Influence of children's oral health-related quality of life on school performance and school absenteeism

Objective: This study assessed the relation of child oral health-related quality of life with school performance and school absenteeism. Methods: We followed a cross-sectional design with a multistage random sample of 312 12-year-old schoolchildren living in Brazil. The participants completed the child perceptions questionnaire (CPQ1114) that provides information about psychological factors, while their parents or guardians answered questions on their socioeconomic status measured by parents' education level and household income. A dental examination of each child provided information on the prevalence of caries and dental trauma. Data on school performance, which included the results of baseline Brazilian language (Portuguese) tests, and school absenteeism (school days missed) were obtained from the school register. Multilevel linear regression was used to investigate the association among psychological and socioeconomic status and children's school performance. Results: In the multiple model, after adjusting for individual covariates, being a girl was associated with higher school performance (P < 0.05), whereas low household income (P < 0.05), higher mean of CPQ1114 (P < 0.05), and higher school days missed (P < 0.001) were identified as individual determinants of lower school performance. When the school-level covariates were included in the model, the association between subjects' level characteristics and school performance still persisted. Conclusion: Children's school performance and absence were influenced by psychological and socioeconomic conditions.

A mixed model QTL analysis for sugarcane multiple-harvest-location trial data

Sugarcane-breeding programs take at least 12 years to develop new commercial cultivars. Molecular markers offer a possibility to study the genetic architecture of quantitative traits in sugarcane, and they may be used in marker-assisted selection to speed up artificial selection. Although the performance of sugarcane progenies in breeding programs are commonly evaluated across a range of locations and harvest years, many of the QTL detection methods ignore two- and three-way interactions between QTL, harvest, and location. In this work, a strategy for QTL detection in multi-harvest-location trial data, based on interval mapping and mixed models, is proposed and applied to map QTL effects on a segregating progeny from a biparental cross of pre-commercial Brazilian cultivars, evaluated at two locations and three consecutive harvest years for cane yield (tonnes per hectare), sugar yield (tonnes per hectare), fiber percent, and sucrose content. In the mixed model, we have included appropriate (co)variance structures for modeling heterogeneity and correlation of genetic effects and non-genetic residual effects. Forty-six QTLs were found: 13 QTLs for cane yield, 14 for sugar yield, 11 for fiber percent, and 8 for sucrose content. In addition, QTL by harvest, QTL by location, and QTL by harvest by location interaction effects were significant for all evaluated traits (30 QTLs showed some interaction, and 16 none). Our results contribute to a better understanding of the genetic architecture of complex traits related to biomass production and sucrose content in sugarcane.

A multiple time scale survival model with a cure fraction

Many recent survival studies propose modeling data with a cure fraction, i.e., data in which part of the population is not susceptible to the event of interest. This event may occur more than once for the same individual (recurrent event). We then have a scenario of recurrent event data in the presence of a cure fraction, which may appear in various areas such as oncology, finance, industries, among others. This paper proposes a multiple time scale survival model to analyze recurrent events using a cure fraction. The objective is analyzing the efficiency of certain interventions so that the studied event will not happen again in terms of covariates and censoring. All estimates were obtained using a sampling-based approach, which allows information to be input beforehand with lower computational effort. Simulations were done based on a clinical scenario in order to observe some frequentist properties of the estimation procedure in the presence of small and moderate sample sizes. An application of a well-known set of real mammary tumor data is provided.

Multiple Intravenous Administrations of Human Umbilical Cord Blood Cells Benefit in a Mouse Model of ALS

Background: A promising therapeutic strategy for amyotrophic lateral sclerosis (ALS) is the use of cell-based therapies that can protect motor neurons and thereby retard disease progression. We recently showed that a single large dose (25x10(6) cells) of mononuclear cells from human umbilical cord blood (MNC hUCB) administered intravenously to pre-symptomatic G93A SOD1 mice is optimal in delaying disease progression and increasing lifespan. However, this single high cell dose is impractical for clinical use. The aim of the present pre-clinical translation study was therefore to evaluate the effects of multiple low dose systemic injections of MNC hUCB cell into G93A SOD1 mice at different disease stages. Methodology/Principal Findings: Mice received weekly intravenous injections of MNC hUCB or media. Symptomatic mice received 10(6) or 2.5x10(6) cells from 13 weeks of age. A third, pre-symptomatic, group received 10(6) cells from 9 weeks of age. Control groups were media-injected G93A and mice carrying the normal hSOD1 gene. Motor function tests and various assays determined cell effects. Administered cell distribution, motor neuron counts, and glial cell densities were analyzed in mouse spinal cords. Results showed that mice receiving 10(6) cells pre-symptomatically or 2.5x10(6) cells symptomatically significantly delayed functional deterioration, increased lifespan and had higher motor neuron counts than media mice. Astrocytes and microglia were significantly reduced in all cell-treated groups. Conclusions/Significance: These results demonstrate that multiple injections of MNC hUCB cells, even beginning at the symptomatic disease stage, could benefit disease outcomes by protecting motor neurons from inflammatory effectors. This multiple cell infusion approach may promote future clinical studies.

Efficient Kernel Computation for Volterra Filter Structure Evaluation

Despite their generality, conventional Volterra filters are inadequate for some applications, due to the huge number of parameters that may be needed for accurate modelling. When a state-space model of the target system is known, this can be assessed by computing its kernels, which also provides valuable information for choosing an adequate alternate Volterra filter structure, if necessary, and is useful for validating parameter estimation procedures. In this letter, we derive expressions for the kernels by using the Carleman bilinearization method, for which an efficient algorithm is given. Simulation results are presented, which confirm the usefulness of the proposed approach.

Linear matrix inequality-based robust model predictive control for time-delayed systems

This work addresses the solution to the problem of robust model predictive control (MPC) of systems with model uncertainty. The case of zone control of multi-variable stable systems with multiple time delays is considered. The usual approach of dealing with this kind of problem is through the inclusion of non-linear cost constraint in the control problem. The control action is then obtained at each sampling time as the solution to a non-linear programming (NLP) problem that for high-order systems can be computationally expensive. Here, the robust MPC problem is formulated as a linear matrix inequality problem that can be solved in real time with a fraction of the computer effort. The proposed approach is compared with the conventional robust MPC and tested through the simulation of a reactor system of the process industry.

Trends in aortic aneurysm- and dissection-related mortality in the state of Sao Paulo, Brazil, 1985-2009: multiple-cause-of-death analysis

Background: Aortic aneurysm and dissection are important causes of death in older people. Ruptured aneurysms show catastrophic fatality rates reaching near 80%. Few population-based mortality studies have been published in the world and none in Brazil. The objective of the present study was to use multiple-cause-of-death methodology in the analysis of mortality trends related to aortic aneurysm and dissection in the state of Sao Paulo, between 1985 and 2009. Methods: We analyzed mortality data from the Sao Paulo State Data Analysis System, selecting all death certificates on which aortic aneurysm and dissection were listed as a cause-of-death. The variables sex, age, season of the year, and underlying, associated or total mentions of causes of death were studied using standardized mortality rates, proportions and historical trends. Statistical analyses were performed by chi-square goodness-of-fit and H Kruskal-Wallis tests, and variance analysis. The joinpoint regression model was used to evaluate changes in age-standardized rates trends. A p value less than 0.05 was regarded as significant. Results: Over a 25-year period, there were 42,615 deaths related to aortic aneurysm and dissection, of which 36,088 (84.7%) were identified as underlying cause and 6,527 (15.3%) as an associated cause-of-death. Dissection and ruptured aneurysms were considered as an underlying cause of death in 93% of the deaths. For the entire period, a significant increased trend of age-standardized death rates was observed in men and women, while certain non-significant decreases occurred from 1996/2004 until 2009. Abdominal aortic aneurysms and aortic dissections prevailed among men and aortic dissections and aortic aneurysms of unspecified site among women. In 1985 and 2009 death rates ratios of men to women were respectively 2.86 and 2.19, corresponding to a difference decrease between rates of 23.4%. For aortic dissection, ruptured and non-ruptured aneurysms, the overall mean ages at death were, respectively, 63.2, 68.4 and 71.6 years; while, as the underlying cause, the main associated causes of death were as follows: hemorrhages (in 43.8%/40.5%/13.9%); hypertensive diseases (in 49.2%/22.43%/24.5%) and atherosclerosis (in 14.8%/25.5%/15.3%); and, as associated causes, their principal overall underlying causes of death were diseases of the circulatory (55.7%), and respiratory (13.8%) systems and neoplasms (7.8%). A significant seasonal variation, with highest frequency in winter, occurred in deaths identified as underlying cause for aortic dissection, ruptured and non-ruptured aneurysms. Conclusions: This study introduces the methodology of multiple-causes-of-death to enhance epidemiologic knowledge of aortic aneurysm and dissection in Sao Paulo, Brazil. The results presented confer light to the importance of mortality statistics and the need for epidemiologic studies to understand unique trends in our own population.

A comparative transcriptome analysis reveals expression profiles conserved across three Eimeria spp. of domestic fowl and associated with multiple developmental stages

Coccidiosis of the domestic fowl is a worldwide disease caused by seven species of protozoan parasites of the genus Eimeria. The genome of the model species, Eimeria tenella, presents a complexity of 55-60 MB distributed in 14 chromosomes. Relatively few studies have been undertaken to unravel the complexity of the transcriptome of Eimeria parasites. We report here the generation of more than 45,000 open reading frame expressed sequence tag (ORESTES) cDNA reads of E. tenella, Eimeria maxima and Eimeria acervulina, covering several developmental stages: unsporulated oocysts, sporoblastic oocysts, sporulated oocysts, sporozoites and second generation merozoites. All reads were assembled to constitute gene indices and submitted to a comprehensive functional annotation pipeline. In the case of E. tenella, we also incorporated publicly available ESTs to generate an integrated body of information. Orthology analyses have identified genes conserved across different apicomplexan parasites, as well as genes restricted to the genus Eimeria. Digital expression profiles obtained from ORESTES/EST countings, submitted to clustering analyses, revealed a high conservation pattern across the three Eimeria spp. Distance trees showed that unsporulated and sporoblastic oocysts constitute a distinct clade in all species, with sporulated oocysts forming a more external branch. This latter stage also shows a close relationship with sporozoites, whereas first and second generation merozoites are more closely related to each other than to sporozoites. The profiles were unambiguously associated with the distinct developmental stages and strongly correlated with the order of the stages in the parasite life cycle. Finally, we present The Eimeria Transcript Database (http://www.coccidia.icb.usp.br/eimeriatdb), a website that provides open access to all sequencing data, annotation and comparative analysis. We expect this repository to represent a useful resource to the Eimeria scientific community, helping to define potential candidates for the development of new strategies to control coccidiosis of the domestic fowl. (C) 2011 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Experimental Model of Arthritis Induced by Paracoccidioides brasiliensis in Rats

Paracoccidioidomycosis (PCM), a disease caused by the fungus Paracoccidioides brasiliensis (Pb), is highly prevalent in Brazil, where it is the principal cause of death by systemic mycoses. The disease primarily affects men aged 30-50 year old and usually starts as a pulmonary focus and then may spread to other organs and systems, including the joints. The present study aimed to develop an experimental model of paracoccidioidomycotic arthritis. Two-month-old male Wistar rats (n = 48) were used, divided in 6 groups: test groups EG/15 and EG/45 (received one dose of 100 mu l of saline containing 10(5) Pb viable yeasts in the knee); heat killed Pb-group HK/15 and HK/45 (received a suspension of 10(5) Pb nonviable yeasts in the knee) and control groups CG/15 and CG/45 (received only sterile saline in the knee). The rats were killed 15 and 45 days postinoculation. In contrast with the control rats, the histopathology of the joints of rats of the test groups (EG/15 and EG/45) revealed a picture of well-established PCM arthritis characterized by extensive sclerosing granulomatous inflammation with numerous multiple budding fungal cells. The X-ray examination revealed joint alterations in these groups. Only metabolic active fungi evoked inflammation. The experimental model was able to induce fungal arthritis in the knees of the rats infected with metabolic active P. brasiliensis. The disease tended to be regressive and restrained by the immune system. No evidence of fungal dissemination to the lungs was observed.

Synthesis Methodology Applied to a Tunable Patch Filter With Independent Frequency and Bandwidth Control

A new methodology for the synthesis of tunable patch filters is presented. The methodology helps the designer to perform a theoretical analysis of the filter through a coupling matrix that includes the effect of the tuning elements used to tune the filter. This general methodology accounts for any tuning parameter desired and was applied to the design of a tunable dual-mode patch filter with independent control of center frequency and bandwidth (BW). The bandpass filter uses a single triangular resonator with two etched slots that split the fundamental degenerate modes and form the filter passband. Varactor diodes assembled across the slots are used to vary the frequency of each degenerate fundamental mode independently, which is feasible due to the nature of the coupling scheme of the filter. The varactor diode model used in simulations, their assembling, the dc bias configuration, and measured results are presented. The theory results are compared to the simulations and to measurements showing a very good agreement and validating the proposed methodology. The fabricated filter presents an elliptic response with 20% of center frequency tuning range around 3.2 GHz and a fractional BW variation from 4% to 12% with low insertion loss and high power handling with a 1-dB compression point higher than +14.5 dB.

Comparison of multiple-input single-output single-user ultra-wideband systems with pre-distortion

This paper presents a performance analysis of a baseband multiple-input single-output ultra-wideband system over scenarios CM1 and CM3 of the IEEE 802.15.3a channel model, incorporating four different schemes of pre-distortion: time reversal, zero-forcing pre-equaliser, constrained least squares pre-equaliser, and minimum mean square error pre-equaliser. For the third case, a simple solution based on the steepest-descent (gradient) algorithm is adopted and compared with theoretical results. The channel estimations at the transmitter are assumed to be truncated and noisy. Results show that the constrained least squares algorithm has a good trade-off between intersymbol interference reduction and signal-to-noise ratio preservation, providing a performance comparable to the minimum mean square error method but with lower computational complexity. Copyright (C) 2011 John Wiley & Sons, Ltd.

Are Multiple Cryoprobes Additive or Synergistic in Renal Cryotherapy?

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.

A biophysical model of Sugarcane growth

Scientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in crop-based biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process-based sugarcane model (included as a module within the Agro-IBIS dynamic agro-ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/overestimated the daily sensible/latent heat flux (by -10.5% and 14.8%, H and E, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between -10.1% and 12.5%) when compared against an agro-meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of Sao Paulo, Brazil, over a period of 16 years, with a yield relative bias of -0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (-2.67%), but exhibited a lower interannual variability than the observed yields.

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

A novel method for power quality multiple disturbance decomposition based on Independent Component Analysis

In this paper, a novel method for power quality signal decomposition is proposed based on Independent Component Analysis (ICA). This method aims to decompose the power system signal (voltage or current) into components that can provide more specific information about the different disturbances which are occurring simultaneously during a multiple disturbance situation. The ICA is originally a multichannel technique. However, the method proposes its use to blindly separate out disturbances existing in a single measured signal (single channel). Therefore, a preprocessing step for the ICA is proposed using a filter bank. The proposed method was applied to synthetic data, simulated data, as well as actual power system signals, showing a very good performance. A comparison with the decomposition provided by the Discrete Wavelet Transform shows that the proposed method presented better decoupling for the analyzed data. (C) 2012 Elsevier Ltd. All rights reserved.