Proteome alterations induced in human white blood cells by consumption of Brussels sprouts: Results of a pilot intervention study

Epidemiological studies indicate a correlation of cruciferous vegetables consumption with reduced incidence of cancer. This study was designed to investigate molecular mechanisms, which may help to understand the beneficial effects of Brussels sprout consumption. In order to avoid the limitations of in vitro model systems, we performed a dietary intervention study with five participants. We investigated, whether sprout consumption affects the proteome profile of primary white blood cells. In order to achieve maximal sensitivity in detecting specific adaptive proteome alterations, we metabolically labelled freshly isolated cells in the presence of ³⁵S‐methionine/cysteine and performed autoradiographic quantification of protein synthesis. Proteins were separated by 2‐DE and spots of interest were cut out, digested and identified by MS. After the intervention, we found a significant up‐regulation of the synthesis of manganese superoxide dismutase (1.56‐fold) and significant down‐regulation of the synthesis of heat shock 70 kDa protein (hsp70; 2.27‐fold). Both proteins play a role in malignant transformation of cells. Hsp‐70 is involved in the regulation of apoptosis, which leads to elimination of cancer cells, while SOD plays a key role in protection against reactive oxygen species mediated effects. Our findings indicate that the alteration of the synthesis of these proteins may be involved in the anticarcinogenic effects of cruciferous vegetables, which was observed in earlier laboratory studies with animals.     

Device for characterization of thermal effusivity of liquids using photothermal beam deflection

We propose and study a novel optoelectronic device for thermal characterization of materials. It is based on monitoring the photothermal deflection of a laser beam within a slab of a thermo-optic material in thermal contact with the sample under study. An optical angle sensor is used to measure the laser deflection providing a simple and experimental arrangement. We demonstrate its principle and a simple procedure to measure thermal effusivity of liquids. The proposed device could be implemented into a compact sensor head for remote measurements using electrical and fiber optic links.     

Ab initio determination of heavy oxide perovskite related structures from precession electron diffraction data

Two complex perovskite-related structures were solved by ab initio from precession electron diffraction intensities. Structure models were firstly derived from HREM images and than have been confirmed independently using two and three-dimensional sets of precession intensities. Patterson techniques prove to be effective for ab initio structure resolution, specially in case of projections with no overlapping atoms. Quality of precession intensity data may be suitable enough to resolve unknown heavy oxide structures.     

Gaussian mean-shift is an EM algorithm

The mean-shift algorithm, based on ideas proposed by Fukunaga and Hosteller, is a hill-climbing algorithm on the density defined by a finite mixture or a kernel density estimate. Mean-shift can be used as a nonparametric clustering method and has attracted recent attention in computer vision applications such as image segmentation or tracking. We show that, when the kernel is Gaussian, mean-shift is an expectation-maximization (EM) algorithm and, when the kernel is non-Gaussian, mean-shift is a generalized EM algorithm. This implies that mean-shift converges from almost any starting point and that, in general, its convergence is of linear order. For Gaussian mean-shift, we show: 1) the rate of linear convergence approaches 0 (superlinear convergence) for very narrow or very wide kernels, but is often close to 1 (thus, extremely slow) for intermediate widths and exactly 1 (sublinear convergence) for widths at which modes merge, 2) the iterates approach the mode along the local principal component of the data points from the inside of the convex hull of the data points, and 3) the convergence domains are nonconvex and can be disconnected and show fractal behavior. We suggest ways of accelerating mean-shift based on the EM interpretation     

Simple multichannel system for the measurement of the net water flux across biological tissues

This paper describes the development of a simple system for measurement of net water movement through biological membrane barriers. The system is based on the detection of a water meniscus inside a polyethylene tube, which reflects the water movement inside one hemichamber of a modified Ussing chamber containing a membrane barrier. The detection device consists of a commercial computer-controlled flat bed scanner and specifically developed software. This system allows one to perform a relatively high number of individual experiments per physical unit. It is a flexible and affordable device, which allows comparatively more information per unit to be obtained than previously described methods.     

Guidance of a mobile robot using an array of static cameras located in the environment

This paper presents a new proposal for positioning and guiding mobile robots in indoor environments. The proposal is based on the information provided by static cameras located in the movement environment. This proposal falls within the scope of what are known as intelligent environments; in this case, the environment is provided with cameras that, once calibrated, allow the position of the robots to be obtained. Based on this information, control orders for the robots can be generated using a radio frequency link. In order to facilitate identification of the robots, even under extremely adverse ambient lighting conditions, a beacon consisting of four circular elements constructed from infrared diodes is mounted on board the robots. In order to identify the beacon, an edge detection process is carried out. This is followed by a process that, based on the algebraic distance, obtains the estimated ellipses associated with each element of the beacon. Once the beacon has been identified, the coordinates of the centroids for the elements that make up the beacon are obtained on the various image planes. Based on these coordinates, an algorithm is proposed that takes into account the standard deviation of the error produced in the various cameras in ascertaining the coordinates of the beacon’s elements. An odometric system is also used in guidance that, in conjunction with a Kalman Filter, allows the position of the robot to be estimated during the time intervals required to process the visual information provided by the cameras.

Local Stability of an Endoreversible Heat Engine Working in an Ecological Regime

We present a local stability analysis of an endoreversible engine working in an ecological regime, for three common heat transfer laws. From our local stability analysis we conclude that the system is stable for every value of the heat conductivity g, the heat capacity C and the ratio of temperatures with T ₁ > T ₂. After a small perturbation the system decays exponentially to the steady state determined by two different relaxation times. We observe that the stability of the system improves as increases whereas the steady-state energetic properties of the engine decline. Moreover, we compare the stability properties of the engine working in the ecological regime and under maximum power output. Finally, qualitative phase-space portraits for the evolution of the system are presented for representative cases.     

Protein radial distribution function (P-RDF) and Bayesian-Regularized Genetic Neural Networks for modeling protein conformational stability: chymotrypsin inhibitor 2 mutants

Development of novel computational approaches for modeling protein properties is a main goal in applied Proteomics. In this work, we reported the extension of the radial distribution function (RDF) scores formalism to proteins for encoding 3D structural information with modeling purposes. Protein-RDF (P-RDF) scores measure spherical distributions on protein 3D structure of 48 amino acids/residues properties selected from the AAindex data base. P-RDF scores were tested for building predictive models of the change of thermal unfolding Gibbs free energy change (DeltaDeltaG) of chymotrypsin inhibitor 2 upon mutations. In this sense, an ensemble of Bayesian-Regularized Genetic Neural Networks (BRGNNs) yielded an optimum nonlinear model for the conformational stability. The ensemble predictor described about 84% and 70% variance of the data in training and test sets, respectively.