A network-based approach for predicting key enzymes explaining metabolite abundance alterations in a disease phenotype

<p>Background The study of metabolism has attracted much attention during the last years due to its relevance in various diseases. The advance in metabolomics platforms allows us to detect an increasing number of metabolites in abnormal high/low concentration in a disease phenotype. Finding a mechanistic interpretation for these alterations is important to understand pathophysiological processes, however it is not an easy task. The availability of genome scale metabolic networks and Systems Biology techniques open new avenues to address this question.</p> <p>Results In this article we present a novel mathematical framework to find enzymes whose malfunction explains the accumulation/depletion of a given metabolite in a disease phenotype. Our approach is based on a recently introduced pathway concept termed Carbon Flux Paths (CFPs), which extends classical topological definition by including network stoichiometry. Using CFPs, we determine the Connectivity Curve of an altered metabolite, which allows us to quantify changes in its pathway structure when a certain enzyme is removed. The influence of enzyme removal is then ranked and used to explain the accumulation/depletion of such metabolite. For illustration, we center our study in the accumulation of two metabolites (L-Cystine and Homocysteine) found in high concentration in the brain of patients with mental disorders. Our results were discussed based on literature and found a good agreement with previously reported mechanisms. In addition, we hypothesize a novel role of several enzymes for the accumulation of these metabolites, which opens new strategies to understand the metabolic processes underlying these diseases.</p> <p>Conclusions With personalized medicine on the horizon, metabolomic platforms are providing us with a vast amount of experimental data for a number of complex diseases. Our approach provides a novel apparatus to rationally investigate and understand metabolite alterations under disease phenotypes. This work contributes to the development of Systems Medicine, whose objective is to answer clinical questions based on theoretical methods and high-throughput “omics” data.</p&gt

Gate-controlled conductance through bilayer graphene ribbons

We study the conductance of a biased bilayer graphene flake with monolayer nanoribbon contacts. We find that the transmission through the bilayer ribbon strongly depends on the applied bias between the two layers and on the relative position of the monolayer contacts. Besides the opening of an energy gap on the bilayer, the bias allows to tune the electronic density on the bilayer flake, making possible the control of the electronic transmission by an external parameter.Comment: 5 pages, 5 figures include

Using synchronization to improve earthquake forecasting in a cellular automaton model

A new forecasting strategy for stochastic systems is introduced. It is inspired by the concept of anticipated synchronization between pairs of chaotic oscillators, recently developed in the area of Dynamical Systems, and by the earthquake forecasting algorithms in which different pattern recognition functions are used for identifying seismic premonitory phenomena. In the new strategy, copies (clones) of the original system (the master) are defined, and they are driven using rules that tend to synchronize them with the master dynamics. The observation of definite patterns in the state of the clones is the signal for connecting an alarm in the original system that efficiently marks the impending occurrence of a catastrophic event. The power of this method is quantitatively illustrated by forecasting the occurrence of characteristic earthquakes in the so-called Minimalist Model.Comment: 4 pages, 3 figure

COVID-19 Mortality Risk Prediction Using X-Ray Images

The pandemic caused by coronavirus COVID-19 has already had a massive impact in our societies in terms of health, economy, and social distress. One of the most common symptoms caused by COVID-19 are lung problems like pneumonia, which can be detected using X-ray images. On the other hand, the popularity of Machine Learning models has grown exponentially in recent years and Deep Learning techniques have become the state-of-the-art for image classification tasks and is widely used in the healthcare sector nowadays as support for clinical decisions. This research aims to build a prediction model based on Machine Learning, including Deep Learning, techniques to predict the mortality risk of a particular patient given an X-ray and some basic demographic data. Keeping this in mind, this paper has three goals. First, we use Deep Learning models to predict the mortality risk of a patient based on this patient X-ray images. For this purpose, we apply Convolutional Neural Networks as well as Transfer Learning techniques to mitigate the effect of the reduced amount of COVID19 data available. Second, we propose to combine the prediction of this Convolutional Neural Network with other patient data, like gender and age, as input features of a final Machine Learning model, that will act as second and final layer. This second model layer will aim to improve the goodness of fit and prediction power of our first layer. Finally, and in accordance with the principle of reproducible research, the data used for the experiments is publicly available and we make the implementations developed easily accessible via public repositories. Experiments over a real dataset of COVID-19 patients yield high AUROC values and show our two-layer framework to obtain better results than a single Convolutional Neural Network (CNN) model, achieving close to perfect classification

Procesos de alteración de materiales pétreos en edificios de interés histórico

This is a general survey of the different stages in the technicaldiagnostic activities carried out at present on the conservation state of monuments previous to restoration.Diagnostic studies are commonly hased on the effects of pollution (external factor), and on the study of rock porosity and its hydric properties (interna1 factors). Other alteration processes may also be caused by the mineralogical nature, as well as the crystallochemical characteristics of the rock. These mechanisms may be determinig factors that can go unnoticed if no in-depth petroiogicai and crystallochemical studies are carried out, especially those using the new techniques of electron microscopy and electron drilling.Here a rock of Miocenic age from the " Covas del Llorito" near Tarragona quarries is described. This partially dolomitized calcisiltite presents a zoned idiotypic fabric, with an anomalous intracrystalline distribution of calcium and magnesium, non-stechiomehic and deficient in magnesium. These crystalls undergo a differential disolution of their nuclei, wich produces abundan1 intracrystalline moldic porosity, and subsequent disaggregation and the formation of sand. This predisposition to alteration, of diagenetic origin, is speeded up by existing gypsum efflorescences, external to the rock

Limpieza real de costra negra de contaminación en arenisca silícea con láser de elevado pulso de repetición: efectos morfológicos en la superficie

This research project studies the role of pulse repetition rate in laser removal of black soiling crust from siliceous sandstone, and specifically, how laser fluence correlates with high pulse repetition rates in cleaning practice. The aim is to define practical cleaning processes and determine simple techniques for evaluation based on end-users’ perspective (restorers). Spot and surface tests were made using a Q-switched Nd:YAG laser system with a wide range of pulse repetition rates (5–200 Hz), systematically analysed and compared by macrophotography, portable microscope, stereomicroscope with 3D visualizing and area roughness measurements, SEM imaging and spectrophotometry. The results allow the conclusion that for operation under high pulse repetition rates the average of total energy applied per spot on a treated surface should be attendant upon fluence values in order to provide a systematic and accurate description of an actual laser cleaning intervention.En este trabajo se estudia el papel de la frecuencia de repetición en la limpieza láser de costras de contaminación sobre una arenisca silícea, y concretamente, como se relaciona fluencia y frecuencias elevadas en una limpieza real. Se pretende definir un procedimiento práctico de limpieza y determinar técnicas sencillas de evaluación desde el punto de vista de los usuarios finales (restauradores). Para el estudio se realizaron diferentes ensayos en spot y en superficie mediante un equipo Q-switched Nd:YAG con un amplio rango de frecuencias (5–200 Hz), que se analizaron y compararon sistemáticamente mediante macrofotografía, microscopio portátil, estereomicroscopio con visualización 3D y mediciones de rugosidad en área, imágenes SEM y espectrofotometría. Los resultados permiten proponer que, al trabajar con altas frecuencias, la media de la energía total depositada por spot en la superficie debería acompañar los valores de fluencia para describir y comprender mejor una limpieza real con láser

Efficient formalism for large scale ab initio molecular dynamics based on time-dependent density functional theory

A new "on the fly" method to perform Born-Oppenheimer ab initio molecular dynamics (AIMD) is presented. Inspired by Ehrenfest dynamics in time-dependent density functional theory, the electronic orbitals are evolved by a Schroedinger-like equation, where the orbital time derivative is multiplied by a parameter. This parameter controls the time scale of the fictitious electronic motion and speeds up the calculations with respect to standard Ehrenfest dynamics. In contrast to other methods, wave function orthogonality needs not be imposed as it is automatically preserved, which is of paramount relevance for large scale AIMD simulations.Comment: 5 pages, 3 color figures, revtex4 packag

Clauser-Horne inequality and decoherence in mesoscopic conductors

We analyze the effect of decoherence on the violation of the Clauser-Horne (CH) inequality for the full electron counting statistics in a mesoscopic multiterminal conductor. Our setup consists of an entangler that emits a flux of entangled electrons into two conductors characterized by a scattering matrix and subject to decoherence. Loss of phase memory is modeled phenomenologically by introducing fictitious extra leads. The outgoing electrons are detected using spin-sensitive electron counters. Given a certain average number of incoming entangled electrons, the CH inequality is evaluated as a function of the numbers of detected particles and on the various quantities characterizing the scattering matrix. When decoherence is turned on, we show that the amount of violation of the CH inequality is effectively reduced. Interestingly we find that, by adjusting the parameters of the system, there exists a protected region of $Q$ values for which violation holds for arbitrary strong decoherence.Comment: 14 pages, 10 figures. Published versio

High precision quantum control of single donor spins in silicon

The Stark shift of the hyperfine coupling constant is investigated for a P donor in Si far below the ionization regime in the presence of interfaces using Tight-binding and Band Minima Basis approaches and compared to the recent precision measurements. The TB electronic structure calculations included over 3 million atoms. In contrast to previous effective mass based results, the quadratic Stark coefficient obtained from both theories agrees closely with the experiments. This work represents the most sensitive and precise comparison between theory and experiment for single donor spin control. It is also shown that there is a significant linear Stark effect for an impurity near the interface, whereas, far from the interface, the quadratic Stark effect dominates. Such precise control of single donor spin states is required particularly in quantum computing applications of single donor electronics, which forms the driving motivation of this work.Comment: 5 pages, 2 figure