The Effect of Different Fluoride Concentrations and pH of Dentifrices on Plaque and Nail Fluoride Levels in Young Children

To evaluate the influence of dentifrice pH and fluoride (F) concentration on F uptake by plaque and nails, two sets of 5-to 6-year-old children were randomly allocated into four groups, according to the type of dentifrice they had been using for 1 year: (1) experimental liquid dentifrice (ELD), 1,100 ppm F, pH 7.0; (2) ELD, 1,100 ppm F, pH 4.5; (3) ELD, 550 ppm F, pH 4.5, and (4) commercial toothpaste, 1,100 ppm F, pH 7.0. In one set of children, nails were clipped. In the second, plaque samples were collected 1 h after the last use of dentifrice. F concentration in plaque and nails was analyzed. Plaque F concentration was significantly lower in group 4 than in groups 1-3. Nail F concentration was significantly higher in group 4, and significantly lower in group 3, than in group 1 or 2. Plaque F uptake was influenced significantly by dentifrice consistency and nonsignificantly by pH and F concentration. Reduction of dentifrice pH did not affect nail F concentration. Copyright (C) 2009 S. Karger AG, Basel

The Drop Technique: a Method to Control the Amount of Fluoride Dentifrice Used by Young Children

Purpose: The purpose of this study was to evaluate the amount of dentifrice applied to the toothbrush by school children using a liquid dentifrice (drop technique), when compared to toothpaste. Materials and Methods: A total of 178 school children (4-8 years old) from two cities in Brazil (Bauru and Bariri) participated in the present two-part crossover study. Children from Bauru received training regarding tooth-brushing techniques and use of dentifrice before data collection. In each phase, the amount of toothpaste or liquid dentifrice applied by the children to the toothbrush was measured, using a portable analytical balance (+/- 0.01 g). Data were tested by analysis of covariance (Ancova) and linear regression (p < 0.05). Results: The mean (+/- standard deviation) amounts of toothpaste and liquid dentifrice applied to the toothbrushes for children from Bauru were 0.41 +/- 0.20 g and 0.15 +/- 0.06 g, respectively. For children from Bariri, the amounts applied were and 0.48 +/- 0.24 g and 0.14 +/- 0.05 g, respectively. The amount of toothpaste applied was significantly larger than the amount of liquid dentifrice for both cities. Children from Bariri applied a significantly larger amount of toothpaste, when compared to those from Bauru. However, for the liquid dentifrice, there was no statistically significant difference between the cities. A significant correlation between the amount of toothpaste applied and the age of the children was verified, but the same was not found for the liquid dentifrice. Conclusion: The use of the drop technique reduced and standardised the amount of dentifrice applied to the toothbrush, which could reduce the risk of dental fluorosis for young children.

Evolutionary model trees for handling continuous classes in machine learning

Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.

Exercise x BCAA supplementation in young trained rats: what are their effects on body growth?

The purpose of this study was to evaluate whether Branched-chain amino acids (BCAAs) supplementation had any beneficial effects on growth and metabolic parameters of young rats submitted to chronic aerobic exercise. Thirty-two young rats (age: 21-d) were randomly assigned to four experimental groups (n = 8): Supplemented Trained (Sup/Ex), Control Trained (Ctrl/Ex), Supplemented Sedentary (Sup/Sed) and Control Sedentary (Ctrl/Sed). The trained groups underwent a five-week swimming protocol and received supplemented (45 mg BCAA/body weight/day) or control ration. Trained animals presented a lower body length and a higher cartilage weight, regardless of supplementation. Physical activity was responsible for a substantial reduction in proteoglycan synthesis in cartilage tissue, and BCAA supplementation was able to attenuate this reduction and also to improve glycogen stores in the liver, although no major differences were found in body growth associated to this supplementation.

Dez anos de parâmetros curriculares nacionais: a prática da Educação Física na visão dos seus autores

The study checked possible theory-methodologic assumptions into Physical Education PCNs by the teachers of the last years of elementary school. The analyses in the publishing allow us to identify the different didactic procedures when compared with those which set up the traditional expectations. From these elements and using the projective method, it was developed an interview with focal group. The data obtained showed us docent perceptions which rearrange the educative practice, and interpretation allows us to realize which of the teachers views approaches the propositions in the official document, even if no reference has been done to it.

Phase Equilibrium and Optimization Tools: Application for Enhanced Structured Lipids for Foods

Solid-liquid phase equilibrium modeling of triacylglycerol mixtures is essential for lipids design. Considering the alpha polymorphism and liquid phase as ideal, the Margules 2-suffix excess Gibbs energy model with predictive binary parameter correlations describes the non ideal beta and beta` solid polymorphs. Solving by direct optimization of the Gibbs free energy enables one to predict from a bulk mixture composition the phases composition at a given temperature and thus the SFC curve, the melting profile and the Differential Scanning Calorimetry (DSC) curve that are related to end-user lipid properties. Phase diagram, SFC and DSC curve experimental data are qualitatively and quantitatively well predicted for the binary mixture 1,3-dipalmitoyl-2-oleoyl-sn-glycerol (POP) and 1,2,3-tripalmitoyl-sn-glycerol (PPP), the ternary mixture 1,3-dimyristoyl-2-palmitoyl-sn-glycerol (MPM), 1,2-distearoyl-3-oleoyl-sn-glycerol (SSO) and 1,2,3-trioleoyl-sn-glycerol (OOO), for palm oil and cocoa butter. Then, addition to palm oil of Medium-Long-Medium type structured lipids is evaluated, using caprylic acid as medium chain and long chain fatty acids (EPA-eicosapentaenoic acid, DHA-docosahexaenoic acid, gamma-linolenic-octadecatrienoic acid and AA-arachidonic acid), as sn-2 substitutes. EPA, DHA and AA increase the melting range on both the fusion and crystallization side. gamma-linolenic shifts the melting range upwards. This predictive tool is useful for the pre-screening of lipids matching desired properties set a priori.

Providing Integrity and Authenticity in DICOM Images: A Novel Approach

The increasing adoption of information systems in healthcare has led to a scenario where patient information security is more and more being regarded as a critical issue. Allowing patient information to be in jeopardy may lead to irreparable damage, physically, morally, and socially to the patient, potentially shaking the credibility of the healthcare institution. Medical images play a crucial role in such context, given their importance in diagnosis, treatment, and research. Therefore, it is vital to take measures in order to prevent tampering and determine their provenance. This demands adoption of security mechanisms to assure information integrity and authenticity. There are a number of works done in this field, based on two major approaches: use of metadata and use of watermarking. However, there still are limitations for both approaches that must be properly addressed. This paper presents a new method using cryptographic means to improve trustworthiness of medical images, providing a stronger link between the image and the information on its integrity and authenticity, without compromising image quality to the end user. Use of Digital Imaging and Communications in Medicine structures is also an advantage for ease of development and deployment.