990 resultados para predictive modeling
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We investigate the dynamic and asymmetric dependence structure between equity portfolios from the US and UK. We demonstrate the statistical significance of dynamic asymmetric copula models in modelling and forecasting market risk. First, we construct “high-minus-low" equity portfolios sorted on beta, coskewness, and cokurtosis. We find substantial evidence of dynamic and asymmetric dependence between characteristic-sorted portfolios. Second, we consider a dynamic asymmetric copula model by combining the generalized hyperbolic skewed t copula with the generalized autoregressive score (GAS) model to capture both the multivariate non-normality and the dynamic and asymmetric dependence between equity portfolios. We demonstrate its usefulness by evaluating the forecasting performance of Value-at-Risk and Expected Shortfall for the high-minus-low portfolios. From back-testing, e find consistent and robust evidence that our dynamic asymmetric copula model provides the most accurate forecasts, indicating the importance of incorporating the dynamic and asymmetric dependence structure in risk management.
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PECUBE is a three-dimensional thermal-kinematic code capable of solving the heat production-diffusion-advection equation under a temporally varying surface boundary condition. It was initially developed to assess the effects of time-varying surface topography (relief) on low-temperature thermochronological datasets. Thermochronometric ages are predicted by tracking the time-temperature histories of rock-particles ending up at the surface and by combining these with various age-prediction models. In the decade since its inception, the PECUBE code has been under continuous development as its use became wider and addressed different tectonic-geomorphic problems. This paper describes several major recent improvements in the code, including its integration with an inverse-modeling package based on the Neighborhood Algorithm, the incorporation of fault-controlled kinematics, several different ways to address topographic and drainage change through time, the ability to predict subsurface (tunnel or borehole) data, prediction of detrital thermochronology data and a method to compare these with observations, and the coupling with landscape-evolution (or surface-process) models. Each new development is described together with one or several applications, so that the reader and potential user can clearly assess and make use of the capabilities of PECUBE. We end with describing some developments that are currently underway or should take place in the foreseeable future. (C) 2012 Elsevier B.V. All rights reserved.
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This paper discuses current strategies for the development of AIDS vaccines wich allow immunzation to disturb the natural course of HIV at different detailed stages of its life cycle. Mathematical models describing the main biological phenomena (i.e. virus and vaccine induced T4 cell growth; virus and vaccine induced activation latently infected T4 cells; incremental changes immune response as infection progress; antibody dependent enhancement and neutralization of infection) and allowing for different vaccination strategies serve as a backgroud for computer simulations. The mathematical models reproduce updated information on the behavior of immune cells, antibody concentrations and free viruses. The results point to some controversial outcomes of an AIDS vaccine such as an early increase in virus concentration among vaccinated when compared to nonvaccinated individuals.
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Computational modeling has become a widely used tool for unraveling the mechanisms of higher level cooperative cell behavior during vascular morphogenesis. However, experimenting with published simulation models or adding new assumptions to those models can be daunting for novice and even for experienced computational scientists. Here, we present a step-by-step, practical tutorial for building cell-based simulations of vascular morphogenesis using the Tissue Simulation Toolkit (TST). The TST is a freely available, open-source C++ library for developing simulations with the two-dimensional cellular Potts model, a stochastic, agent-based framework to simulate collective cell behavior. We will show the basic use of the TST to simulate and experiment with published simulations of vascular network formation. Then, we will present step-by-step instructions and explanations for building a recent simulation model of tumor angiogenesis. Demonstrated mechanisms include cell-cell adhesion, chemotaxis, cell elongation, haptotaxis, and haptokinesis.
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BACKGROUND: For over 50 years, radiocephalic wrist arteriovenous fistulae (RCAVF) have been the primary and best vascular access for haemodialysis. Nevertheless, early failure due to thrombosis or non-maturation is a major complication resulting in their abandonment. This prospective study was designed to investigate the predictive value of intra-operative blood flow on early failure of primary RCAVF before the first effective dialysis. METHODS: We enrolled patients undergoing creation of primary RCAVF for haemodialysis based on the pre-operative ultrasound vascular mapping discussed in a multidisciplinary approach. Intra-operative blood flow measurement was systematically performed once the anastomosis had been completed using a transit-time ultrasonic flowmeter. During the follow-up, blood flow was estimated by colour flow ultrasound at various intervals. Any events related to the RCAVF were recorded. RESULTS: Autogenous RCAVFs (n = 58) in 58 patients were constructed and followed up for an average of 30 days. Thrombosis and non-maturation occurred in eight (14%) and four (7%) patients, respectively. The intra-operative blood flow in functioning RCAVFs was significantly higher compared to non-functioning RCAVFs (230 vs 98 mL/min; P = 0.007), as well as 1 week (753 vs 228 mL/min; P = 0.0008) and 4 weeks (915 vs 245 mL/min, P < 0.0001) later. Blood flow volume measurements with a cut-off value of 120 mL/min had a sensitivity of 67%, specificity of 75% and positive predictive value of 91%. CONCLUSIONS: Blood flow <120 mL has a good predictive value for early failure in RCAVF. During the procedure, this cut-off value may be used to select appropriately which RCAVF should be investigated in the operation theatre in order to correct in real time any abnormality.
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Background: There is currently no identified marker predicting benefit from Bev in patients with breast cancer (pts). We monitored prospectively 6 angiogenesis-related factors in the blood of advanced stage pts treated with a combination of Bev and PLD in a phase II trial of the Swiss Group for Clinical Cancer Research, SAKK.Methods: Pts received PLD (20 mg/m2) and Bev (10 mg/kg) every 2 weeks for a maximum of 12 administrations, followed by Bev monotherapy until progression or severe toxicity. Blood samples were collected at baseline, during treatment and at treatment discontinuation. Enzyme-linked immunosorbent assays (Quantikine, R&DSystems and Reliatech) were used to measure vascular endothelial growth factor (VEGF), placental growth factor (PlGF), matrix metalloproteinase 9 (MMP-9) and soluble VEGF receptors -1, -2 and -3. The natural log-transformed (ln) data for each factor was analyzed by analysis of variance (ANOVA) model to investigate differences between the mean values of the subgroups of interest (where a = 0.05), based on the best tumor response by RECIST.Results: 132 samples were collected in 41 pts. The mean of baseline ln MMP-9 levels was significantly lower in pts with tumor progression than those with tumor response (p=0.0202, log fold change=0.8786) or disease control (p=0.0035, log fold change=0.8427). Higher MMP-9 level was a significant predictor of superior progression free survival (PFS): p=0.0417, hazard ratio=0.574, 95% CI=0.336-0.979. In a multivariate cox proportional hazards model, containing performance status, disease free interval, number of tumor sites, visceral involvement and prior adjuvant chemotherapy, using stepwise regression baseline MMP-9 was still a statistically 117P Table 1. SOLTI-0701* AC01B07* NU07B1* SOR+CAP N=20 PL+CAP N=33 SOR+ GEM/CAP N=23 PL+ GEM/CAP N=27 SOR+PAC N=48 PL+PAC N=46 Baseline characteristics Age, median (range), y 49 (32-72) 53 (30-78 54 (32-69) 57 (31-82) 50 (27-80) 52 (23-74) AJCC stage, n (%) IIIB/IIIC 3 (15) 6 (18) 0 (0) 3 (11) 8 (17) 9 (20) IV 17 (85) 27 (82) 23 (100) 24 (89) 40 (83) 37 (80) Metastatic site, n (%) Non-visceral 3 (15) 6 (18) 7 (30) 6 (22) 9 (19) 17 (37) Visceral 17 (85) 27 (82) 16 (70) 21 (78) 39 (81) 29 (63) Prior metastatic chemo, n (%) 8 (40) 15 (45) 21 (91) 25 (93) - - Efficacy PFS, median, mo 4.3 2.5 3.1 2.6 5.6 5.5 HR (95% CI)_ 0.60 (0.31, 1.14) 0.57 (0.30, 1.09) 0.86 (0.50, 1.45) 1-sided P value_ 0.055 0.044 0.281 Overall survival, median, mo 17.5 16.1 Pending 14.7 18.2 HR (95% CI)_ 0.98 (0.50, 1.89) 1.11 (0.64, 1.94) 1-sided P value_ 0.476 0.352 Safety N=20 N=33 N=22 N=27 N=46 N=46 Tx-emergent Grade 3/4, n (%) 15 (75) 16 (48) 20 (91) 17 (63) 36 (78) 16 (35) Grade 3§ hand-foot skin reaction/ syndrome 8 (40) 5 (15) 8 (36) 0 (0) 14 (30) 2 (4) *Efficacy results based on intent-to-treat population and safety results based on safety population (pts who received study drug[s]); _Cox regression within each subgroup; _log-rank test within each subgroup; §maximum toxicity grade for hand-foot skin reaction/syndrome; AJCC, American Joint Committee on Cancer mittedabstractsª The Author 2011. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com Downloaded from annonc.oxfordjournals.org at Bibliotheque Cantonale et Universitaire on June 6, 2011 significant factor (p=0.0266). The results of the other measured factors were presented elsewhere.Conclusions: Higher levels of MMP-9 could predict tumor response and superior PFSin pts treated with a combination of Bev and PLD. These exploratory results justify further investigations of MMP-9 in pts treated with Bev combinations in order to assess its role as a prognostic and predictive factor.Disclosure: K. Zaman: Participation in advisory board of Roche; partial sponsoring ofthe study by Roche (the main sponsor was the Swiss Federation against Cancer (Oncosuisse)). B. Thu¨rlimann: stock of Roche; Research grants from Roche. R. vonMoos: Participant of Advisory Board and Speaker honoraria
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The Keller-Segel system has been widely proposed as a model for bacterial waves driven by chemotactic processes. Current experiments on E. coli have shown precise structure of traveling pulses. We present here an alternative mathematical description of traveling pulses at a macroscopic scale. This modeling task is complemented with numerical simulations in accordance with the experimental observations. Our model is derived from an accurate kinetic description of the mesoscopic run-and-tumble process performed by bacteria. This model can account for recent experimental observations with E. coli. Qualitative agreements include the asymmetry of the pulse and transition in the collective behaviour (clustered motion versus dispersion). In addition we can capture quantitatively the main characteristics of the pulse such as the speed and the relative size of tails. This work opens several experimental and theoretical perspectives. Coefficients at the macroscopic level are derived from considerations at the cellular scale. For instance the stiffness of the signal integration process turns out to have a strong effect on collective motion. Furthermore the bottom-up scaling allows to perform preliminary mathematical analysis and write efficient numerical schemes. This model is intended as a predictive tool for the investigation of bacterial collective motion.
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The benefit of bevacizumab (Bv) has been shown in different tumors including colorectal cancer, renal cancer, pulmonary non-small cell cancer and also breast cancer. However to date, there is no established test evaluating the angiogenic status of a patient and monitoring the effects of anti-angiogenic treatments. Tumor angiogenesis is the result of a balance between multiple pro- and anti¬angiogenic molecules. There is very little published clinical data exploring the impact of the anti-angiogenic therapy on the different angiogenesis-related molecules and the potential role of these molecules as prognostic or predictive factors.
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The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.
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AbstractBACKGROUND: KRAB-ZFPs (Krüppel-associated box domain-zinc finger proteins) are vertebrate-restricted transcriptional repressors encoded in the hundreds by the mouse and human genomes. They act via an essential cofactor, KAP1, which recruits effectors responsible for the formation of facultative heterochromatin. We have recently shown that KRAB/KAP1 can mediate long-range transcriptional repression through heterochromatin spreading, but also demonstrated that this process is at times countered by endogenous influences.METHOD: To investigate this issue further we used an ectopic KRAB-based repressor. This system allowed us to tether KRAB/KAP1 to hundreds of euchromatic sites within genes, and to record its impact on gene expression. We then correlated this KRAB/KAP1-mediated transcriptional effect to pre-existing genomic and chromatin structures to identify specific characteristics making a gene susceptible to repression.RESULTS: We found that genes that were susceptible to KRAB/KAP1-mediated silencing carried higher levels of repressive histone marks both at the promoter and over the transcribed region than genes that were insensitive. In parallel, we found a high enrichment in euchromatic marks within both the close and more distant environment of these genes.CONCLUSION: Together, these data indicate that high levels of gene activity in the genomic environment and the pre-deposition of repressive histone marks within a gene increase its susceptibility to KRAB/KAP1-mediated repression.
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Current parallel applications running on clusters require the use of an interconnection network to perform communications among all computing nodes available. Imbalance of communications can produce network congestion, reducing throughput and increasing latency, degrading the overall system performance. On the other hand, parallel applications running on these networks posses representative stages which allow their characterization, as well as repetitive behavior that can be identified on the basis of this characterization. This work presents the Predictive and Distributed Routing Balancing (PR-DRB), a new method developed to gradually control network congestion, based on paths expansion, traffic distribution and effective traffic load, in order to maintain low latency values. PR-DRB monitors messages latencies on intermediate routers, makes decisions about alternative paths and record communication pattern information encountered during congestion situation. Based on the concept of applications repetitiveness, best solution recorded are reapplied when saved communication pattern re-appears. Traffic congestion experiments were conducted in order to evaluate the performance of the method, and improvements were observed.