The impact of asymptomatic vertebral fractures on quality of life in older community-dwelling women: the Sao Paulo Ageing & Health Study

OBJECTIVES: The aim of this study was to investigate the impact of asymptomatic vertebral fractures on the quality of life in older women as part of the Sao Paulo Ageing & Health Study. METHODS: This study was a cross-sectional study with a random sample of 180 women 65 years of age or older with or without vertebral fractures. The Quality of Life Questionnaire of the European Foundation for Osteoporosis was administered to all subjects. Anthropometric data were obtained by physical examination, and the body mass index was calculated. Lateral thoracic and lumbar spine X-ray scans were obtained to identify asymptomatic vertebral fractures using a semi-quantitative method. RESULTS: Women with asymptomatic vertebral fractures had lower total scores [61.4(15.3) vs. 67.1(14.2), p = 0.03] and worse physical function domain scores [69.5(20.1) vs. 77.3(17.1), p = 0.02] for the Quality of Life Questionnaire of the European Foundation for Osteoporosis compared with women without fractures. The total score of this questionnaire was also worse in women classified as obese than in women classified as overweight or normal. High physical activity was related to a better total score for this questionnaire (p = 0.01). Likewise, lower physical function scores were observed in women with higher body mass index values (p < 0.05) and lower physical activity levels (p < 0.05). Generalized linear models with gamma distributions and logarithmic link functions, adjusted for age, showed that lower total scores and physical function domain scores for the Quality of Life Questionnaire of the European Foundation for Osteoporosis were related to a high body mass index, lower physical activity, and the presence of vertebral fractures (p < 0.05). CONCLUSION: Vertebral fractures are associated with decreased quality of life mainly physical functioning in older community-dwelling women regardless of age, body mass index, and physical activity. Therefore, the results highlight the importance of preventing and controlling asymptomatic vertebral fractures to reduce their impact on quality of life among older women.

The impact of asymptomatic vertebral fractures on quality of life in older community-dwelling women: the São Paulo Ageing & Health Study

OBJECTIVES: The aim of this study was to investigate the impact of asymptomatic vertebral fractures on the quality of life in older women as part of the Sao Paulo Ageing & Health Study. METHODS: This study was a cross-sectional study with a random sample of 180 women 65 years of age or older with or without vertebral fractures. The Quality of Life Questionnaire of the European Foundation for Osteoporosis was administered to all subjects. Anthropometric data were obtained by physical examination, and the body mass index was calculated. Lateral thoracic and lumbar spine X-ray scans were obtained to identify asymptomatic vertebral fractures using a semi-quantitative method. RESULTS: Women with asymptomatic vertebral fractures had lower total scores [61.4(15.3) vs. 67.1(14.2), p = 0.03] and worse physical function domain scores [69.5(20.1) vs. 77.3(17.1), p = 0.02] for the Quality of Life Questionnaire of the European Foundation for Osteoporosis compared with women without fractures. The total score of this questionnaire was also worse in women classified as obese than in women classified as overweight or normal. High physical activity was related to a better total score for this questionnaire (p = 0.01). Likewise, lower physical function scores were observed in women with higher body mass index values (p<0.05) and lower physical activity levels (p,0.05). Generalized linear models with gamma distributions and logarithmic link functions, adjusted for age, showed that lower total scores and physical function domain scores for the Quality of Life Questionnaire of the European Foundation for Osteoporosis were related to a high body mass index, lower physical activity, and the presence of vertebral fractures (p<0.05). CONCLUSION: Vertebral fractures are associated with decreased quality of life mainly physical functioning in older community-dwelling women regardless of age, body mass index, and physical activity. Therefore, the results highlight the importance of preventing and controlling asymptomatic vertebral fractures to reduce their impact on quality of life among older women.

Dynamics of the 3:1 resonant planetary systems

Many of the discovered exoplanetary systems are involved inside mean-motion resonances. In this work we focus on the dynamics of the 3:1 mean-motion resonant planetary systems. Our main purpose is to understand the dynamics in the vicinity of the apsidal corotation resonance (ACR) which are stationary solutions of the resonant problem. We apply the semi-analytical method (Michtchenko et al., 2006) to construct the averaged three-body Hamiltonian of a planetary system near a 3:1 resonance. Then we obtain the families of ACR, composed of symmetric and asymmetric solutions. Using the symmetric stable solutions we observe the law of structures (Ferraz-Mello,1988), for different mass ratio of the planets. We also study the evolution of the frequencies of σ1, resonant angle, and Δω, the secular angle. The resonant domains outside the immediate vicinity of ACR are studied using dynamical maps techniques. We compared the results obtained to planetary systems near a 3:1 MMR, namely 55 Cnc b-c, HD 60532 b-c and Kepler 20 b-c.

Spin Orbit Effects in the Electronic Transport Properties of Adsorbed Graphene Nanoribbons

Graphene has received great attention due to its exceptional properties, which include corners with zero effective mass, extremely large mobilities, this could render it the new template for the next generation of electronic devices. Furthermore it has weak spin orbit interaction because of the low atomic number of carbon atom in turn results in long spin coherence lengths. Therefore, graphene is also a promising material for future applications in spintronic devices - the use of electronic spin degrees of freedom instead of the electron charge. Graphene can be engineered to form a number of different structures. In particular, by appropriately cutting it one can obtain 1-D system -with only a few nanometers in width - known as graphene nanoribbon, which strongly owe their properties to the width of the ribbons and to the atomic structure along the edges. Those GNR-based systems have been shown to have great potential applications specially as connectors for integrated circuits. Impurities and defects might play an important role to the coherence of these systems. In particular, the presence of transition metal atoms can lead to significant spin-flip processes of conduction electrons. Understanding this effect is of utmost importance for spintronics applied design. In this work, we focus on electronic transport properties of armchair graphene nanoribbons with adsorbed transition metal atoms as impurities and taking into account the spin-orbit effect. Our calculations were performed using a combination of density functional theory and non-equilibrium Greens functions. Also, employing a recursive method we consider a large number of impurities randomly distributed along the nanoribbon in order to infer, for different concentrations of defects, the spin-coherence length.

Food Competition in a Semi-Free-Ranging Cebus apella Group

The competitive regime faced by individuals is fundamental to modelling the evolution of social organization. In this paper, we assess the relative importance of contest and scramble food competition on the social dynamics of a provisioned semi-free-ranging Cebus apella group (n=18). Individuals competed directly for provisioned and clumped foods. Effects of indirect competition were apparent with individuals foraging in different areas and with increased group dispersion during periods of low food abundance. We suggest that both forms of competition can act simultaneously and to some extent synergistically in their influence on social dynamics; the combination of social and ecological opportunities for competition and how those opportunities are exploited both influence the nature of the relationships within social groups of primates and underlie the evolved social structure. Copyright (c) 2008 S. Karger AG, Basel

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) semi-supervised classification model is proposed. It employs a combined random-greedy walk of particles, with competition and cooperation mechanisms, to propagate class labels to the whole network. Due to the competition mechanism, the proposed model has a local label spreading fashion, i.e., each particle only visits a portion of nodes potentially belonging to it, while it is not allowed to visit those nodes definitely occupied by particles of other classes. In this way, a "divide-and-conquer" effect is naturally embedded in the model. As a result, the proposed model can achieve a good classification rate while exhibiting low computational complexity order in comparison to other network-based semi-supervised algorithms. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method.

Describing the Situational Contexts of Sweetened Product Consumption in a Middle Eastern Canadian Community: Application of a Mixed Method Design

Little is known about the situational contexts in which individuals consume processed sources of dietary sugars. This study aimed to describe the situational contexts associated with the consumption of sweetened food and drink products in a Catholic Middle Eastern Canadian community. A two-stage exploratory sequential mixed-method design was employed with a rationale of triangulation. In stage 1 (n = 62), items and themes describing the situational contexts of sweetened food and drink product consumption were identified from semi-structured interviews and were used to develop the content for the Situational Context Instrument for Sweetened Product Consumption (SCISPC). Face validity, readability and cultural relevance of the instrument were assessed. In stage 2 (n = 192), a cross-sectional study was conducted and exploratory factor analysis was used to examine the structure of themes that emerged from the qualitative analysis as a means of furthering construct validation. The SCISPC reliability and predictive validity on the daily consumption of sweetened products were also assessed. In stage 1, six themes and 40-items describing the situational contexts of sweetened product consumption emerged from the qualitative analysis and were used to construct the first draft of the SCISPC. In stage 2, factor analysis enabled the clarification and/or expansion of the instrument's initial thematic structure. The revised SCISPC has seven factors and 31 items describing the situational contexts of sweetened product consumption. Initial validation of the instrument indicated it has excellent internal consistency and adequate test-retest reliability. Two factors of the SCISPC had predictive validity for the daily consumption of total sugar from sweetened products (Snacking and Energy demands) while the other factors (Socialization, Indulgence, Constraints, Visual Stimuli and Emotional needs) were rather associated to occasional consumption of these products.

Generating unconstrained two-dimensional non-guillotine cutting patterns by a Recursive Partitioning Algorithm

In this study, a dynamic programming approach to deal with the unconstrained two-dimensional non-guillotine cutting problem is presented. The method extends the recently introduced recursive partitioning approach for the manufacturer's pallet loading problem. The approach involves two phases and uses bounds based on unconstrained two-staged and non-staged guillotine cutting. The method is able to find the optimal cutting pattern of a large number of pro blem instances of moderate sizes known in the literature and a counterexample for which the approach fails to find known optimal solutions was not found. For the instances that the required computer runtime is excessive, the approach is combined with simple heuristics to reduce its running time. Detailed numerical experiments show the reliability of the method. Journal of the Operational Research Society (2012) 63, 183-200. doi: 10.1057/jors.2011.6 Published online 17 August 2011

Semi-supervised learning guided by the modularity measure in complex networks

Semi-supervised learning techniques have gained increasing attention in the machine learning community, as a result of two main factors: (1) the available data is exponentially increasing; (2) the task of data labeling is cumbersome and expensive, involving human experts in the process. In this paper, we propose a network-based semi-supervised learning method inspired by the modularity greedy algorithm, which was originally applied for unsupervised learning. Changes have been made in the process of modularity maximization in a way to adapt the model to propagate labels throughout the network. Furthermore, a network reduction technique is introduced, as well as an extensive analysis of its impact on the network. Computer simulations are performed for artificial and real-world databases, providing a numerical quantitative basis for the performance of the proposed method.

AN EFFICIENT HPLC-UV METHOD FOR THE QUANTITATIVE DETERMINATION OF CEFADROXIL IN HUMAN PLASMA AND ITS APPLICATION IN PHARMACOKINETIC STUDIES

Cefadroxil is a semi-synthetic first-generation oral cephalosporin used in the treatment of mild to moderate infections of the respiratory and urinary tracts, skin and soft tissue infections. In this work a simple, rapid, economic and sensitive HPLC-UV method is described for the quantitative determination of cefadroxil in human plasma samples using lamivudine as internal standard. Sample pre-treatment was accomplished through protein precipitation with acetonitrile and chromatographic separation was performed with a mobile phase consisting of a mixture of sodium dihydrogen phosphate monohydrate solution, methanol and acetonitrile in the ratio of 90:8:2 (v/v/v) at a flow rate of 1.0mL/min. The proposed method is linear between 0.4 to 40.0 mu g/mL and its average recovery is 102.21% for cefadroxil and 97.94% for lamivudine. The method is simple, sensitive, reproducible, less time consuming for determination of cefadroxil in human plasma. The method can therefore be recommended for pharmacokinetics studies, including bioavailability and bioequivalence studies.

Semi-supervised dimensionality reduction based on partial least squares for visual analysis of high dimensional data

Dimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve data segregation on reduced or visual spaces, they have limited capabilities for adjusting the results according to user's knowledge. In this paper, we propose a novel approach to handling both dimensionality reduction and visualization of high dimensional data, taking into account user's input. It employs Partial Least Squares (PLS), a statistical tool to perform retrieval of latent spaces focusing on the discriminability of the data. The method employs a training set for building a highly precise model that can then be applied to a much larger data set very effectively. The reduced data set can be exhibited using various existing visualization techniques. The training data is important to code user's knowledge into the loop. However, this work also devises a strategy for calculating PLS reduced spaces when no training data is available. The approach produces increasingly precise visual mappings as the user feeds back his or her knowledge and is capable of working with small and unbalanced training sets.