41 resultados para Random Coefficient Autoregressive Model{ RCAR (1)}


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Abstract Background To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems. Results We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets. Conclusion The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any a priori information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.

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One of the greatest challenges in urological oncology is renal cell carcinoma (RCC), which is the third leading cause of death in genitourinary cancers. RCCs are highly vascularized and respond positively to antiangiogenic therapy. Endostatin (ES) is a fragment of collagen XVIII that possesses antiangiogenic activity. In this study, we examined the potential of ES-based antiangiogenic therapy to activate tumor-associated endothelial cells in metastatic RCC (mRCC). Balb/c-bearing Renca cells were treated with NIH/3T3-LendSN or, as a control, with NIH/3T3-LXSN cells. The T-cell subsets and lymphocyte populations of tumors, mediastinal lymph nodes and the spleen were assessed by flow cytometry. The expression of intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) was assessed by real-time PCR, flow cytometry and immunohistochemistry analysis. ES gene therapy led to an increase in the percentage of infiltrating CD4-interferon (IFN)-gamma cells (P<0.05), CD8-IFN-gamma cells (P<0.01) and CD49b-tumor necrosis factor-alpha cells (P<0.01). In addition, ES therapy caused an increase at the mRNA level of ICAM-1 (1.4-fold; P<0.01) and VCAM-1 (1.5-fold) (control vs treated group; P<0.001). Through flow cytometry, we found a significant increase in the CD34/ICAM-1 cells (8.1-fold; P<0.001) and CD34/VCAM-1 cells (1.6-fold; P<0.05). ES gene therapy induced a significant increase in both T CD4 and CD8 cells in the lymph nodes and the spleen, suggesting that ES therapy may facilitate cell survival or clonal expansion. CD49b cells were also present in increased quantities in all of these organs. In this study, we demonstrate an antitumor inflammatory effect of ES in an mRCC model, and this effect is mediated by an increase in ICAM-1 and VCAM-1 expression in tumor-associated endothelial cells.

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Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

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In this paper, we propose a random intercept Poisson model in which the random effect is assumed to follow a generalized log-gamma (GLG) distribution. This random effect accommodates (or captures) the overdispersion in the counts and induces within-cluster correlation. We derive the first two moments for the marginal distribution as well as the intraclass correlation. Even though numerical integration methods are, in general, required for deriving the marginal models, we obtain the multivariate negative binomial model from a particular parameter setting of the hierarchical model. An iterative process is derived for obtaining the maximum likelihood estimates for the parameters in the multivariate negative binomial model. Residual analysis is proposed and two applications with real data are given for illustration. (C) 2011 Elsevier B.V. All rights reserved.

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The present paper has two goals. First to present a natural example of a new class of random fields which are the variable neighborhood random fields. The example we consider is a partially observed nearest neighbor binary Markov random field. The second goal is to establish sufficient conditions ensuring that the variable neighborhoods are almost surely finite. We discuss the relationship between the almost sure finiteness of the interaction neighborhoods and the presence/absence of phase transition of the underlying Markov random field. In the case where the underlying random field has no phase transition we show that the finiteness of neighborhoods depends on a specific relation between the noise level and the minimum values of the one-point specification of the Markov random field. The case in which there is phase transition is addressed in the frame of the ferromagnetic Ising model. We prove that the existence of infinite interaction neighborhoods depends on the phase.

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We construct harmonic functions on random graphs given by Delaunay triangulations of ergodic point processes as the limit of the zero-temperature harness process. (C) 2012 Elsevier B.V All rights reserved.

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Background and Study Aim: The grip strength endurance is important for Brazilian Jiu-Jitsu (BJJ). Thus, the aims of this study were: a) to test the reliability of two kimono grip strength tests named maximum static lift (MSL) and maximum number of repetitions (MNR) and b) to examine differences between elite and non-elite BJJ players in these tests. Material/Methods: Thirty BJJ players participated into two phases: "A" to test reliability and "B" to compare elite and non-elite. In phase A, twenty participants performed the MSL and, 15 min later, the MNR in two occasions with 24-h interval. In phase B, ten other BJJ practitioners (non-elite) and ten athletes (elite) performed the same tests. The intraclass correlation coefficient (ICC) two way fixed model (3,1), Bland-Altman plot and the limits of agreement were used to test reliability, correlation between the tests were evaluated by Pearson correlations and independent T test (P<0.05) was utilized to compare elite vs. non-elite. Results: The ICC was high for repeated measurements on different days of phase A (MSL: r=0.99 and MNR: r=0.97). Limits of agreement for time of suspension were -6.9 to 2.4-s, with a mean difference of -2.3 s (CI: -3.3 to -1.2-s), while for number of repetitions the limits of agreement were -2.9 to 2.3-rep, with a mean difference of -0.3-rep (CI: -0.9 to 0.3-rep). In phase B, elite presented better performance for both tests (P<0.05) compared to non-elite (56 +/- 10-s vs. 37 +/- 11-s in MSL and 15 +/- 4-rep vs. 8 +/- 3-rep in MNR). Moderate correlation were found between MSL and MNR for absolute values during test (r=0.475; p=0.034), and retest phases (r=0.489; p=0.029), while moderate and high correlations in the test (r=0.615; p=0.004) and retest phases (r=0.716; p=0.001) were found for relative values, respectively. Conclusions: These proposed tests are reliable and both static and dynamic grip strength endurance tests seem to differentiate BJJ athletes from different levels.

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The partitioning of Clavulanic Acid (CA) in a novel inexpensive and stable aqueous two-phase system (ATPS) composed by poly(ethylene glycol) (PEG) and sodium polyacrylate (NaPA) has been studied. The aqueous two-phase systems are formed by mixing both polymers with a salt (NaCl or Na2SO4) and an aqueous solution of CA. The stability of CA on the presence of both polymers was investigated and it was observed that these polymers do not degrade the biomolecule. The effect of PEG-molecular size, polymer concentrations on the commercial CA partitioning has been studied, at 25 degrees C. The data showed that commercial CA was preferentially partitioned for the PEG-rich phase with a partition coefficient (K-CA) between 1 and 12 in the PEG/NaPA aqueous two phase systems supplemented with NaCl and Na2SO4. The partition to the PEG phase was increased in the systems with high polymer concentrations. Furthermore, Na2SO4 caused higher CA preference for the PEG-phase than NaCl. The systems having a composition with 10 wt.% of PEG4000, 20 wt.% of NaPA8000 and 6 wt.% of Na2SO4 were selected as the optimal ones in terms of recovery of CA from fermented broth of Streptomyces clavuligerus. The partitioning results (K-CA = 9.15 +/- 1.06) are competitive with commercial extraction methods of CA (K-CA = 11.91 +/- 2.08) which emphasizes that the system PEG/NaPA/Na2SO4 can be used as a new process to CA purification/concentration from fermented broth. (C) 2012 Elsevier B.V. All rights reserved.

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OBJECTIVE To investigate the relationship between multiple cryoprobes was investigated to determine whether they work in an additive or synergistic fashion in an in vivo animal model because 1.47 mm (17-gauge) cryoprobes have been introduced to the armamentarium for renal cryotherapy. METHODS Laparoscopic-guided percutaneous cryoablation was performed in both renal poles of 3 pigs using 3 IceRod cryoprobes. These 12 cryolesions were compared with 12 cryolesions using a single IceRod cryoprobe. Each cycle consisted of two 10-minute freeze cycles separated by a 5-minute thaw. The iceball volume was measured using intraoperative ultrasonography. The kidneys were harvested, and cryolesion surface area was calculated. The lesions were fixed and excised to obtain a volume measurement. Statistical analysis was used to compare the single probe results multiplied by 3 to the multiple probe group for iceball volume, cryolesion surface area, and cryolesion volume. RESULTS The iceball volume for the first freeze cycle for the single cryoprobe multiplied by 3 was 8.55 cm(3) compared with 9.79 cm(3) for the multiple cryoprobe group (P = .44) and 10.01 cm(3) versus 16.58 cm(3) for the second freeze (P = .03). The cryolesion volume for the single cryoprobe multiplied by 3 was 11.29 cm(3) versus 14.75 cm(3) for the multiple cyroprobe group (P = .06). The gross cryolesion surface area for the single cryoprobe multiplied by 3 was 13.14 cm(2) versus 13.89 cm(2) for the multiple probe group (P = .52). CONCLUSION The cryolesion created by 3 simultaneously activated 1.47-mm probes appears to be larger than that of an additive effect. The lesions were significantly larger as measured by ultrasonography and nearly so (P = .06) as measured by the gross cryolesion volume. UROLOGY 79: 484.e1-484.e6, 2012. (c) 2012 Elsevier Inc. All rights reserved.

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Local anesthetic efficacy of tramadol has been reported following intradermal application. Our aim was to investigate the effect of perineural tramadol as the sole analgesic in two pain models. Male Wistar rats (280-380 g; N = 5/group) were used in these experiments. A neurostimulation-guided sciatic nerve block was performed and 2% lidocaine or tramadol (1.25 and 5 mg) was perineurally injected in two different animal pain models. In the flinching behavior test, the number of flinches was evaluated and in the plantar incision model, mechanical and heat thresholds were measured. Motor effects of lidocaine and tramadol were quantified and a motor block score elaborated. Tramadol, 1.25 mg, completely blocked the first and reduced the second phase of the flinching behavior test. In the plantar incision model, tramadol (1.25 mg) increased both paw withdrawal latency in response to radiant heat (8.3 +/- 1.1, 12.7 +/- 1.8, 8.4 +/- 0.8, and 11.1 +/- 3.3 s) and mechanical threshold in response to von Frey filaments (459 +/- 82.8, 447.5 +/- 91.7, 320.1 +/- 120, 126.43 +/- 92.8 mN) at 5, 15, 30, and 60 min, respectively. Sham block or contralateral sciatic nerve block did not differ from perineural saline injection throughout the study in either model. The effect of tramadol was not antagonized by intraperitoneal naloxone. High dose tramadol (5 mg) blocked motor function as well as 2% lidocaine. In conclusion, tramadol blocks nociception and motor function in vivo similar to local anesthetics.

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In this paper we discuss some ideas on how to define the concept of quasi-integrability. Our ideas stem from the observation that many field theory models are "almost" integrable; i.e. they possess a large number of "almost" conserved quantities. Most of our discussion will involve a certain class of models which generalize the sine-Gordon model in (1 + 1) dimensions. As will be mentioned many field configurations of these models look like those of the integrable systems and so appear to be close to those in integrable model. We will then attempt to quantify these claims looking in particular, both analytically and numerically, at field configurations with scattering solitons. We will also discuss some preliminary results obtained in other models.

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The composition and seasonal variation of brachyuran and anomuran species associated with mussel farms were evaluated at Praia da Cocanha, Sao Paulo between May 2007 and February 2008. Nine mussel ropes were sampled at random in each quarter, and 1,208 organisms were identified, comprising five families and 28 species. The most numerous species was the porcellanid Pachycheles laevidactylus (18.5%), followed by the xanthids Acantholobulus schmitti (16.6%), Hexapanopeus paulensis (11.3%), Panopeus americanus (10.2%), and Menippe nodifrons (8.4%). The exotic crab Charybdis hellerii was recorded throughout the study period. The ecological descriptors, except Pielou evenness index, varied significantly over the time. The highest abundance and diversity of the species were recorded during November and February. This pattern was reversed for Berger-Parker dominance, with the lowest values recorded in February. The development of epifauna was correlated with the different stages of the mussel farms, since the mean size of mussels and consequently the abundance of epibiotic organisms and the structural complexity on the mussel ropes increased from May (seeding) until February (harvest). Despite this, the temporal population variations in recruitment patterns of the different epibionts should not be overlooked. The results indicated that the mussel farms provided favorable conditions for the development of these crustacean groups, which could be used in environmental monitoring programs and / or be exploited for the aquarium trade.

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The composition and seasonal variation of brachyuran and anomuran species associated with mussel farms were evaluated at Praia da Cocanha, São Paulo between May 2007 and February 2008. Nine mussel ropes were sampled at random in each quarter, and 1,208 organisms were identified, comprising five families and 28 species. The most numerous species was the porcellanid Pachycheles laevidactylus (18.5%), followed by the xanthids Acantholobulus schmitti (16.6%), Hexapanopeus paulensis (11.3%), Panopeus americanus (10.2%), and Menippe nodifrons (8.4%). The exotic crab Charybdis hellerii was recorded throughout the study period. The ecological descriptors, except Pielou evenness index, varied significantly over the time. The highest abundance and diversity of the species were recorded during November and February. This pattern was reversed for Berger-Parker dominance, with the lowest values recorded in February. The development of epifauna was correlated with the different stages of the mussel farms, since the mean size of mussels and consequently the abundance of epibiotic organisms and the structural complexity on the mussel ropes increased from May (seeding) until February (harvest). Despite this, the temporal population variations in recruitment patterns of the different epibionts should not be overlooked. The results indicated that the mussel farms provided favorable conditions for the development of these crustacean groups, which could be used in environmental monitoring programs and / or be exploited for the aquarium trade.

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A non-Markovian one-dimensional random walk model is studied with emphasis on the phase-diagram, showing all the diffusion regimes, along with the exactly determined critical lines. The model, known as the Alzheimer walk, is endowed with memory-controlled diffusion, responsible for the model's long-range correlations, and is characterized by a rich variety of diffusive regimes. The importance of this model is that superdiffusion arises due not to memory per se, but rather also due to loss of memory. The recently reported numerically and analytically estimated values for the Hurst exponent are hereby reviewed. We report the finding of two, previously overlooked, phases, namely, evanescent log-periodic diffusion and log-periodic diffusion with escape, both with Hurst exponent H = 1/2. In the former, the log-periodicity gets damped, whereas in the latter the first moment diverges. These phases further enrich the already intricate phase diagram. The results are discussed in the context of phase transitions, aging phenomena, and symmetry breaking.

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The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.