Augmented Mixed Models For Clustered Proportion Data.

Often in biomedical research, we deal with continuous (clustered) proportion responses ranging between zero and one quantifying the disease status of the cluster units. Interestingly, the study population might also consist of relatively disease-free as well as highly diseased subjects, contributing to proportion values in the interval [0, 1]. Regression on a variety of parametric densities with support lying in (0, 1), such as beta regression, can assess important covariate effects. However, they are deemed inappropriate due to the presence of zeros and/or ones. To evade this, we introduce a class of general proportion density, and further augment the probabilities of zero and one to this general proportion density, controlling for the clustering. Our approach is Bayesian and presents a computationally convenient framework amenable to available freeware. Bayesian case-deletion influence diagnostics based on q-divergence measures are automatic from the Markov chain Monte Carlo output. The methodology is illustrated using both simulation studies and application to a real dataset from a clinical periodontology study.

Possibilidades e limites da avaliação da qualidade de vida : análise dos instrumentos WHOQOL e modelos clássicos de qualidade de vida no trabalho = Possibilities and limits of quality of life assessment : analysis of WHOQOL instruments and quality of work life classical models

Universidade Estadual de Campinas . Faculdade de Educação Física

Comparative study of dental arch width in plaster models, photocopies and digitized images

The aim of this study was to comparatively assess dental arch width, in the canine and molar regions, by means of direct measurements from plaster models, photocopies and digitized images of the models. The sample consisted of 130 pairs of plaster models, photocopies and digitized images of the models of white patients (n = 65), both genders, with Class I and Class II Division 1 malocclusions, treated by standard Edgewise mechanics and extraction of the four first premolars. Maxillary and mandibular intercanine and intermolar widths were measured by a calibrated examiner, prior to and after orthodontic treatment, using the three modes of reproduction of the dental arches. Dispersion of the data relative to pre- and posttreatment intra-arch linear measurements (mm) was represented as box plots. The three measuring methods were compared by one-way ANOVA for repeated measurements (α = 0.05). Initial / final mean values varied as follows: 33.94 to 34.29 mm / 34.49 to 34.66 mm (maxillary intercanine width); 26.23 to 26.26 mm / 26.77 to 26.84 mm (mandibular intercanine width); 49.55 to 49.66 mm / 47.28 to 47.45 mm (maxillary intermolar width) and 43.28 to 43.41 mm / 40.29 to 40.46 mm (mandibular intermolar width). There were no statistically significant differences between mean dental arch widths estimated by the three studied methods, prior to and after orthodontic treatment. It may be concluded that photocopies and digitized images of the plaster models provided reliable reproductions of the dental arches for obtaining transversal intra-arch measurements.

Anatomic variation of cranial parasympathetic ganglia

Having broad knowledge of anatomy is essential for practicing dentistry. Certain anatomical structures call for detailed studies due to their anatomical and functional importance. Nevertheless, some structures are difficult to visualize and identify due to their small volume and complicated access. Such is the case of the parasympathetic ganglia located in the cranial part of the autonomic nervous system, which include: the ciliary ganglion (located deeply in the orbit, laterally to the optic nerve), the pterygopalatine ganglion (located in the pterygopalatine fossa), the submandibular ganglion (located laterally to the hyoglossus muscle, below the lingual nerve), and the otic ganglion (located medially to the mandibular nerve, right beneath the oval foramen). The aim of this study was to present these structures in dissected anatomic specimens and perform a comparative analysis regarding location and morphology. The proximity of the ganglia and associated nerves were also analyzed, as well as the number and volume of fibers connected to them. Human heads were dissected by planes, partially removing the adjacent structures to the point we could reach the parasympathetic ganglia. With this study, we concluded that there was no significant variation regarding the location of the studied ganglia. Morphologically, our observations concur with previous classical descriptions of the parasympathetic ganglia, but we observed variations regarding the proximity of the otic ganglion to the mandibular nerve. We also observed that there were variations regarding the number and volume of fiber bundles connected to the submandibular, otic, and pterygopalatine ganglia.

Allometric models for estimating the phytomass of a secondary Atlantic Forest area of southeastern Brazil

The purpose of this study was to develop and validate equations to estimate the aboveground phytomass of a 30 years old plot of Atlantic Forest. In two plots of 100 m², a total of 82 trees were cut down at ground level. For each tree, height and diameter were measured. Leaves and woody material were separated in order to determine their fresh weights in field conditions. Samples of each fraction were oven dried at 80 °C to constant weight to determine their dry weight. Tree data were divided into two random samples. One sample was used for the development of the regression equations, and the other for validation. The models were developed using single linear regression analysis, where the dependent variable was the dry mass, and the independent variables were height (h), diameter (d) and d²h. The validation was carried out using Pearson correlation coefficient, paired t-Student test and standard error of estimation. The best equations to estimate aboveground phytomass were: lnDW = -3.068+2.522lnd (r² = 0.91; s y/x = 0.67) and lnDW = -3.676+0.951ln d²h (r² = 0.94; s y/x = 0.56).

Descriptor-and fragment-based QSAR models for a series of Schistosoma mansoni purine nucleoside inhibitors

The enzyme purine nucleoside phosphorylase from Schistosoma mansoni (SmPNP) is an attractive molecular target for the treatment of major parasitic infectious diseases, with special emphasis on its role in the discovery of new drugs against schistosomiasis, a tropical disease that affects millions of people worldwide. In the present work, we have determined the inhibitory potency and developed descriptor- and fragment-based quantitative structure-activity relationships (QSAR) for a series of 9-deazaguanine analogs as inhibitors of SmPNP. Significant statistical parameters (descriptor-based model: r² = 0.79, q² = 0.62, r²pred = 0.52; and fragment-based model: r² = 0.95, q² = 0.81, r²pred = 0.80) were obtained, indicating the potential of the models for untested compounds. The fragment-based model was then used to predict the inhibitory potency of a test set of compounds, and the predicted values are in good agreement with the experimental results

Comparison of some theoretical models for fittings of the temperature dependence of the fundamental energy gap in GaAs

In this work we report on a comparison of some theoretical models usually used to fit the dependence on temperature of the fundamental energy gap of semiconductor materials. We used in our investigations the theoretical models of Viña, Pässler-p and Pässler-ρ to fit several sets of experimental data, available in the literature for the energy gap of GaAs in the temperature range from 12 to 974 K. Performing several fittings for different values of the upper limit of the analyzed temperature range (Tmax), we were able to follow in a systematic way the evolution of the fitting parameters up to the limit of high temperatures and make a comparison between the zero-point values obtained from the different models by extrapolating the linear dependence of the gaps at high T to T = 0 K and that determined by the dependence of the gap on isotope mass. Using experimental data measured by absorption spectroscopy, we observed the non-linear behavior of Eg(T) of GaAs for T > ΘD.

Stress distribution in the cervical region of an upper central incisor in a 3D finite element model

The aim of this study was to evaluate the stress distribution in the cervical region of a sound upper central incisor in two clinical situations, standard and maximum masticatory forces, by means of a 3D model with the highest possible level of fidelity to the anatomic dimensions. Two models with 331,887 linear tetrahedral elements that represent a sound upper central incisor with periodontal ligament, cortical and trabecular bones were loaded at 45º in relation to the tooth's long axis. All structures were considered to be homogeneous and isotropic, with the exception of the enamel (anisotropic). A standard masticatory force (100 N) was simulated on one of the models, while on the other one a maximum masticatory force was simulated (235.9 N). The software used were: PATRAN for pre- and post-processing and Nastran for processing. In the cementoenamel junction area, tensile forces reached 14.7 MPa in the 100 N model, and 40.2 MPa in the 235.9 N model, exceeding the enamel's tensile strength (16.7 MPa). The fact that the stress concentration in the amelodentinal junction exceeded the enamel's tensile strength under simulated conditions of maximum masticatory force suggests the possibility of the occurrence of non-carious cervical lesions such as abfractions.

Reproducibility, reliability and validity of measurements obtained from Cecile3 digital models

The aim of this study was to determine the reproducibility, reliability and validity of measurements in digital models compared to plaster models. Fifteen pairs of plaster models were obtained from orthodontic patients with permanent dentition before treatment. These were digitized to be evaluated with the program Cécile3 v2.554.2 beta. Two examiners measured three times the mesiodistal width of all the teeth present, intercanine, interpremolar and intermolar distances, overjet and overbite. The plaster models were measured using a digital vernier. The t-Student test for paired samples and interclass correlation coefficient (ICC) were used for statistical analysis. The ICC of the digital models were 0.84 ± 0.15 (intra-examiner) and 0.80 ± 0.19 (inter-examiner). The average mean difference of the digital models was 0.23 ± 0.14 and 0.24 ± 0.11 for each examiner, respectively. When the two types of measurements were compared, the values obtained from the digital models were lower than those obtained from the plaster models (p < 0.05), although the differences were considered clinically insignificant (differences < 0.1 mm). The Cécile digital models are a clinically acceptable alternative for use in Orthodontics.

Women's satisfaction with childbirth's experience in different models of care: a descriptive study

Com o objetivo de comparar a satisfação das mulheres com a experiência do parto em três modelos assistenciais, foi realizada pesquisa descritiva, com abordagem quantitativa, em dois hospitais públicos de São Paulo, um promovendo o modelo "Típico" e o outro com um centro de parto intra-hospitalar (modelo "CPNIH") e um peri-hospitalar (modelo "CPNPH"). A amostra foi constituída por 90 puérperas, 30 de cada modelo. A comparação entre os resultados referentes à satisfação das mulheres com o atendimento prestado pelos profissionais de saúde, com a qualidade da assistência e os motivos de satisfação e insatisfação, com a indicação ou recomendação dos serviços recebidos, com a sensação de segurança no processo e com as sugestões de melhorias, mostrou que o modelo CPHPH foi o melhor avaliado, vindo em seguida o CPNIH e por último o Típico. Conclui-se que o modelo peri-hospitalar de assistência ao parto deveria receber maior apoio do SUS, por se constituir em serviço em que as mulheres se mostram satisfeitas com a atenção recebida

The full Bayesian significance test for mixture models: results in gene expression clustering

Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method's sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results.

Dynamical models for computer viruses propagation

Nowadays, digital computer systems and networks are the main engineering tools, being used in planning, design, operation, and control of all sizes of building, transportation, machinery, business, and life maintaining devices. Consequently, computer viruses became one of the most important sources of uncertainty, contributing to decrease the reliability of vital activities. A lot of antivirus programs have been developed, but they are limited to detecting and removing infections, based on previous knowledge of the virus code. In spite of having good adaptation capability, these programs work just as vaccines against diseases and are not able to prevent new infections based on the network state. Here, a trial on modeling computer viruses propagation dynamics relates it to other notable events occurring in the network permitting to establish preventive policies in the network management. Data from three different viruses are collected in the Internet and two different identification techniques, autoregressive and Fourier analyses, are applied showing that it is possible to forecast the dynamics of a new virus propagation by using the data collected from other viruses that formerly infected the network. Copyright (c) 2008 J. R. C. Piqueira and F. B. Cesar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Evaluation of Antiproliferative, Anti-Type 2 Diabetes, and Antihypertension Potentials of Ellagitannins from Strawberries (Fragaria x ananassa Duch.) Using In Vitro Models

Strawberries represent the main source of ellagic acid derivatives in the Brazilian diet, corresponding to more than 50% of all phenolic compounds found in the fruit. There is a particular interest in the determination of the ellagic acid content in fruits because of possible chemopreventive benefits. In the present study, the potential health benefits of purified ellagitannins from strawberries were evaluated in relation to the antiproliferative activity and in vitro inhibition of alpha-amylase, alpha-glucosidase, and angiotensin I-converting enzyme (ACE) relevant for potential management of hyperglycemia and hypertension. Therefore, a comparison among ellagic acid, purified ellagitannins, and a strawberry extract was done to evaluate the possible synergistic effects of phenolics. In relation to the antiproliferative activity, it was observed that ellagic acid had the highest percentage inhibition of cell proliferation. The strawberry extract had lower efficacy in inhibiting the cell proliferation, indicating that in the case of this fruit there is no synergism. Purified ellagitannins had high alpha-amylase and ACE inhibitory activities. However, these compounds had low alpha-glucosidase inhibitory activity. These results suggested that the ellagitannins and ellagic acid have good potential for the management of hyperglycemia and hypertension linked to type 2 diabetes. However, further studies with animal and human models are needed to advance the in vitro assay-based biochemical rationale from this study.

Evaluation of Antihyperglycemia and Antihypertension Potential of Native Peruvian Fruits Using In Vitro Models

Local food diversity and traditional crops are essential for cost-effective management of the global epidemic of type 2 diabetes and associated complications of hypertension. Water and 12% ethanol extracts of native Peruvian fruits such as Lucuma (Pouteria lucuma), Pacae (Inga feuille), Papayita arequipena (Carica pubescens), Capuli (Prunus capuli), Aguaymanto (Physalis peruviana), and Algarrobo (Prosopis pallida) were evaluated for total phenolics, antioxidant activity based on 2, 2-diphenyl-1-picrylhydrazyl radical scavenging assay, and functionality such as in vitro inhibition of alpha-amylase, alpha-glucosidase, and angiotensin I-converting enzyme (ACE) relevant for potential management of hyperglycemia and hypertension linked to type 2 diabetes. The total phenolic content ranged from 3.2 (Aguaymanto) to 11.4 (Lucuma fruit) mg/g of sample dry weight. A significant positive correlation was found between total phenolic content and antioxidant activity for the ethanolic extracts. No phenolic compound was detected in Lucuma (fruit and powder) and Pacae. Aqueous extracts from Lucuma and Algarrobo had the highest alpha-glucosidase inhibitory activities. Papayita arequipena and Algarrobo had significant ACE inhibitory activities reflecting antihypertensive potential. These in vitro results point to the excellent potential of Peruvian fruits for food-based strategies for complementing effective antidiabetes and antihypertension solutions based on further animal and clinical studies.

Antidiabetes and antihypertension potential of commonly consumed carbohydrate sweeteners using in vitro models

Commonly consumed carbohydrate sweeteners derived from sugar cane, palm, and corn (syrups) were investigated to determine their potential to inhibit key enzymes relevant to Type 2 diabetes and hypertension based on the total phenolic content and antioxidant activity using in vitro models. Among sugar cane derivatives, brown sugars showed higher antidiabetes potential than white sugars; nevertheless, no angiotensin I-converting enzyme (ACE) inhibition was detected in both sugar classes. Brown sugar from Peru and Mauritius (dark muscovado) had the highest total phenolic content and 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity, which correlated with a moderate inhibition of yeast alpha-glucosidase without showing a significant effect on porcine pancreatic alpha-amylase activity. In addition, chlorogenic acid quantified by high-performance liquid chromatography was detected in these sugars (128 +/- 6 and 144 +/- 2 mu g/g of sample weight, respectively). Date sugar exhibited high alpha-glucosidase, alpha-amylase, and ACE inhibitory activities that correlated with high total phenolic content and antioxidant activity. Neither phenolic compounds or antioxidant activity was detected in corn syrups, indicating that nonphenolic factors may be involved in their significant ability to inhibit alpha-glucosidase, alpha-amylase, and ACE. This study provides a strong biochemical rationale for further in vivo studies and useful information to make better dietary sweetener choices for Type 2 diabetes and hypertension management.