Bone tissue response to four-month antiorthostatic bedrest: a bone histomorphometric study

A histomorphometric analysis were made on iliac crest biopsies from eight healthy male volunteers submitted to a 4-month antiorthostatic bedrest. Bone mass and bone cell parameters, reflecting resorption and formation activities, were measured before and after the bedrest period. Trabecular bone volume and mean cortical thickness were not modified despite a decreased number of trabeculae and nonsignificant increase of the trabecular thickness; total and active resorption surfaces and the number of osteoclast per mm2 of trabecular surfaces do not vary significantly. Osteoid thickness does not vary but we found a reduced osteoid surface and a nonsignificant decreased osteoid volume. Our results suggest that bone architecture may be more affected by the reduction of mechanical forces than the bone mass. These modifications were supposed to be the result of an accelerated bone turnover in the early stage of immobilization. In this study, we failed to find disuse osteoporosis; however, we must point out that the new organization of the trabeculae could affect the bone mechanical properties.     

A Learning Rule to Model the Development of Orientation Selectivity in Visual Cortex

This paper presents a learning rule, CBA, to develop oriented receptive fields similar to those founded in cat striate cortex. The inherent complexity of the development of selectivity in visual cortex has led most authors to test their models by using a restricted input environment. Only recently, some learning rules (the PCA and the BCM rules) have been studied in a realistic visual environment. For these rules, which are based upon Hebbian learning, single neuron models have been proposed in order to get a better understanding of their properties and dynamics. These models suffered from unbounded growing of synaptic strength, which is remedied by a normalization process. However, normalization seems biologically implausible, given the non-local nature of this process. A detailed stability analysis of the proposed rule proves that the CBA attains a stable state without any need for normalization. Also, a comparison among the results achieved in different types of visual environments by the PCA, the BCM and the CBA rules is provided. The final results show that the CBA rule is appropriate for studying the biological process of receptive field formation and its application in image processing and artificial vision tasks.     

Exploration of Vanilla pompona from the Peruvian Amazon as a potential source of vanilla essence: Quantification of phenolics by HPLC-DAD

This study provides the first chemical investigation of wild-harvested fruits of Vanilla pompona ssp. grandiflora (Lindl.) Soto-Arenas developed in their natural habitat in the Peruvian Amazon. Flowers were hand-pollinated and the resulting fruits were analysed at different developmental stages using an HPLC-DAD method validated for the quantification of glucovanillin and seven other compounds. The method showed satisfactory linearity (r² > 0.9969), precision (coefficient of variation <2%), recoveries (70–100%), limit of detection (0.008–0.212 μg/ml), and limit of quantification (0.027–0.707 μg/ml). The evaluation of crude and enzyme-hydrolyzed Soxhlet-extracted samples confirmed the leading role of glucosides in fruit development. LC–ESI-MS studies corroborated the identities of four glucosides and seven aglycones, among them vanillin (5.7/100 g), 4-hydroxybenzyl alcohol (3.6/100 g), and anisyl alcohol (7.1/100 g) were found in high concentrations. The attractive flavor/aroma profile exhibited by wild V. pompona fruits supports studies focused on the development of this species as a specialty crop.     

Deep Neural Networks for Wind and Solar Energy Prediction

Deep Learning models are recently receiving a large attention because of their very powerful modeling abilities, particularly on inputs that have a intrinsic one- or two-dimensional structure that can be captured and exploited by convolutional layers. In this work we will apply Deep Neural Networks (DNNs) in two problems, wind energy and daily solar radiation prediction, whose inputs, derived from Numerical Weather Prediction systems, have a clear spatial structure. As we shall see, the predictions of single deep models and, more so, of DNN ensembles can improve on those of Support Vector Regression, a Machine Learning method that can be considered the state of the art for regression.     

Scattering by a finite set of perfectly conducting cylinders buried in a dielectric half-space: a spectral-domain solution

An analytical-numerical technique, for the solution of the two-dimensional electromagnetic plane-wave scattering by a finite set of perfectly conducting circular cylinders buried in a dielectric half-space, is presented. The problem is solved for both the near- and the far-field regions, for TM and TE polarizations. The diffracted field is represented in terms of a superposition of cylindrical waves and use is made of the plane-wave spectrum to take into account the reflection and transmission of such waves by the interface. The validity of the approach is confirmed by comparisons with results available in the literature, with very good agreement. The multiple interactions between two buried cylinders have been studied by considering both the induced currents and the scattered field diagrams. Applications of the method to objects of arbitrary cross-section simulated by a suitable configuration of circular cylinders are shown.     

"Osteoclast-like' giant cells in a feline mammary carcinoma

The authors describe the first case of mammary carcinoma with 'osteoclast-like' giant cells (OGCs) in a cat. The histological, immunohistochemical and ultrastructural findings observed show many similarities between feline and human mammary carcinomas with OGCs and support the opinion that cats suffering from mammary carcinoma can represent a useful animal model for human disease.     

Tracking the time-varying cortical connectivity patterns by adaptive multivariate estimators

The directed transfer function (DTF) and the partial directed coherence (PDC) are frequency-domain estimators that are able to describe interactions between cortical areas in terms of the concept of Granger causality. However, the classical estimation of these methods is based on the multivariate autoregressive modelling (MVAR) of time series, which requires the stationarity of the signals. In this way, transient pathways of information transfer remains hidden. The objective of this study is to test a time-varying multivariate method for the estimation of rapidly changing connectivity relationships between cortical areas of the human brain, based on DTF/PDC and on the use of adaptive MVAR modelling (AMVAR) and to apply it to a set of real high resolution EEG data. This approach will allow the observation of rapidly changing influences between the cortical areas during the execution of a task. The simulation results indicated that time-varying DTF and PDC are able to estimate correctly the imposed connectivity patterns under reasonable operative conditions of signal-to-noise ratio (SNR) ad number of trials. An SNR of five and a number of trials of at least 20 provide a good accuracy in the estimation. After testing the method by the simulation study, we provide an application to the cortical estimations obtained from high resolution EEG data recorded from a group of healthy subject during a combined foot-lips movement and present the time-varying connectivity patterns resulting from the application of both DTF and PDC. Two different cortical networks were detected with the proposed methods, one constant across the task and the other evolving during the preparation of the joint movement.     

Role of the extracellular domain of human herpesvirus 7 glycoprotein B in virus binding to cell surface heparan sulfate proteoglycans

In an attempt to identify the human herpesvirus 7 (HHV-7) envelope protein(s) involved in cell surface binding, the extracellular domain of the HHV-7 glycoprotein B (gB) homolog protein was cloned and expressed as a fusion product with the Fc domain of human immunoglobulin G heavy chain gamma1 (gB-Fc) in an eukaryotic cell system. Indirect immunofluorescence followed by flow cytometric analysis revealed specific binding of gB-Fc to the membrane of SupT1 cells but not to other CD4+ T-lymphoblastoid cell lines, such as Jurkat or PM1, clearly indicating that gB-Fc did not bind to the CD4 molecule. This was also suggested by the ability of gB-Fc to bind to CD4-negative fibroblastoid Chinese hamster ovary (CHO) cells. The binding was abrogated by enzymatic removal of cell surface heparan sulfate proteoglycans by heparinase and heparitinase but not by treatment with condroitinase ABC. In addition, binding of the gB-Fc fusion protein to CHO cells was severely impaired in the presence of soluble heparin, as well as when heparan sulfate-deficient mutant CHO cells were used. Consistent with these findings, soluble heparin was found to block HHV-7 infection and syncytium formation in the SupT1 cell line. Although the CD4 antigen is a critical component of the receptor for the T-lymphotropic HHV-7, these findings suggest that heparin-like molecules also play an important role in HHV-7-cell surface interactions required for infection and that gB represents one of the HHV-7 envelope proteins involved in the adsorption of virus-to-cell surface proteoglycans.     

Improved algorithms for automatic bone histomorphometry on a numerized image analysis system

Quantitative histological methods have proved to be the most effective methods in bone disease research. Faster and more accurate techniques are currently needed. We have developed a simple digitized image analysis system which allows accurate measurements of trabecular bone mass. The algorithm is based on the 'four-connected sets' mathematical theory. Given a numerized image displayed by a CCD camera, the algorithm recognizes all possible four-connected sets and provides area measurements. The first procedure automatically eliminates small, irrelevant profiles (wrinkles, cell nuclei, etc.) while larger profiles are erased interactively. The second procedure similarly erases the artefactual defects within the trabecule (artefactual cracks or empty osteocytic lacunae). The method was shown to be very accurate and time-saving.