Amazonian malaria: Asymptomatic human reservoirs, diagnostic challenges, environmentally driven changes in mosquito vector populations, and the mandate for sustainable control strategies

Across the Americas and the Caribbean, nearly 561,000 slide-confirmed malaria infections were reported officially in 2008. The nine Amazonian countries accounted for 89% of these infections; Brazil and Peru alone contributed 56% and 7% of them, respectively. Local populations of the relatively neglected parasite Plasmodium vivax, which currently accounts for 77% of the regional malaria burden, are extremely diverse genetically and geographically structured. At a time when malaria elimination is placed on the public health agenda of several endemic countries, it remains unclear why malaria proved so difficult to control in areas of relatively low levels of transmission such as the Amazon Basin. We hypothesize that asymptomatic parasite carriage and massive environmental changes that affect vector abundance and behavior are major contributors to malaria transmission in epidemiologically diverse areas across the Amazon Basin. Here we review available data supporting this hypothesis and discuss their implications for current and future malaria intervention policies in the region. Given that locally generated scientific evidence is urgently required to support malaria control interventions in Amazonia, we briefly describe the aims of our current field-oriented malaria research in rural villages and gold-mining enclaves in Peru and a recently opened agricultural settlement in Brazil. (C) 2011 Elsevier B.V. All rights reserved.

Globally solvable systems of complex vector fields

We consider a class of involutive systems of n smooth vector fields on the n + 1 dimensional torus. We obtain a complete characterization for the global solvability of this class in terms of Liouville forms and of the connectedness of all sublevel and superlevel sets of the primitive of a certain 1-form in the minimal covering space.

Bioelectrical impedance vector analysis (BIVA) in stable preterm newborns

Objective: To observe the behavior of the plotted vectors on the RXc (R - resistance - and Xc - reactance corrected for body height/length) graph through bioelectrical impedance analysis (BIVA) and phase angle (PA) values in stable premature infants, considering the hypothesis that preterm infants present vector behavior on BIVA suggestive of less total body water and soft tissues, compared to reference data for term infants. Methods: Cross-sectional study, including preterm neonates of both genders, in-patients admitted to an intermediate care unit at a tertiary care hospital. Data on delivery, diet and bioelectrical impedance (800 mA, 50 kHz) were collected. The graphs and vector analysis were performed with the BIVA software. Results: A total of 108 preterm infants were studied, separated according to age (< 7 days and >= 7 days). Most of the premature babies were without the normal range (above the 95% tolerance intervals) existing in literature for term newborn infants and there was a tendency to dispersion of the points in the upper right quadrant, RXc plan. The PA was 4.92 degrees (+/- 2.18) for newborns < 7 days and 4.34 degrees (+/- 2.37) for newborns >= 7 days. Conclusion: Premature infants behave similarly in terms of BIVA and most of them have less absolute body water, presenting less fat free mass and fat mass in absolute values, compared to term newborn infants.

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.

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.

Evaluation of inadequate anti-retroviral treatment in patients with HIV/AIDS

Introduction: Since the emergence of antiretroviral therapy, the survival of patients infected with human immunodeficiency virus has increased. Non-adherence to this therapy is directly related to treatment failure, which allows the emergence of resistant viral strains. Methods: A retrospective descriptive study of the antiretroviral dispensing records of 229 patients from the Center for Health Care, University Hospital, Federal University of Juiz de Fora, Brazil, was conducted between January and December 2009. Results: The study aimed to evaluate patient compliance and determine if there was an association between non-adherence and the therapy. Among these patients, 63.8% were men with an average age of 44.0 +/- 9.9 years. The most used treatment was a combination of 2 nucleoside reverse transcriptase inhibitors with 1 non-nucleoside reverse transcriptase inhibitor (55.5%) or with 2 protease inhibitors (28.8%). It was found that patients taking lopinavir/ritonavir with zidovudine and lamivudine had a greater frequency of inadequate treatment than those taking atazanavir with zidovudine and lamivudine (85% and 83.3%, respectively). Moreover, when the combination of zidovudine/lamivudine was used, the patients were less compliant (chi(2) = 4.468, 1 degree of freedom, p = 0.035). Conclusions: The majority of patients failed to correctly adhere to their treatment; therefore, it is necessary to implement strategies that lead to improved compliance, thus ensuring therapeutic efficacy and increased patient survival.

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.

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.

Retroviral transfer of the p16INK4a cDNA inhibits C6 glioma formation in Wistar rats

Abstract Background The p16INK4A gene product halts cell proliferation by preventing phosphorylation of the Rb protein. The p16INK4a gene is often deleted in human glioblastoma multiforme, contributing to unchecked Rb phosphorylation and rapid cell division. We show here that transduction of the human p16INK4a cDNA using the pCL retroviral system is an efficient means of stopping the proliferation of the rat-derrived glioma cell line, C6, both in tissue culture and in an animal model. C6 cells were transduced with pCL retrovirus encoding the p16INK4a, p53, or Rb genes. These cells were analyzed by a colony formation assay. Expression of p16INK4a was confirmed by immunohistochemistry and Western blot analysis. The altered morphology of the p16-expressing cells was further characterized by the senescence-associated β-galactosidase assay. C6 cells infected ex vivo were implanted by stereotaxic injection in order to assess tumor formation. Results The p16INK4a gene arrested C6 cells more efficiently than either p53 or Rb. Continued studies with the p16INK4a gene revealed that a large portion of infected cells expressed the p16INK4a protein and the morphology of these cells was altered. The enlarged, flat, and bi-polar shape indicated a senescence-like state, confirmed by the senescence-associated β-galactosidase assay. The animal model revealed that cells infected with the pCLp16 virus did not form tumors. Conclusion Our results show that retrovirus mediated transfer of p16INK4a halts glioma formation in a rat model. These results corroborate the idea that retrovirus-mediated transfer of the p16INK4a gene may be an effective means to arrest human glioma and glioblastoma.

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.