Combining adapted Judo training and pharmacological treatment to improve bone mineral density on postmenopausal women: A two years study

Background & Study Aim: Physical activity has been an important factor to increase bone mineral density (BMD) and, consequently, to prevent and treat osteoporosis. The study aimed the effects of adapted Judo training on BMD in postmenopausal women, during pharmacological treatment. Material & Methods: Eighteen female volunteers participated in this study. They were separated into two groups: Adapted Judo training (AJT) (n=11; 52.2±5.3 years) and control group (CG) (n=7; 53.8±4.4 years). Lunar GE Dual Energy X-Ray Absorptiometry (DXA) measured BMD at lumbar L2-L4, femoral neck and trochanter sites. The training period for AJT was two years, comprised 12 mesocycles with different intensities. ANOVA compared 2 groups in 3 moments of testing and Scheffé Test allowed multiple comparisons between groups for the L2-L4 and femoral neck sites, but at trochanter was Fisher LSD. Results: ANOVA showed significant differences in the AJT group (F(2, 32)=15.187, p=0.000023). Scheffé Test showed significant increase on lumbar BMD after one year of AJT (Δ%=+8.9%, p=0.000017) and after two years this improvement stand still (p=0.33). The CG after one year presented significant decrease in BMD of femoral neck (Δ%=-6.9%, p=0.03) and trochanter (Δ%=-3.7%, p=0.0084). However, the CG recovered the loss of BMD of femoral neck (Δ%=+7.6%, p=0.02) and trochanter (Δ%=+3.8%, p=0.0079) after two years of study. Conclusions: Drug therapy, without the physical activity practice, can aid the maintenance of BMD. AJT may be considered as an efficient physical activity for postmenopausal women with low BMD in pharmacological treatment. © ARCHIVES OF BUDO | SCIENCE OF MARTIAL ARTS.

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

Facilitation of sodium intake by combining noradrenaline into the lateral parabrachial nucleus with prazosin peripherally

Injections of noradrenaline into the lateral parabrachial nucleus (LPBN) increase arterial pressure and 1.8% NaCl intake and decrease water intake in rats treated with the diuretic furosemide (FURO) combined with a low dose of the angiotensin converting enzyme inhibitor captopril (CAP). In the present study, we investigated the influence of the pressor response elicited by noradrenaline injected into the LPBN on FURO + CAP-induced water and 1.8% NaCl intake. Male Holtzman rats with bilateral stainless steel guide-cannulas implanted into LPBN were used. Bilateral injections of noradrenaline (40 nmol/0.2 μl) into the LPBN increased FURO + CAP-induced 1.8% NaCl intake (12.2 ± 3.5, vs., saline: 4.2 ± 0.8 ml/180 min), reduced water intake and strongly increased arterial pressure (50 ± 7, vs. saline: 1 ± 1 mm Hg). The blockade of the α1 adrenoceptors with the prazosin injected intraperitoneally abolished the pressor response and increased 1.8% NaCl and water intake in rats treated with FURO + CAP combined with noradrenaline injected into the LPBN. The deactivation of baro and perhaps volume receptors due to the cardiovascular effects of prazosin is a mechanism that may facilitate water and NaCl intake in rats treated with FURO + CAP combined with noradrenaline injected into the LPBN. Therefore, the activation of α2 adrenoceptors with noradrenaline injected into the LPBN, at least in dose tested, may not completely remove the inhibitory signals produced by the activation of the cardiovascular receptors, particularly the signals that result from the extra activation of these receptors with the increase of arterial pressure. © 2013 Elsevier Inc.

Combining anisotropic diffusion, transport equation and texture synthesis for inpainting textured images

In this work we propose a new image inpainting technique that combines texture synthesis, anisotropic diffusion, transport equation and a new sampling mechanism designed to alleviate the computational burden of the inpainting process. Given an image to be inpainted, anisotropic diffusion is initially applied to generate a cartoon image. A block-based inpainting approach is then applied so that to combine the cartoon image and a measure based on transport equation that dictates the priority on which pixels are filled. A sampling region is then defined dynamically so as to hold the propagation of the edges towards image structures while avoiding unnecessary searches during the completion process. Finally, a cartoon-based metric is computed to measure likeness between target and candidate blocks. Experimental results and comparisons against existing techniques attest the good performance and flexibility of our technique when dealing with real and synthetic images. © 2013 Elsevier B.V. All rights reserved.

Economic aspects of combining thermal and hydroelectric plants

Includes bibliography

Combining hydro and thermal capacity results in maximum economic benefits

Includes bibliography

Mexico: Combining monthly inflation predictions from surveys

We examine the problem of combining Mexican inflation predictions or projections provided by a biweekly survey of professional forecasters. Consumer price inflation in Mexico is measured twice a month. We consider several combining methods and advocate the use of dimension reduction techniques whose performance is compared with different benchmark methods, including the simplest average prediction. Missing values in the database are imputed by two different databased methods. The results obtained are basically robust to the choice of the imputation method. A preliminary analysis of the data was based on its panel data structure and showed the potential usefulness of using dimension reduction techniques to combine the experts' predictions. The main findings are: the first monthly predictions are best combined by way of the first principal component of the predictions available; the best second monthly prediction is obtained by calculating the median prediction and is more accurate than the first one.

Post-partum anoestrus in tropical beef cattle: A systems approach combining gene expression and genome-wide association results

The length of the post-partum anoestrous interval affects reproductive efficiency in many tropical beef cattle herds. In this study, results from genome-wide association studies (Experiment 1: GWAS) and gene expression (Experiment 2: microarray) were combined in a systems approach to reveal genetic markers, genes and pathways underlying the physiology of post-partum anoestrus in tropically adapted cattle. The microarray study measured the expression of 13,964 genes in the hypothalamus of Brahman cows. A total of 366 genes were differentially expressed (DE) in the post-partum period, when acyclic cows were compared to cows that had resumed ovarian cycles. Associated markers (P < 0.05) from a high density GWAS pointed to 2829 genes that were associated with post-partum anoestrous interval (PPAI) in two populations of beef cattle: Brahman and Tropical composite. Together the experiments provided evidence for 63 genes that are likely to influence the resumption of ovulation post-partum in tropically adapted beef cattle. Functional annotation analysis revealed that some of the 63 genes have known roles in hormonal activity, energy balance and neuronal synapse plasticity. Polymorphisms within candidate genes identified by this systems approach could have biological significance in post-partum anoestrus and help select Zebu (Bos indicus) influenced cattle with genetic potential for shorter post-partum anoestrus. Crown Copyright (C) 2014 Published by Elsevier B.V. All rights reserved.

Combining Experimental Evidence and Molecular Dynamic Simulations To Understand the Mechanism of Action of the Antimicrobial Octapeptide Jelleine-I

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Sodium intake combining cholinergic activation and noradrenaline into the lateral parabrachial nucleus

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Combining xanthan and chitosan membranes to multipotent mesenchymal stromal cells as bioactive dressings for dermo-epidermal wounds

The association between tridimensional scaffolds to cells of interest has provided excellent perspectives for obtaining viable complex tissues in vitro, such as skin, resulting in impressive advances in the field of tissue engineering applied to regenerative therapies. The use of multipotent mesenchymal stromal cells in the treatment of dermo-epidermal wounds is particularly promising due to several relevant properties of these cells, such as high capacity of proliferation in culture, potential of differentiation in multiple skin cell types, important paracrine and immunomodulatory effects, among others. Membranes of chitosan complexed with xanthan may be potentially useful as scaffolds for multipotent mesenchymal stromal cells, given that they present suitable physico-chemical characteristics and have adequate tridimensional structure for the adhesion, growth, and maintenance of cell function. Therefore, the purpose of this work was to assess the applicability of bioactive dressings associating dense and porous chitosan-xanthan membranes to multipotent mesenchymal stromal cells for the treatment of skin wounds. The membranes showed to be non-mutagenic and allowed efficient adhesion and proliferation of the mesenchymal stromal cells in vitro. In vivo assays performed with mesenchymal stromal cells grown on the surface of the dense membranes showed acceleration of wound healing in Wistar rats, thus indicating that the use of this cell-scaffold association for tissue engineering purposes is feasible and attractive.

Encapsulation of paclitaxel into a bio-nanocomposite. a study combining inelastic neutron scattering to thermal analysis and infrared spectroscopy

The anticancer drug paclitaxel was encapsulated into a bio-nanocomposite formed by magnetic nanoparticles, chitosan and apatite. The aim of this drug carrier is to provide a new perspective against breast cancer. The dynamics of the pure and encapsulated drug were investigated in order to verify possible molecular changes caused by the encapsulation, as well as to follow which interactions may occur between paclitaxel and the composite. Fourier transformed infrared spectroscopy, thermal analysis, inelastic and quasi-elastic neutron scattering experiments were performed. These very preliminary results suggest the successful encapsulation of the drug.

Combining plant and bird data increases the accuracy of an Index of Biotic Integrity to assess conservation levels of tropical forest fragments

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Combining ALOS/PALSAR derived vegetation structure and inundation patterns to characterize major vegetation types in the Mamiraua Sustainable Development Reserve, Central Amazon floodplain, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Semiautomatic object-space road extraction combining a stereoscopic image pair and a TIN-Based DTM

In this letter, a semiautomatic method for road extraction in object space is proposed that combines a stereoscopic pair of low-resolution aerial images with a digital terrain model (DTM) structured as a triangulated irregular network (TIN). First, we formulate an objective function in the object space to allow the modeling of roads in 3-D. In this model, the TIN-based DTM allows the search for the optimal polyline to be restricted along a narrow band that is overlaid upon it. Finally, the optimal polyline for each road is obtained by optimizing the objective function using the dynamic programming optimization algorithm. A few seed points need to be supplied by an operator. To evaluate the performance of the proposed method, a set of experiments was designed using two stereoscopic pairs of low-resolution aerial images and a TIN-based DTM with an average resolution of 1 m. The experimental results showed that the proposed method worked properly, even when faced with anomalies along roads, such as obstructions caused by shadows and trees.