Cardiovascular Disease Parameters in Periodontitis

Background: Recently, there has been an increasing in the impact of oral health on atherosclerosis and subsequent cardiovascular disease. The aim of this study is to investigate the association between chronic periodontitis and cardiovascular risk markers. Methods: Forty patients with periodontitis and 40 healthy gender-, body mass index-, and age-matched individuals were compared by measuring total cholesterol, high-density lipoprotein, low-density lipoprotein, triglycerides, levels of cytokines, antibodies against oxidized low-density lipoprotein, thiobarbituric acid reactive substances, total and differential white blood cell counts, and the non-linear index of refraction. Results: The levels of triglycerides and high-density lipoprotein in periodontitis patients were significantly higher and lower, respectively (P=0.002 and P=0.0126), compared to controls. Total cholesterol, low-density lipoprotein, and lipid peroxide levels were the same in both groups (P = 0.2943, P = 0.1284, and P = 0.067, respectively). Interleukin (IL)-6 and -8, antibodies against oxidized low-density lipoprotein, and leukocyte and neutrophil counts were significantly higher in periodontitis patients (P<0.05). The value of the non-linear index of refraction of low-density lipoprotein solutions was higher in the controls (P = 0.015) compared to individuals with periodontitis. Conclusion: Our results confirmed and further strengthened the suggested association between coronary artery disease and periodontitis. J Periodontol 2009;80:378-388.

The influence of ARIMA-GARCH parameters in feed forward neural networks prediction

The objective of this article is to find out the influence of the parameters of the ARIMA-GARCH models in the prediction of artificial neural networks (ANN) of the feed forward type, trained with the Levenberg-Marquardt algorithm, through Monte Carlo simulations. The paper presents a study of the relationship between ANN performance and ARIMA-GARCH model parameters, i.e. the fact that depending on the stationarity and other parameters of the time series, the ANN structure should be selected differently. Neural networks have been widely used to predict time series and their capacity for dealing with non-linearities is a normally outstanding advantage. However, the values of the parameters of the models of generalized autoregressive conditional heteroscedasticity have an influence on ANN prediction performance. The combination of the values of the GARCH parameters with the ARIMA autoregressive terms also implies in ANN performance variation. Combining the parameters of the ARIMA-GARCH models and changing the ANN`s topologies, we used the Theil inequality coefficient to measure the prediction of the feed forward ANN.

Sodium Tungstate on Some Biochemical Parameters of the Parotid Salivary Gland of Streptozotocin-Induced Diabetic Rats: A Short-Term Study

Several studies have shown the antidiabetic properties of sodium tungstate. In this study, we evaluated some biochemical parameters of the parotid salivary gland of streptozotocin-induced diabetic rats treated with sodium tungstate solution (2 mg/ml). The studied groups were: untreated control (UC), treated control (TC), untreated diabetic (UD), and treated diabetic (TD). After 2 and 6 weeks of treatment, parotid gland was removed and total protein and sialic acid (free and total) concentration and amylase and peroxidase activities were determined. Data were compared by variance analysis and Tukey test (p < 0.05). The sodium tungstate treatment modestly decreased the glycemia of streptozotocin-induced diabetic rats. At week 2 of the study, parotid gland of diabetic rats presented a reduction of total protein concentration (55%) and an increase of amylase (120%) and peroxidase (160%) activities, free (150%) and total (170%) sialic acid concentration. No alteration in the evaluated parameters at week 6 of the study was observed. Sodium tungstate presented no significant effect in parotid gland. Our results suggest that diabetes causes initial modification in biochemical composition of parotid. However, this gland showed a recovery capacity after 6 week of the experimental time. Sodium tungstate has no effect in peripheral tissues, such as salivary glands.

Does the neuromotor abnormality type affect the salivary parameters in individuals with cerebral palsy?

Background: Previous studies reported alterations in salivary flow rate and biochemical parameters of saliva in cerebral palsy (CP) individuals; however, none of these considered the type of neuromotor abnormality among CP individuals, thus it remains unclear whether the different anatomical and extended regions of the brain lesions responsible for the neurological damage in CP might include disruption of the regulatory mechanism of saliva secretion as part of the encephalopathy. The aim of this study was to evaluate salivary flow rate, pH and buffer capacity in saliva of individuals with CP, aged 3-16 years, with spastic neuromotor abnormality type and clinical patterns of involvement. Methods: Sixty-seven individuals with CP spasticity movement disorder, were divided in two groups according to age (3-8- and 9-16-years-old) and compared with 35 sibling volunteers with no neurological damage, divided in two groups according to age (3-8- and 9-16-years-old). Whole saliva was collected under slight suction and pH and buffer capacity were determined using a digital pHmeter. Buffer capacity was measured by titration using 0.01N HCL, and flow rate was calculated in ml/min. Results: In both age groups studied, whole saliva flow rate, pH and buffer capacity were significantly lower in the spastic CP group (P < 0.05). The clinical patterns of involvement did not influence the studied parameters. Conclusion: These findings show that individuals with spastic cerebral palsy present lower salivary flow rate, pH and buffer capacity that can increase the risk of oral disease in this population.

Structural parameters of polyacrylamide hydrogels obtained by the Equilibrium Swelling Theory

In this paper, the synthesis and structural characterization of a series of polyacrylamide hydrogels with different degrees of reticulation are reported. Although the Equilibrium Swelling Theory was recognized as a simple and reliable tool for the determination of structural hydrogels network parameters like equilibrium degree of swelling, cross-link ratio and mesh size, this is the first application of this methodology for polyacrylamide hydrogels. By changing the total monomer content in the synthesis solution (%T) from 5 to 30%, at a fixed value of cross-linker content in the total monomer amount (%C) of 5%, the final parameter obtained, the mesh size, can be tuned from 2 to 0.3 nm. It was also possible to change the mesh size (0.19-0.35) by varying %C from 5 to 12% (at %T = 20%). Scanning Electron Microscopy images for the most different formulations are shown and corroborate data obtained from the theory. (c) 2008 Elsevier Ltd. All rights reserved.

Metal transport parameters of a gneiss saprolitic silty soil for liner design

Diffusion coefficients and retardation factors of two metal cations (Cd2+ and Pb2+) were measured for a compacted Brazilian saprolitic soil derived from gneiss, aiming to assess its geoenvironmental performance as a liner for waste disposal sites. This soil occurs extensively all over the country in very thick layers, but has not been used in liners because of its hydraulic conductivity, higher than 10(-9) m/s when compacted at optimum water content of standard Proctor energy, but which can be reduced by means of appropriate compaction techniques or additives. Batch, column, and diffusion tests were carried out with monospecies synthetic solutions at pH 1, 3, and 5.5. Measured diffusion coefficients varied between 0.5 and 4 X 10(-10) m(2)/s. Retardation factors show that cadmium, a very mobile cation, is not adsorbed at pH I but is significantly retained at pH 3 and pH 5.5, whereas lead is retained at all tested pH values though slightly at pH 1. Estimated retardation factors from batch tests were 1.3-2.3 times those resulting from column tests and at its highest when obtained by diffusion tests; whereas batch tests allow a more complete exposure of the soil grains to the solution, time-dependent nonspecific adsorption may take longer to occur. The importance of contact time was observed and should be considered in further investigations. Its significant retention of metals suggests a promising utilization of this soil as a bottom liner for wastes landfills.

Thermal stability of extracellular hemoglobin of Glossoscolex paulistus: Determination of activation parameters by optical spectroscopic and differential scanning calorimetric studies

Glossoscolex paulistus hemoglobin (HbGp) was studied by dynamic light scattering (DLS), optical absorption spectroscopy (UV-VIS) and differential scanning calorimetry (DSC). At pH 7.0, cyanomet-HbGp is very stable, no oligomeric dissociation is observed, while denaturation occurs at 56 degrees C, 4 degrees C higher as compared to oxy-HbGp. The oligomeric dissociation of HbGp occurs simultaneously with some protein aggregation. Kinetic studies for oxy-HbGp using UV-VIS and DES allowed to obtain activation energy (E(a)) values of 278-262 kJ/mol (DES) and 333 kJ/mol (UV-VIS). Complimentary DSC studies indicate that the denaturation is irreversible, giving endotherms strongly dependent upon the heating scan rates, suggesting a kinetically controlled process. Dependence on protein concentration suggests that the two components in the endotherms are due to oligomeric dissociation effect upon denaturation. Activation energies are in the range 200-560 kJ/mol. The mid-point transition temperatures were in the range 50-65 degrees C. Cyanomet-HbGp shows higher mid-point temperatures as well as activation energies, consistent with its higher stability. DSC data are reported for the first time for an extracellular hemoglobin. (C) 2010 Elsevier B.V. All rights reserved.

Important Parameters in Designing and Presenting Exhibits and Planetarium Programs in Science Centers : A Visitor-Based Framework

This dissertation proposes an initial framework for designing and presenting exhibits in science centers and to recommend methods for improving the educational role of planetariums in science centers.

Methodology for identifying parameters for the TRNSYS model Type 210 -wood pellet stoves and boilers

This report describes a method how to perform measurements on boilers and stoves and how to identify parameters from the measurements for the boiler/stove-model TRNSYS Type 210. The model can be used for detailed annual system simulations using TRNSYS. Experience from measurements on three different pellet stoves and four boilers were used to develop this methodology. Recommendations for the set up of measurements are given and the re-quired combustion theory for the data evaluation and data preparation are given. The data evalua-tion showed that the uncertainties are quite large for the measured flue gas flow rate and for boilers and stoves with high fraction of energy going to the water jacket also the calculated heat rate to the room may have large uncertainties. A methodology for the parameter identification process and identified parameters for two different stoves and three boilers are given. Finally the identified models are compared with measured data showing that the model generally agreed well with meas-ured data during both stationary and dynamic conditions.

Estimation of Parameters in Random Effect Models with Incidence Matrix Uncertainty

Random effect models have been widely applied in many fields of research. However, models with uncertain design matrices for random effects have been little investigated before. In some applications with such problems, an expectation method has been used for simplicity. This method does not include the extra information of uncertainty in the design matrix is not included. The closed solution for this problem is generally difficult to attain. We therefore propose an two-step algorithm for estimating the parameters, especially the variance components in the model. The implementation is based on Monte Carlo approximation and a Newton-Raphson-based EM algorithm. As an example, a simulated genetics dataset was analyzed. The results showed that the proportion of the total variance explained by the random effects was accurately estimated, which was highly underestimated by the expectation method. By introducing heuristic search and optimization methods, the algorithm can possibly be developed to infer the 'model-based' best design matrix and the corresponding best estimates.

Performance Evaluation Of SMOS Soil Moisture Retrieval Parameters For Hydrological Application

Microwave remote sensing has high potential for soil moisture retrieval. However, the efficient retrieval of soil moisture depends on optimally choosing the soil moisture retrieval parameters. In this study first the initial evaluation of SMOS L2 product is performed and then four approaches regarding soil moisture retrieval from SMOS brightness temperature are reported. The radiative transfer equation based tau-omega rationale is used in this study for the soil moisture retrievals. The single channel algorithms (SCA) using H polarisation is implemented with modifications, which includes the effective temperatures simulated from ECMWF (downscaled using WRF-NOAH Land Surface Model (LSM)) and MODIS. The retrieved soil moisture is then utilized for soil moisture deficit (SMD) estimation using empirical relationships with Probability Distributed Model based SMD as a benchmark. The square of correlation during the calibration indicates a value of R2 =0.359 for approach 4 (WRF-NOAH LSM based LST with optimized roughness parameters) followed by the approach 2 (optimized roughness parameters and MODIS based LST) (R2 =0.293), approach 3 (WRF-NOAH LSM based LST with no optimization) (R2 =0.267) and approach 1(MODIS based LST with no optimization) (R2 =0.163). Similarly, during the validation a highest performance is reported by approach 4. The other approaches are also following a similar trend as calibration. All the performances are depicted through Taylor diagram which indicates that the H polarisation using ECMWF based LST is giving a better performance for SMD estimation than the original SMOS L2 products at a catchment scale.

Semiparametric estimation and inference using doubly robust moment conditions

We study semiparametric two-step estimators which have the same structure as parametric doubly robust estimators in their second step. The key difference is that we do not impose any parametric restriction on the nuisance functions that are estimated in a first stage, but retain a fully nonparametric model instead. We call these estimators semiparametric doubly robust estimators (SDREs), and show that they possess superior theoretical and practical properties compared to generic semiparametric two-step estimators. In particular, our estimators have substantially smaller first-order bias, allow for a wider range of nonparametric first-stage estimates, rate-optimal choices of smoothing parameters and data-driven estimates thereof, and their stochastic behavior can be well-approximated by classical first-order asymptotics. SDREs exist for a wide range of parameters of interest, particularly in semiparametric missing data and causal inference models. We illustrate our method with a simulation exercise.

Bounds on policy relevant parameters with discrete policy variation

When estimating policy parameters, also known as treatment effects, the assignment to treatment mechanism almost always causes endogeneity and thus bias many of these policy parameters estimates. Additionally, heterogeneity in program impacts is more likely to be the norm than the exception for most social programs. In situations where these issues are present, the Marginal Treatment Effect (MTE) parameter estimation makes use of an instrument to avoid assignment bias and simultaneously to account for heterogeneous effects throughout individuals. Although this parameter is point identified in the literature, the assumptions required for identification may be strong. Given that, we use weaker assumptions in order to partially identify the MTE, i.e. to stablish a methodology for MTE bounds estimation, implementing it computationally and showing results from Monte Carlo simulations. The partial identification we perfom requires the MTE to be a monotone function over the propensity score, which is a reasonable assumption on several economics' examples, and the simulation results shows it is possible to get informative even in restricted cases where point identification is lost. Additionally, in situations where estimated bounds are not informative and the traditional point identification is lost, we suggest a more generic method to point estimate MTE using the Moore-Penrose Pseudo-Invese Matrix, achieving better results than traditional methods.