A systematic review of the Trypanosoma cruzi genetic heterogeneity, host immune response and genetic factors as plausible drivers of chronic chagasic cardiomyopathy

Chagas disease is a complex tropical pathology caused by the kinetoplastid Trypanosoma cruzi. This parasite displays massive genetic diversity and has been classified by international consensus in at least six Discrete Typing Units (DTUs) that are broadly distributed in the American continent. The main clinical manifestation of the disease is the chronic chagasic cardiomyopathy (CCC) that is lethal in the infected individuals. However, one intriguing feature is that only 30-40% of the infected individuals will develop CCC. Some authors have suggested that the immune response, host genetic factors, virulence factors and even the massive genetic heterogeneity of T. cruzi are responsible of this clinical pattern. To date, no conclusive data support the reason why a few percentages of the infected individuals will develop CCC. Therefore, we decided to conduct a systematic review analysing the host genetic factors, immune response, cytokine production, virulence factors and the plausible association of the parasite DTUs and CCC. The epidemiological and clinical implications are herein discussed. © Cambridge University Press 2018

Pulmonary thromboembolism and alveolar hemorrhage as initial manifestations of systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disease that affects multiple organs. SLE can affect the lung, the pulmonary vasculature, and the pleura. A 38-year-old female with limb pain and ecchymosis who later developed pulmonary thromboembolism and alveolar hemorrhage is presented here. Clinical, imaging, laboratory, and histopathological evidence is presented. The patient met the European League Against Rheumatism (EULAR) and the American College of Rheumatology (ACR) criteria for SLE. Furthermore, the patient had a Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) score of 35; thus, indicating severe disease. This case is an example of concomitant venous and arterial lung complications in an SLE patient

The Association Between Abdominal Fat, Cardiorespiratory Fitness, and Clinical Markers of Metabolic Syndrome

Our purpose was to determine the association between abdominal fat and cardiorespiratory fitness (CRF) on markers of metabolic syndrome (MetS) total cholesterol (TC), high-density lipoprotein (HDL-C), low-density lipoprotein (LDL-C), triglycerides (TG), glucose, and blood pressure. We conducted a retrospective study on 165 adults (108 men) in which correlations between waist girth (WG), CRF and blood variables were determined. The cohort was partitioned by gender into quartiles and again by WG and differences in markers of MetS were compared across quartiles by ANOVA and by ANCOVA to determine the influence of CRF. Males in the lowest WG quartile exhibited greater HDL-C and lower diastolic blood pressure vs. the highest quartile (p < 0.05). TG were lower in the lowest vs. the third and highest quartile (p < 0.05), and glucose was greater in the highest vs. the first and second quartiles (p < 0.05). Females in the second WG quartile exhibited higher HDL-C vs. the highest quartile, and TG, glucose, systolic and diastolic blood pressure were lower in the lowest vs. the highest quartile (p < 0.05). After adjusting for CRF, diastolic blood pressure across WG in males were no longer significant, and    HLD-C and TG quartile differences were no longer significant in females. We confirm WG as an important correlate of clinical markers of MetS in adults. CRF mitigates relationships between WG and clinical markers of cardio-metabolic risk in men and women

Predictive Trading Strategy for Physical Electricity Futures

This article presents an original predictive strategy, based on a new mid-term forecasting model, to be used for trading physical electricity futures. The forecasting model is used to predict the average spot price, which is used to estimate the Risk Premium corresponding to electricity futures trade operations with a physical delivery. A feed-forward neural network trained with the extreme learning machine algorithm is used as the initial implementation of the forecasting model. The predictive strategy and the forecasting model only need information available from electricity derivatives and spot markets at the time of negotiation. In this paper, the predictive trading strategy has been applied successfully to the Iberian Electricity Market (MIBEL). The forecasting model was applied for the six types of maturities available for monthly futures in the MIBEL, from 1 to 6 months ahead. The forecasting model was trained with MIBEL price data corresponding to 44 months and the performances of the forecasting model and of the predictive strategy were tested with data corresponding to a further 12 months. Furthermore, a simpler forecasting model and three benchmark trading strategies are also presented and evaluated using the Risk Premium in the testing period, for comparative purposes. The results prove the advantages of the predictive strategy, even using the simpler forecasting model, which showed improvements over the conventional benchmark trading strategy, evincing an interesting hedging potential for electricity futures trading

Adiabatic lapse rate of real gases

We derive a formula for the dry adiabatic lapse rate of atmospheres composed of real gases. We restrict our study to those described by a family of two-parameter cubic equations of state and the recent Guevara-Rodríguez noncubic equation. Since our formula depends on the adiabatic curves, we compute them all at once, considering molecules that can move, rotate, and vibrate, for any equation of state. To illustrate our results, we estimate the lapse rate of the troposphere of Titan, obtaining a better approximation to the observed data in some instances, when compared to the estimation provided by the virial expansion up to the third order.B.D. acknowledges support from the CONEX-Plus programme funded by the Universidad Carlos III de Madrid and the European Union's Horizon 2020 research and innovation program under Marie Sklodowska-Curie Grant No. 801538. J.E.R. acknowledges financial support from the Consejo de Ciencia y Tecnología del Estado de Puebla. This work has been supported by the Spanish Ministerio de Ciencia Innovación y Universidades-Agencia Estatal de Investigación under Grant No. PID2020-116567GB-C22

Effect of Salmonella Typhimurium on the proteome of Pig Gut

Comunicaciones a congreso

Use and effectiveness of fly goalkeepers in european futsal

Using a fly goalkeeper (FG) is one of futsal´s most specific offensive strategy and gives leverage over the opponent to change the game''s final result. This study will analyze the goals obtained from the use of a FG and relate them to the score momentum variable and others in order to offer a better understanding and to establish if there are differences between main European futsal leagues. Sample made from all offensive situations that lead to a goal while using FG scheme (n=673) during 2014-2015 Spanish, Russian and Italian pro futsal leagues. Observational, nomothetic and multidimensional study. Statistical analysis using the SPSS vr 22 for inferential and descriptive statistics. Chi-square relation for cathegorical variables and Spearman''s Rho to establish non parametrical bi-varial correlations for ordinary variables, establishing significant differences p <0.05. FG strategy obtains 15.33% of the total goals. The league''s behaviour very similar, except in the Italian league, which scores more goals with their attack than against its defence, making differences between goals scored as local and visitor both in attack and defence

AIRPA: An Architecture to Support the Execution and Maintenance of AI-Powered RPA Robots

Robotic Process Automation (RPA) has quickly evolved from automating simple rule-based tasks. Nowadays, RPA is required to mimic more sophisticated human tasks, thus implying its combina tion with Artificial Intelligence (AI) technology, i.e., the so-called intelli gent RPA. Putting together RPA with AI leads to a challenging scenario since (1) it involves professionals from both fields who typically have different skills and backgrounds, and (2) AI models tend to degrade over time which affects the performance of the overall solution. This paper describes the AIRPA project, which addresses these challenges by proposing a software architecture that enables (1) the abstraction of the robot development from the AI development and (2) the monitor, con trol, and maintain intelligent RPA developments to ensure its quality and performance over time. The project has been conducted in the Serv inform context, a Spanish consultancy firm, and the proposed prototype has been validated with reality settings. The initial experiences yield promising results in reducing AHT (Average Handle Time) in processes where AIRPA deployed cognitive robots, which encourages exploring the support of intelligent RPA development.Ministerio de Ciencia, Innovación y Universidades PID2019-105455GB-C31Centro para el Desarrollo Tecnológico Industrial EXP00118029/IDI-20190524Centro para el Desarrollo Tecnológico Industrial P011-19/E0

sSLAM: Speeded-Up Visual SLAM Mixing Artificial Markers and Temporary Keypoints

Environment landmarks are generally employed by visual SLAM (vSLAM) methods in the form of keypoints. However, these landmarks are unstable over time because they belong to areas that tend to change, e.g., shadows or moving objects. To solve this, some other authors have proposed the combination of keypoints and artificial markers distributed in the environment so as to facilitate the tracking process in the long run. Artificial markers are special elements (similar to beacons) that can be permanently placed in the environment to facilitate tracking. In any case, these systems keep a set of keypoints that is not likely to be reused, thus unnecessarily increasing the computing time required for tracking. This paper proposes a novel visual SLAM approach that efficiently combines keypoints and artificial markers, allowing for a substantial reduction in the computing time and memory required without noticeably degrading the tracking accuracy. In the first stage, our system creates a map of the environment using both keypoints and artificial markers, but once the map is created, the keypoints are removed and only the markers are kept. Thus, our map stores only long-lasting features of the environment (i.e., the markers). Then, for localization purposes, our algorithm uses the marker information along with temporary keypoints created just in the time of tracking, which are removed after a while. Since our algorithm keeps only a small subset of recent keypoints, it is faster than the state-of-the-art vSLAM approaches. The experimental results show that our proposed sSLAM compares favorably with ORB-SLAM2, ORB-SLAM3, OpenVSLAM and UcoSLAM in terms of speed, without statistically significant differences in accuracy

sSLAM: Speeded-Up Visual SLAM Mixing Artificial Markers and Temporary Keypoints

Environment landmarks are generally employed by visual SLAM (vSLAM) methods in the form of keypoints. However, these landmarks are unstable over time because they belong to areas that tend to change, e.g., shadows or moving objects. To solve this, some other authors have proposed the combination of keypoints and artificial markers distributed in the environment so as to facilitate the tracking process in the long run. Artificial markers are special elements (similar to beacons) that can be permanently placed in the environment to facilitate tracking. In any case, these systems keep a set of keypoints that is not likely to be reused, thus unnecessarily increasing the computing time required for tracking. This paper proposes a novel visual SLAM approach that efficiently combines keypoints and artificial markers, allowing for a substantial reduction in the computing time and memory required without noticeably degrading the tracking accuracy. In the first stage, our system creates a map of the environment using both keypoints and artificial markers, but once the map is created, the keypoints are removed and only the markers are kept. Thus, our map stores only long-lasting features of the environment (i.e., the markers). Then, for localization purposes, our algorithm uses the marker information along with temporary keypoints created just in the time of tracking, which are removed after a while. Since our algorithm keeps only a small subset of recent keypoints, it is faster than the state-of-the-art vSLAM approaches. The experimental results show that our proposed sSLAM compares favorably with ORB-SLAM2, ORB-SLAM3, OpenVSLAM and UcoSLAM in terms of speed, without statistically significant differences in accuracy.This research was funded by the project PID2019-103871GB-I00 of the Spanish Ministry of Economy, Industry and Competitiveness, FEDER, Project 1380047-F UCOFEDER-2021 of Andalusia and by the European Union–NextGeneration EU for requalification of Spanish University System 2021–2023