack day. Interpretation of the model parameters is discussed and predictive performance of the models is evaluated.

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Dynamic light scattering (DLS) has become a primary nanoparticle characterization technique with applications from materials characterization to biological and environmental detection. With the expansion in DLS use from homogeneous spheres to more complicated nanostructures, comes a decrease in accuracy. Much research has been performed to develop different diffusion models that account for the vastly different structures but little attention has been given to the effect on the light scattering properties in relation to DLS. In this work, small (core size < 5 nm) core-shell nanoparticles were used as a case study to measure the capping thickness of a layer of dodecanethiol (DDT) on Au and ZnO nanoparticles by DLS. We find that the DDT shell has very little effect on the scattering properties of the inorganic core and hence can be ignored to a first approximation. However, this results in conventional DLS analysis overestimating the hydrodynamic size in the volume and number weighted distributions. By introducing a simple correction formula that more accurately yields hydrodynamic size distributions a more precise determination of the molecular shell thickness is obtained. With this correction, the measured thickness of the DDT shell was found to be 7.3 ± 0.3 Å, much less than the extended chain length of 16 Å. This organic layer thickness suggests that on small nanoparticles, the DDT monolayer adopts a compact disordered structure rather than an open ordered structure on both ZnO and Au nanoparticle surfaces. These observations are in agreement with published molecular dynamics results.

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Organizational learning has been studied as a key factor in firm performance and internationalization. Moving beyond the past emphasis on market learning, we develop a more complete explanation of learning, its relationship to innovation, and their joint effect on early internationalization. We theorize that, driven by the founders’ international vision, early internationalizing firms employ a dual subsystem of dynamic capabilities: a market subsystem consisting of market-focused learning capability and marketing capability, and a socio-technical subsystem comprised of network learning capability and internally focused learning capability. We argue that innovation mediates the proposed relationship between the dynamic capability structure and early internationalization. We conduct case studies to develop the conceptual framework and test it in a field survey of early internationalizing firms from Australia and the United States. Our findings indicate a complex interplay of capabilities driving innovation and early internationalization. We provide theoretical and practical implications and offer insights for future research.

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The 21st century will see monumental change. Either the human race will use its knowledge and skills and change the way it interacts with the environment, or the environment will change the way it interacts with its inhabitants. In the first case, the focus of this book, we would see our sophisticated understanding in areas such as physics, chemistry, engineering, biology, planning, commerce, business and governance accumulated over the last 1,000 years brought to bear on the challenge of dramatically reducing our pressure on the environment. The second case however is the opposite scenario, involving the decline of the planet’s ecosystems until they reach thresholds where recovery is not possible, and following which we have no idea what happens. For instance, if we fail to respond to Sir Nicolas Stern’s call to meet appropriate stabilisation trajectories for greenhouse gas emissions, and we allow the average temperature of our planets surface to increase by 4-6 degrees Celsius, we will see staggering changes to our environment, including rapidly rising sea level, withering crops, diminishing water reserves, drought, cyclones, floods… allowing this to happen will be the failure of our species, and those that survive will have a deadly legacy. In this update to the 1997 International Best Seller, Factor Four, Ernst von Weizsäcker again leads a team to present a compelling case for sector wide advances that can deliver significant resource productivity improvements over the coming century. The purpose of this book is to inspire hope and to then inform meaningful action in the coming decades to respond to the greatest challenge our species has ever faced – that of living in harmony with our planet and its other inhabitants.

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We have applied X-ray and neutron small-angle scattering techniques (SAXS, SANS, and USANS) to study the interaction between fluids and porous media in the particular case of subcritical CO2 sorption in coal. These techniques are demonstrated to give unique, pore-size-specific insights into the kinetics of CO2 sorption in a wide range of coal pores (nano to meso) and to provide data that may be used to determine the density of the sorbed CO2. We observed densification of the adsorbed CO2 by a factor up to five compared to the free fluid at the same (p, T) conditions. Our results indicate that details of CO2 sorption into coal pores differ greatly between different coals and depend on the amount of mineral matter dispersed in the coal matrix: a purely organic matrix absorbs more CO2 per unit volume than one containing mineral matter, but mineral matter markedly accelerates the sorption kinetics. Small pores are filled preferentially by the invading CO2 fluid and the apparent diffusion coefficients have been estimated to vary in the range from 5 × 10-7 cm2/min to more than 10-4 cm2/min, depending on the CO2 pressure and location on the sample.

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This article deals with time-domain hydroelastic analysis of a marine structure. The convolution terms associated with fluid memory effects are replaced by an alternative state-space representation, the parameters of which are obtained by using realization theory. The mathematical model established is validated by comparison to experimental results of a very flexible barge. Two types of time-domain simulations are performed: dynamic response of the initially inert structure to incident regular waves and transient response of the structure after it is released from a displaced condition in still water. The accuracy and the efficiency of the simulations based on the state-space model representations are compared to those that integrate the convolutions.

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Mammographic density (MD) is a strong heritable risk factor for breast cancer, and may decrease with increasing parity. However, the biomolecular basis for MD-associated breast cancer remains unclear, and systemic hormonal effects on MD-associated risk is poorly understood. This study assessed the effect of murine peripartum states on high and low MD tissue maintained in a xenograft model of human MD. Method High and low MD human breast tissues were precisely sampled under radiographic guidance from prophylactic mastectomy specimens of women. The high and low MD tissues were maintained in separate vascularised biochambers in nulliparous or pregnant SCID mice for 4 weeks, or mice undergoing postpartum involution or lactation for three additional weeks. High and low MD biochamber material was harvested for histologic and radiographic comparisons during various murine peripartum states. High and low MD biochamber tissues in nulliparous mice were harvested at different timepoints for histologic and radiographic comparisons. Results High MD biochamber tissues had decreased stromal (p = 0.0027), increased adipose (p = 0.0003) and a trend to increased glandular tissue areas (p = 0.076) after murine postpartum involution. Stromal areas decreased (p = 0.042), while glandular (p = 0.001) and adipose areas (p = 0.009) increased in high MD biochamber tissues during lactation. A difference in radiographic density was observed in high (p = 0.0021) or low MD biochamber tissues (p = 0.004) between nulliparous, pregnant and involution groups. No differences in tissue composition were observed in high or low MD biochamber tissues maintained for different durations, although radiographic density increased over time. Conclusion High MD biochamber tissues had measurable histologic changes after postpartum involution or lactation. Alterations in radiographic density occurred in biochamber tissues between different peripartum states and over time. These findings demonstrate the dynamic nature of the human MD xenograft model, providing a platform for studying the biomolecular basis of MD-associated cancer risk. © 2013 Springer Science+Business Media New York.

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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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Epithelial-to-mesenchymal transition (EMT) processes endow epithelial cells with enhanced migratory/invasive properties and are therefore likely to contribute to tumor invasion and metastatic spread. Because of the difficulty in following EMT processes in human tumors, we have developed and characterized an animal model with transplantable human breast tumor cells (MDA-MB-468) uniquely showing spontaneous EMT events to occur. Using vimentin as a marker of EMT, heterogeneity was revealed in the primary MDA-MB-468 xenografts with vimentin-negative and vimentin-positive areas, as also observed on clinical human invasive breast tumor specimens. Reverse transcriptase-PCR after microdissection of these populations from the xenografts revealed EMT traits in the vimentin-positive zones characterized by enhanced 'mesenchymal gene' expression (Snail, Slug and fibroblast-specific protein-1) and diminished expression of epithelial molecules (E-cadherin, ZO-3 and JAM-A). Circulating tumor cells (CTCs) were detected in the blood as soon as 8 days after s.c. injection, and lung metastases developed in all animals injected as examined by in vivo imaging analyses and histology. High levels of vimentin RNA were detected in CTCs by reverse transcriptase-quantitative PCR as well as, to a lesser extent, Snail and Slug RNA. Von Willebrand Factor/vimentin double immunostainings further showed that tumor cells in vascular tumoral emboli all expressed vimentin. Tumoral emboli in the lungs also expressed vimentin whereas macrometastases displayed heterogenous vimentin expression, as seen in the primary xenografts. In conclusion, our data uniquely demonstrate in an in vivo context that EMT occurs in the primary tumors, and associates with an enhanced ability to intravasate and generate CTCs. They further suggest that mesenchymal-to-epithelial phenomena occur in secondary organs, facilitating the metastatic growth.

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A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

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Cleavage and polyadenylation factor (CPF) is a multi‐protein complex that functions in pre‐mRNA 3′‐end formation and in the RNA polymerase II (RNAP II) transcription cycle. Ydh1p/Cft2p is an essential component of CPF but its precise role in 3′‐end processing remained unclear. We found that mutations in YDH1 inhibited both the cleavage and the polyadenylation steps of the 3′‐end formation reaction in vitro. Recently, we demonstrated that an important function of CPF lies in the recognition of poly(A) site sequences and RNA binding analyses suggesting that Ydh1p/Cft2p interacts with the poly(A) site region. Here we show that mutant ydh1 strains are deficient in the recognition of the ACT1 cleavage site in vivo. The C‐terminal domain (CTD) of RNAP II plays a major role in coupling 3′‐end processing and transcription. We provide evidence that Ydh1p/Cft2p interacts with the CTD of RNAP II, several other subunits of CPF and with Pcf11p, a component of CF IA. We propose that Ydh1p/Cft2p contributes to the formation of important interaction surfaces that mediate the dynamic association of CPF with RNAP II, the recognition of poly(A) site sequences and the assembly of the polyadenylation machinery on the RNA substrate.

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Approximately half of prostate cancers (PCa) carry TMPRSS2-ERG translocations; however, the clinical impact of this genomic alteration remains enigmatic. Expression of v-ets erythroblastosis virus E26 oncogene like (avian) gene (ERG) promotes prostatic epithelial dysplasia in transgenic mice and acquisition of epithelial-to-mesenchymal transition (EMT) characteristics in human prostatic epithelial cells (PrECs). To explore whether ERG-induced EMT in PrECs was associated with therapeutically targetable transformation characteristics, we established stable populations of BPH-1, PNT1B and RWPE-1 immortalized human PrEC lines that constitutively express flag-tagged ERG3 (fERG). All fERG-expressing populations exhibited characteristics of in vitro and in vivo transformation. Microarray analysis revealed >2000 commonly dysregulated genes in the fERG-PrEC lines. Functional analysis revealed evidence that fERG cells underwent EMT and acquired invasive characteristics. The fERG-induced EMT transcript signature was exemplified by suppressed expression of E-cadherin and keratins 5, 8, 14 and 18; elevated expression of N-cadherin, N-cadherin 2 and vimentin, and of the EMT transcriptional regulators Snail, Zeb1 and Zeb2, and lymphoid enhancer-binding factor-1 (LEF-1). In BPH-1 and RWPE-1-fERG cells, fERG expression is correlated with increased expression of integrin-linked kinase (ILK) and its downstream effectors Snail and LEF-1. Interfering RNA suppression of ERG decreased expression of ILK, Snail and LEF-1, whereas small interfering RNA suppression of ILK did not alter fERG expression. Interfering RNA suppression of ERG or ILK impaired fERG-PrEC Matrigel invasion. Treating fERG-BPH-1 cells with the small molecule ILK inhibitor, QLT-0267, resulted in dose-dependent suppression of Snail and LEF-1 expression, Matrigel invasion and reversion of anchorage-independent growth. These results suggest that ILK is a therapeutically targetable mediator of ERG-induced EMT and transformation in PCa.