Multidisciplinary teaching of Biotechnology and Omics sciences

In the last years, there was a great boom in the Omics fields that have developed as multidisciplinary sciences. They use laboratory techniques related to Biology and Chemistry but also Bioinformatics tools. However, the developmental progress of these disciplines has led that much of undergraduate studies related to Biology have curricula that become outdated. From this point of view, it is necessary to focus the students to the fundamentals and techniques of complementary disciplines that will be essentials for the understanding of the Omics sciences. In the present work, we have developed a new teaching approach for Biochemistry, Biology and Bioinformatics students. They formed interdisciplinary working groups. These groups have prepared and presented communications about different techniques or methods in Molecular Biology, Omics or Bioinformatics participating in a technical meeting. This learning strategy “I do and I learn” has enabled to the students a first contact with the scientific communication including the approach to the scientific literature to acquire technical knowledge. The cooperation between students from different disciplines has enriched their point of view and even has been used in some practical master’s works.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Caracterización del movimiento fuerte en el emplazamiento de la presa de Itoiz

Se presenta en este trabajo una nueva caracterización del movimiento del suelo en la presa de Itoiz, consistente con la peligrosidad sísmica del emplazamiento. En primer lugar, proponemos una metodología con tres niveles de aproximación al movimiento esperado, que es después aplicada considerando las características particulares de la presa y su emplazamiento. Los cálculos de peligrosidad se realizan siguiendo la línea metodológica conocida como PSHA, con un método probabilista zonificado y formulando un árbol lógico que combina diferentes zonificaciones sísmicas y modelos de movimiento fuerte. La peligrosidad se representa en términos de la aceleración pico PGA y de las aceleraciones espectrales para periodos coincidentes con los de vibración de la presa, considerando dos estados de la misma correspondientes a presa vacía (T=0.1s) y presa con capacidad máxima de llenado (T=0.22 s). Se caracterizan los correspondientes movimientos para dos periodos de retorno, 975 años y 4975 años, asociados al sismo de proyecto y al sismo extremo, respectivamente. El efecto de sitio en el emplazamiento de la presa también fue tenido en cuenta. La metodología propuesta conduce a caracterizar el movimiento con tres niveles de detalle. En una primera etapa se obtienen los espectros de respuesta uniforme (UHS) para los dos niveles de movimiento referidos. Seguidamente se desarrolla un análisis de desagregación para obtener los sismos de control que previsiblemente pueden afectar mas a la presa. Estos se identifican como los que más contribuyen a los movimientos objeto dados por las aceleraciones espectrales de los dos periodos característicos, SA (0,1 s) y SA (0.22 s) y para los dos periodos de retorno de 975 y 4975 años asociados a lo sismos de proyecto y extremo. De ahí se obtienen los espectros de respuesta específicos para las cuatro combinaciones resultantes. Finalmente, se realiza una simulación del movimiento en el dominio del tiempo, obteniendo acelerogramas sintéticos mediante el método de número de onda discreto. Las simulaciones se realizaron considerando fuentes finitas en diferentes posiciones y evaluando el efecto de la directividad en las posibles fuentes consideradas. Se concluye destacando la importancia del efecto de directividad, en la caracterización del emplazamiento de la presa

A Combined Experimental-Numerical Investigation of the Thermal Efficiency of the Vessel in Domestic Induction Systems

New studies are emerging to reduce energy costs and become a more sustainable society. One of the processes where the greatest savings can be made is in cooking, due to its large-scale global use. In this vein, this study aims to analyse the influence of the vessel in the thermal efficiency at the cooking process. For that purpose, a numerical model of a cooking vessel was designed and validated with three different experimental heating tests. One of the key factors of the process is the contact between the vessel and the glass, therefore, two new approaches to model the thermal contact between the vessel and the cooktop were explored. Once the numerical models were calibrated, a full factorial analysis was performed to quantify the influence of the key parameters of the vessel in the heating process during cooking (thermal conductivity, specific heat, convection and radiation coefficients, and vessel concavity). Two of the most influential parameters in the heating process are the conductivity and the thermal contact between the vessel and the glass. Higher cooking efficiency can be achieved both with a low thermal conductivity vessel and with a high concavity, i.e., increasing the isolation between the vessel and the glass

Phenomenology of symmetry breaking from extra dimensions

Motivated by the electroweak hierarchy problem, we consider theories with two extra dimensions in which the four-dimensional scalar fields are components of gauge boson in full space. We explore the Nielsen-Olesen instability for SU(N) on a torus, in the presence of a magnetic background. A field theory approach is developed, computing explicitly the minimum of the complete effective potential, including tri-linear and quartic couplings and determining the symmetries of the stable vacua. We also develop appropriate gauge-fixing terms when both Kaluza-Klein and Landau levels are present and interacting, discussing the interplay between the possible six and four dimensional choices. The equivalence between coordinate dependent and constant Scherk-Schwarz boundary conditions -associated to either continuous or discrete Wilson lines- is analyzed.Comment: 39 pages and 8 eps figures. Few changes in section

Graphitic Carbon Nitride Materials for Energy Applications

Polymeric layered carbon nitrides were investigated for use as catalyst support materials for proton exchange membrane fuel cells (PEMFCs) and water electrolyzers (PEMWEs). Three different carbon nitride materials were prepared: a heptazine-based graphitic carbon nitride material (gCNM), poly (triazine) imide carbon nitride intercalated with LiCl component (PTI-Li+Cl-) and boron-doped graphitic carbon nitride (B-gCNM). Following accelerated corrosion testing, all graphitic carbon nitride materials were found to be more electrochemically stable compared to conventional carbon black (Vulcan XC-72R) with B-gCNM support showing the best stability. For the supported Pt, Pt/PTI-Li+Cl- exhibited the best durability with only 19% electrochemical surface area (ECSA) loss versus 36% for Pt/Vulcan. Superior methanol oxidation activity was observed for all gCNM supported Pt catalysts on the basis of the catalyst ECSA. Preliminary results on IrO2 supported on gCNM using a PEMWE cell revealed an enhancement in the charge-transfer resistance as the current density increases when compared to unsupported IrO2. This may be attributed to a higher active surface area of the catalyst nanoparticles on the gCNM support

Remote quantification of soil organic carbon: role of topography in the intra-field distribution

Soil organic carbon (SOC) measurements are an indicator of soil health and an important parameter for the study of land-atmosphere carbon fluxes. Field sampling provides precise measurements at the sample location but entails high costs and cannot provide detailed maps unless the sampling density is very high. Remote sensing offers the possibility to quantify SOC over large areas in a cost-effective way. As a result, numerous studies have sought to quantify SOC using Earth observation data with a focus on inter-field or regional distributions. This study took a different angle and aimed to map the spatial distribution of SOC at the intra-field scale, since this distribution provides important insights into the biophysiochemical processes involved in the retention of SOC. Instead of solely using spectral measurements to quantify SOC, topographic and spectral features act as predictor variables. The necessary data on study fields in South-East England was acquired through a detailed SOC sampling campaign, including a LiDAR survey flight. Multi-spectral Sentinel-2 data of the study fields were acquired for the exact day of the sampling campaign, and for an interval of 18 months before and after this date. Random Forest (RF) and Support Vector Regression (SVR) models were trained and tested on the spectral and topographical data of the fields to predict the observed SOC values. Five different sets of model predictors were assessed, by using independently and in combination, single and multidate spectral data, and topographical features for the SOC sampling points. Both, RF and SVR models performed best when trained on multi-temporal Sentinel-2 data together with topographic features, achieving validation root-mean-square errors (RMSEs) of 0.29% and 0.23% SOC, respectively. These RMSEs are competitive when compared with those found in the literature for similar models. The topographic wetness index (TWI) exhibited the highest permutation importance for virtually all models. Given that farming practices within each field are the same, this result suggests an important role of soil moisture in SOC retention. Contrary to findings in dryer climates or in studies encompassing larger areas, TWI was negatively related to SOC levels in the study fields, suggesting a different role of soil wetness in the SOC storage in climates characterized by excess rainfall and poorly drained soils

Pharmacological profiles of acute myeloid leukemia treatments in patient samples by automated flow cytometry : A bridge to individualized medicine

Background We have evaluated the ex vivo pharmacology of single drugs and drug combinations in malignant cells of bone marrow samples from 125 patients with acute myeloid leukemia using a novel automated flow cytometry-based platform (ExviTech). We have improved previous ex vivo drug testing with 4 innovations: identifying individual leukemic cells, using intact whole blood during the incubation, using an automated platform that escalates reliably data, and performing analyses pharmacodynamic population models. Patients and Methods Samples were sent from 24 hospitals to a central laboratory and incubated for 48 hours in whole blood, after which drug activity was measured in terms of depletion of leukemic cells. Results The sensitivity of single drugs is assessed for standard efficacy (E) and potency (EC) variables, ranked as percentiles within the population. The sensitivity of drug-combination treatments is assessed for the synergism achieved in each patient sample. We found a large variability among patient samples in the dose-response curves to a single drug or combination treatment. Conclusion We hypothesize that the use of the individual patient ex vivo pharmacological profiles may help to guide a personalized treatment selection. © 2014 The Authors. Published by Elsevier Inc. All rights reserved

Enhancing physicians’ radiology diagnostics of COVID-19’s effects on lung health by leveraging artificial intelligence

Introduction: This study aimed to develop an individualized artificial intelligence model to help radiologists assess the severity of COVID-19's effects on patients' lung health.Methods: Data was collected from medical records of 1103 patients diagnosed with COVID-19 using RT- qPCR between March and June 2020, in Hospital Madrid-Group (HM-Group, Spain). By using Convolutional Neural Networks, we determine the effects of COVID-19 in terms of lung area, opacities, and pulmonary air density. We then combine these variables with age and sex in a regression model to assess the severity of these conditions with respect to fatality risk (death or ICU).Results: Our model can predict high effect with an AUC of 0.736. Finally, we compare the performance of the model with respect to six physicians' diagnosis, and test for improvements on physicians' performance when using the prediction algorithm.Discussion: We find that the algorithm outperforms physicians (39.5% less error), and thus, physicians can significantly benefit from the information provided by the algorithm by reducing error by almost 30%

Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis

Background: Infections due to antibiotic-resistant bacteria are threatening modern health care. However, estimating their incidence, complications, and attributable mortality is challenging. We aimed to estimate the burden of infections caused by antibiotic-resistant bacteria of public health concern in countries of the EU and European Economic Area (EEA) in 2015, measured in number of cases, attributable deaths, and disability-adjusted life-years (DALYs). Methods: We estimated the incidence of infections with 16 antibiotic resistance–bacterium combinations from European Antimicrobial Resistance Surveillance Network (EARS-Net) 2015 data that was country-corrected for population coverage. We multiplied the number of bloodstream infections (BSIs) by a conversion factor derived from the European Centre for Disease Prevention and Control point prevalence survey of health-care-associated infections in European acute care hospitals in 2011–12 to estimate the number of non-BSIs. We developed disease outcome models for five types of infection on the basis of systematic reviews of the literature. Findings: From EARS-Net data collected between Jan 1, 2015, and Dec 31, 2015, we estimated 671 689 (95% uncertainty interval [UI] 583 148–763 966) infections with antibiotic-resistant bacteria, of which 63·5% (426 277 of 671 689) were associated with health care. These infections accounted for an estimated 33 110 (28 480–38 430) attributable deaths and 874 541 (768 837–989 068) DALYs. The burden for the EU and EEA was highest in infants (aged <1 year) and people aged 65 years or older, had increased since 2007, and was highest in Italy and Greece. Interpretation: Our results present the health burden of five types of infection with antibiotic-resistant bacteria expressed, for the first time, in DALYs. The estimated burden of infections with antibiotic-resistant bacteria in the EU and EEA is substantial compared with that of other infectious diseases, and has increased since 2007. Our burden estimates provide useful information for public health decision-makers prioritising interventions for infectious diseases

Investigating the Effect of Galaxy Interactions on Star Formation at 0.5<z<3.0

Observations and simulations of interacting galaxies and mergers in the local universe have shown that interactions can significantly enhance the star formation rates (SFR) and fueling of Active Galactic Nuclei (AGN). However, at higher redshift, some simulations suggest that the level of star formation enhancement induced by interactions is lower due to the higher gas fractions and already increased SFRs in these galaxies. To test this, we measure the SFR enhancement in a total of 2351 (1327) massive ($M_*>10^{10}M_\odot$) major ($1<M_1/M_2<4$) spectroscopic galaxy pairs at 0.5<z<3.0 with $\Delta V <5000$ km s$^{-1}$ (1000 km s$^{-1}$) and projected separation <150 kpc selected from the extensive spectroscopic coverage in the COSMOS and CANDELS fields. We find that the highest level of SFR enhancement is a factor of 1.23$^{+0.08}_{-0.09}$ in the closest projected separation bin (<25 kpc) relative to a stellar mass-, redshift-, and environment-matched control sample of isolated galaxies. We find that the level of SFR enhancement is a factor of $\sim1.5$ higher at 0.5<z<1 than at 1<z<3 in the closest projected separation bin. Among a sample of visually identified mergers, we find an enhancement of a factor of 1.86$^{+0.29}_{-0.18}$ for coalesced systems. For this visually identified sample, we see a clear trend of increased SFR enhancement with decreasing projected separation (2.40$^{+0.62}_{-0.37}$ vs.\ 1.58$^{+0.29}_{-0.20}$ for 0.5<z<1.6 and 1.6<z<3.0, respectively). The SFR enhancement seen in our interactions and mergers are all lower than the level seen in local samples at the same separation, suggesting that the level of interaction-induced star formation evolves significantly over this time period.Comment: 23 pages, 13 figures, Accepted for publication in Ap