Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

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.

Production of human factor VIII-FL in 293T cells using the bicistronic MGMT(P140K)-retroviral vector

Hemophilia A is the most common X-linked bleeding disorder; it is caused by deficiency of coagulation factor VIII (FVIII). Replacement therapy with rFVIII produced from human cell line is a major goal for treating hemophilia patients. We prepared a full-length recombinant FVIII (FVIII-FL), using the pMFG-P140K retroviral vector. The IRES DNA fragment was cloned upstream to the P140K gene, providing a 9.34-kb bicistronic vector. FVIII-FL cDNA was then cloned upstream to IRES, resulting in a 16.6-kb construct. In parallel, an eGFP control vector was generated, resulting in a 10.1-kb construct. The 293T cells were transfected with these constructs, generating the 293T-FVIII-FL/P140K and 293T-eGFP/P140K cell lines. In 293T-FVIII-FL/P140K cells, FVIII and P140K mRNAs levels were 4,410 (+/- 931.7)- and 295,400 (+/- 75,769)-fold higher than in virgin cells. In 293T-eGFP/P140K cells, the eGFP and P140K mRNAs levels were 1,501,000 (+/- 493,700)- and 308,000 (+/- 139,300)-fold higher than in virgin cells. The amount of FVIII-FL was 0.2 IU/mL and 45 ng/mL FVIII cells or 4.4 IU/mu g protein. These data demonstrate the efficacy of the bicistronic retroviral vector expressing FVIII-FL and MGMT(P140K), showing that it could be used for producing the FVIII-FL protein in a human cell line.

STABLE PIECEWISE POLYNOMIAL VECTOR FIELDS

Let N = {y > 0} and S = {y < 0} be the semi-planes of R-2 having as common boundary the line D = {y = 0}. Let X and Y be polynomial vector fields defined in N and S, respectively, leading to a discontinuous piecewise polynomial vector field Z = (X, Y). This work pursues the stability and the transition analysis of solutions of Z between N and S, started by Filippov (1988) and Kozlova (1984) and reformulated by Sotomayor-Teixeira (1995) in terms of the regularization method. This method consists in analyzing a one parameter family of continuous vector fields Z(epsilon), defined by averaging X and Y. This family approaches Z when the parameter goes to zero. The results of Sotomayor-Teixeira and Sotomayor-Machado (2002) providing conditions on (X, Y) for the regularized vector fields to be structurally stable on planar compact connected regions are extended to discontinuous piecewise polynomial vector fields on R-2. Pertinent genericity results for vector fields satisfying the above stability conditions are also extended to the present case. A procedure for the study of discontinuous piecewise vector fields at infinity through a compactification is proposed here.

Combining meta-learning and search techniques to select parameters for support vector machines

Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that, on average, the proposed hybrid methods obtained lower error rates when compared to their components applied in isolation.

SK-HEP cells and lentiviral vector for production of human recombinant factor VIII

Hemophilia A is caused by a deficiency in coagulation factor VIII. Recombinant factor VIII can be used as an alternative although it is unavailable for most patients. Here, we describe the production of a human recombinant B-domain-deleted FVIII (rBDDFVIII) by the human cell line SK-HEP-1, modified by a lentiviral vector rBDDFVIII was produced by recombinant SK-HEP cells (rSK-HEP) at 1.5-2.1 IU/10(6) in 24 h. The recombinant factor had increased in vitro stability when compared to commercial pdFVIII. The functionality of rBDDFVIII was shown by its biological activity and by tail-clip challenge in hemophilia A mice. The rSK-HEP cells grew in a scalable system and produced active rBDDFVIII, indicating that this platform production can be optimized to meet the commercial production scale needs.

ENERGY AND VOLUME OF VECTOR FIELDS ON SPHERICAL DOMAINS

We present a "boundary version" for theorems about minimality of volume and energy functionals on a spherical domain of an odd-dimensional Euclidean sphere.

Present bounds on new neutral vector resonances from electroweak gauge boson pair production at the LHC

Several extensions of the standard model predict the existence of new neutral spin-1 resonances associated with the electroweak symmetry breaking sector. Using the data from ATLAS (with integrated luminosity of L = 1.02 fb(-1)) and CMS (with integrated luminosity of L = 1.55 fb(-1)) on the production of W+W- pairs through the process pp --> l(+)l(-)' is not an element of(T), we place model independent bounds on these new vector resonances masses, couplings, and widths. Our analyses show that the present data exclude new neutral vector resonances with masses up to 1-2.3 TeV depending on their couplings and widths. We also demonstrate how to extend our analysis framework to different models with a specific example.

Mosquitoes in degraded and preserved areas of the Atlantic Forest and potential for vector-borne disease risk in the municipality of Sao Paulo, Brazil

In order to assess the epidemiological potential of the Culicidae species in remaining areas of the Brazilian Atlantic Forest, specimens of this family were collected in wild and anthropic environments. A total of 9,403 adult mosquitoes was collected from May, 2009 to June, 2010. The most prevalent among species collected in the wild environment were Anopheles (Kerteszia) cruzii, the Melanoconion section of Culex (Melanoconion), and Aedes serratus, while the most common in the anthropic site were Coquillettidia chrysonotum/albifera, Culex (Culex) Coronator group, and An. (Ker.) cruzii. Mosquito richness was similar between environments, although the abundance of individuals from different species varied. When comparing diversity patterns between environments, anthropic sites exhibited higher richness and evenness, suggesting that environmental stress increased the number of favorable niches for culicids, promoting diversity. Increased abundance of opportunistic species in the anthropic environment enhances contact with culicids that transmit vector-borne diseases.

Effect of contact and systemic insecticides on the sharpshooter Bucephalogonia xanthophis (Hemiptera: cicadellidae), a vector of Xylella fastidiosa in citrus

The knockdown and toxic effects of insecticides of different chemical groups and modes of action registered for citrus in Brazil were investigated for effective control of Bucephalogonia xanthophis, a sharpshooter vector of Xylella fastidiosa in citrus. The active ingredients dimethoate (1.2 mL/1.2L), imidacloprid (0.24 mL/1.2L) and lambda-cyhalothrin (0.24 mL/1.2L), as well as a control (water), were sprayed onto branches of potted-citrus nursery trees to evaluate the effect of residual contact. The insects were confined on sprayed branches by using sleeve cages, in groups of 10 per branch (5 branches/treatment). Lambdacyhalothrin showed a knockdown effect on B. xanthophis (>70% mortality within 2 h of exposure), and the residues were effective for approximately one wk. Imidacloprid, lambdacyhalothrin and dimethoate suppressed the vector populations for up to 3 wk after application, when the insects were exposed to sprayed plants for at least 24 h. In another experiment, 2 neonicotinoid insecticides (thiamethoxam and imidacloprid) were applied by soil drench to potted nursery trees, in order to study their systemic effect, i.e., mortality by ingestion on sharpshooter adults. Thiamethoxam and imidacloprid effectively controlled the vectors at all concentrations tested, when the insects were exposed to treated plants for 24 h (>80% mortality) or 48 h (near 100% mortality). The knockdown effect of thiamethoxam and lambda-cyhalothrin might be particularly important to prevent vector transmission of X. fastidiosa in citrus groves.

Mapping the Energy Distribution of SERRS Hot Spots from Anti-Stokes to Stokes Intensity Ratios

The anomalies in the anti-Stokes to Stokes intensity ratios in single-molecule surface-enhanced resonance Raman scattering were investigated. Brilliant green and crystal violet dyes were the molecular probes, and the experiments were carried out on an electrochemically activated Ag surface. The results allowed new insights into the origin of these anomalies and led to a new method to confirm the single-molecule regime in surface-enhanced Raman scattering. Moreover, a methodology to estimate the distribution of resonance energies that contributed to the imbalance in the anti-Stokes to Stokes intensity ratios at the electromagnetic hot spots was proposed. This method allowed the local plasmonic resonance energies on the metallic surface to be spatially mapped.

Light vector meson production in pp collisions at root s=7 TeV ALICE Collaboration

The ALICE experiment has measured low-mass dimuon production in pp collisions at root s = 7 TeV in the dimuon rapidity region 2.5 < y < 4. The observed dimuon mass spectrum is described as a superposition of resonance decays (eta, rho, omega, eta', phi) into muons and semi-leptonic decays of charmed mesons. The measured production cross sections for omega and phi are sigma(omega)(1 < p(t) < 5 GeV/c. 2.5 < y < 4) = 5.28 +/- 0.54(stat) +/- 0.49(syst) mb and sigma(phi)(1 < p(t) < 5 GeV/c. 2.5 < y < 4) = 0.940 +/- 0.084(stat) +/- 0.076(syst) mb. The differential cross sections d(2)sigma/dy dp(t) are extracted as a function of p(t) for omega and phi. The ratio between the rho and omega cross section is obtained. Results for the phi are compared with other measurements at the same energy and with predictions by models. (C) 2012 CERN. Published by Elsevier B.V. All rights reserved.

Serial bone marrow transplantation reveals in vivo expression of the pCLPG retroviral vector

Abstract Background Gene therapy in the hematopoietic system remains promising, though certain aspects of vector design, such as transcriptional control elements, continue to be studied. Our group has developed a retroviral vector where transgene expression is controlled by p53 with the intention of harnessing the dynamic and inducible nature of this tumor suppressor and transcription factor. We present here a test of in vivo expression provided by the p53-responsive vector, pCLPG. For this, we used a model of serial transplantation of transduced bone marrow cells. Results We observed, by flow cytometry, that the eGFP transgene was expressed at higher levels when the pCLPG vector was used as compared to the parental pCL retrovirus, where expression is directed by the native MoMLV LTR. Expression from the pCLPG vector was longer lasting, but did decay along with each sequential transplant. The detection of eGFP-positive cells containing either vector was successful only in the bone marrow compartment and was not observed in peripheral blood, spleen or thymus. Conclusions These findings indicate that the p53-responsive pCLPG retrovirus did offer expression in vivo and at a level that surpassed the non-modified, parental pCL vector. Our results indicate that the pCLPG platform may provide some advantages when applied in the hematopoietic system.

Modeling gene expression regulatory networks with the sparse vector autoregressive model

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.

Stochastic lattice model describing a vector-borne disease

We employ the approach of stochastic dynamics to describe the dissemination of vector-borne diseases such as dengue, and we focus our attention on the characterization of the threshold of the epidemic. The coexistence space comprises two representative spatial structures for both human and mosquito populations. The human population has its evolution described by a process that is similar to the Susceptible-Infected-Recovered (SIR) dynamics. The population of mosquitoes follows a dynamic of the type of the Susceptible Infected-Susceptible (SIS) model. The coexistence space is a bipartite lattice constituted by two structures representing the human and mosquito populations. We develop a truncation scheme to solve the evolution equations for the densities and the two-site correlations from which we get the threshold of the disease and the reproductive ratio. We present a precise deØnition of the reproductive ratio which reveals the importance of the correlations developed in the early stage of the disease. According to our deØnition, the reproductive rate is directed related to the conditional probability of the occurrence of a susceptible human (mosquito) given the presence in the neighborhood of an infected mosquito (human). The threshold of the epidemic as well as the phase transition between the epidemic and the non-epidemic states are also obtained by performing Monte Carlo simulations. References: [1] David R. de Souza, T^ania Tom∂e, , Suani R. T. Pinho, Florisneide R. Barreto and M∂ario J. de Oliveira, Phys. Rev. E 87, 012709 (2013). [2] D. R. de Souza, T. Tom∂e and R. M. ZiÆ, J. Stat. Mech. P03006 (2011).

Natural blood feeding and temperature shift modulate the global transcriptional profile of Rickettsia rickettsii infecting its tick vector

Rickettsia rickettsii is an obligate intracellular tick-borne bacterium that causes Rocky Mountain Spotted Fever (RMSF), the most lethal spotted fever rickettsiosis. When an infected starving tick begins blood feeding from a vertebrate host, R. rickettsii is exposed to a temperature elevation and to components in the blood meal. These two environmental stimuli have been previously associated with the reactivation of rickettsial virulence in ticks, but the factors responsible for this phenotype conversion have not been completely elucidated. Using customized oligonucleotide microarrays and high-throughput microfluidic qRT-PCR, we analyzed the effects of a 10 degrees C temperature elevation and of a blood meal on the transcriptional profile of R. rickettsii infecting the tick Amblyomma aureolatum. This is the first study of the transcriptome of a bacterium in the genus Rickettsia infecting a natural tick vector. Although both stimuli significantly increased bacterial load, blood feeding had a greater effect, modulating five-fold more genes than the temperature upshift. Certain components of the Type IV Secretion System (T4SS) were up-regulated by blood feeding. This suggests that this important bacterial transport system may be utilized to secrete effectors during the tick vector's blood meal. Blood feeding also up-regulated the expression of antioxidant enzymes, which might correspond to an attempt by R. rickettsii to protect itself against the deleterious effects of free radicals produced by fed ticks. The modulated genes identified in this study, including those encoding hypothetical proteins, require further functional analysis and may have potential as future targets for vaccine development.