Adsorption of landfill leachates onto activated carbon: Equilibrium and kinetics

The adsorption of stabilized leachates generated in a municipal landfill onto three commercial activated carbons has been investigated. Norit 0.8, Chemviron AQ40 and Picacarb 1240 have been used as adsorbents. Equilibrium experiments have been conducted to obtain the experimental isotherm profiles. Isotherms have been plotted based on the adsorption of general parameters, for instance chemical oxygen demand, total carbon, absorption at 410 nm and absorption at 254 nm. Different literature models and error functions have been used to adequately fit the experimental data. As a rule of thumb, three-parameter models do adjust experimental results better than two-parameter models. Norit 0.8 shows better adsorption characteristics than the rest of activated carbons, both in terms of contaminant level reduction of per unit mass of absorbent and in terms of the process kinetics

Study of different integrated physical-chemical + adsorption processes for landfill leachate remediation

Some integrated processes to deal with landfill leachates have been investigated and their efficiencies expressed in terms of chemical oxygen demand (COD) removal. The systems tested were the result of different combinations of the following single stages: acidic pH shift (elimination of humic substances), ozonation (O3), coagulation-flocculation with Fe(III) salts, Fenton's oxidation (Fe(III) + H2O2), wet air oxidation (with or without radical promoters), and adsorption onto activated carbon (commercial Norit 0.8 powdered activated carbon). COD removals obtained ranged in the interval of 80-96% for initial COD values close to 11000 mg L-1. None of the processes tested reduced the COD levels sufficiently to allow direct discharge; however, the ratio biochemical oxygen demand (BOD/COD was significantly increased (up to 1000% in some cases, i.e., from 0.1 to values above 1.0). Total carbon reduction achieved ranged from 60 to 94%, while complete decolorization (measured as the absorbance at 410 nm) was obtained in practically all the combinations investigate

Merged consensus clustering to assess and improve class discovery with microarray data

<p>Abstract</p> <p>Background</p> <p>One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a large number of methods available to perform clustering, but it is often unclear which method is best suited to the data and how to quantify the quality of the classifications produced.</p> <p>Results</p> <p>Here we describe an R package containing methods to analyse the consistency of clustering results from any number of different clustering methods using resampling statistics. These methods allow the identification of the the best supported clusters and additionally rank cluster members by their fidelity within the cluster. These metrics allow us to compare the performance of different clustering algorithms under different experimental conditions and to select those that produce the most reliable clustering structures. We show the application of this method to simulated data, canonical gene expression experiments and our own novel analysis of genes involved in the specification of the peripheral nervous system in the fruitfly, <it>Drosophila melanogaster</it>.</p> <p>Conclusions</p> <p>Our package enables users to apply the merged consensus clustering methodology conveniently within the R programming environment, providing both analysis and graphical display functions for exploring clustering approaches. It extends the basic principle of consensus clustering by allowing the merging of results between different methods to provide an averaged clustering robustness. We show that this extension is useful in correcting for the tendency of clustering algorithms to treat outliers differently within datasets. The R package, <it>clusterCons</it>, is freely available at CRAN and sourceforge under the GNU public licence.</p

Clinical consensus recommendations regarding non-invasive respiratory support in the adult patient with acute respiratory failure secondary to SARS-CoV-2 infection

La enfermedad por coronavirus 2019 (COVID-19) es una infección del tracto respiratorio causada por un nuevo coronavirus emergente que se reconoció por primera vez en Wuhan, China, en diciembre de 2019. Actualmente la Organización Mundial de la Salud (OMS) ha definido la infección como pandemia y existe una situación de emergencia sanitaria y social para el manejo de esta nueva infección. Mientras que la mayoría de las personas con COVID-19 desarrollan solo una enfermedad leve o no complicada, aproximadamente el 14% desarrollan una enfermedad grave que requiere hospitalización y oxígeno, y el 5% pueden requerir ingreso en una unidad de cuidados intensivos. En casos severos, COVID-19 puede complicarse por el síndrome de dificultad respiratoria aguda (SDRA), sepsis y shock séptico y fracaso multiorgánico. Este documento de consenso se ha preparado sobre directrices basadas en evidencia desarrolladas por un panel multidisciplinario de profesionales médicos de cuatro sociedades científicas españolas (Sociedad Española de Medicina Intensiva y Unidades Coronarias [SEMICYUC], Sociedad Española de Neumología y Cirugía Torácica [SEPAR], Sociedad Española de Urgencias y Emergencias [SEMES], Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor [SEDAR]) con experiencia en el manejo clínico de pacientes con COVID-19 y otras infecciones virales, incluido el SARS, así como en sepsis y SDRA. El documento proporciona recomendaciones clínicas para el soporte respiratorio no invasivo (ventilación no invasiva, oxigenoterapia de alto flujo con cánula nasal) en cualquier paciente con presentación sospechada o confirmada de COVID-19 con insuficiencia respiratoria aguda. Esta guía de consenso debe servir como base para una atención optimizada y garantizar la mejor posibilidad de supervivencia, así como permitir una comparación fiable de las futuras intervenciones terapéuticas de investigación que formen parte de futuros estudios observacionales o de ensayos clínicos.Coronavirus disease 2019 (COVID-19) is a respiratory tract infection caused by a newly emergent coronavirus, that was first recognized in Wuhan, China, in December 2019. Currently, the World Health Organization (WHO) has defined the infection as a global pandemic and there is a health and social emergency for the management of this new infection. While most people with COVID-19 develop only mild or uncomplicated illness, approximately 14% develop severe disease that requires hospitalization and oxygen support, and 5% require admission to an intensive care unit. In severe cases, COVID-19 can be complicated by the acute respiratory distress syndrome (ARDS), sepsis and septic shock, and multiorgan failure. This consensus document has been prepared on evidence-informed guidelines developed by a multidisciplinary panel of health care providers from four Spanish scientific societies (Spanish Society of Intensive Care Medicine [SEMICYUC], Spanish Society of Pulmonologists [SEPAR], Spanish Society of Emergency [SEMES], Spanish Society of Anesthesiology, Reanimation, and Pain [SEDAR]) with experience in the clinical management of patients with COVID-19 and other viral infections, including SARS, as well as sepsis and ARDS. The document provides clinical recommendations for the noninvasive respiratory support (noninvasive ventilation, high flow oxygen therapy with nasal cannula) in any patient with suspected or confirmed presentation of COVID-19 with acute respiratory failure. This consensus guidance should serve as a foundation for optimized supportive care to ensure the best possible chance for survival and to allow for reliable comparison of investigational therapeutic interventions as part of randomized controlled trials

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Mapa del territorio de Melilla

Litografia color, sobre paper ; Finestres: Mapa de conjunto, Peninsula Ibérica y zona de influencia española. Datos estadístico

Using microalgae scenedesmus obliquus in the removal of chromium present in plating wastewaters

8 páginas, 5 figuras, 5 tablas.[ES] El vertido de aguas residuales con alto contenido de cromo, procedentes de las industrias galvanoplásticas, es un peligro potencial que se le presenta a la población y al medio ambiente. Se conoce que algunos metales, incluyendo los pesados, a concentraciones bajas participan en diferentes rutas metabólicas, pero en altas concentraciones pueden ser tóxicos para muchos organismos vivos. Algunos microorganismos toman los metales pesados del medio ambiente, siendo capaces de concentrar y acumular grandes cantidades de los mismos en diferentes estructuras citoplasmáticas, sin que lleguen a ocasionar efectos tóxicos en los mismos. Las microalgas son un ejemplo de este comportamiento, ya que tienen afinidad por los metales polivalentes, de ahí la posibilidad de su aplicación como agentes descontaminantes en aguas que contengan iones metálicos disueltos como método alternativo cuando no se pueda utilizar otro método de recuperación. En este trabajo se realizó un estudio de eliminación de cromo presente en las aguas residuales galvánicas, empleando un cultivo de scenedesmus obliquus. Se obtuvo una eficiencia de eliminación de Cr (VI) del 12 % y del 27 % para el Cr (III), y en condiciones de inmovilización del alga fue del 95 % para el Cr (III).[EN] Dumping wastewaters from plating industry with a high content in chromium is a potential hazard for people and environment. It is known that some metals, including the heavy metals, at low concentrations participate in different metabolic routes, but at high concentration are toxic for many living organisms. Some microorganism taking the heavy metals from the environment are capable of concentrating and accumulating large quantities of them in different citoplasmatic structures with no-toxic effects. Microalgae have affinity by the polyvalent metals making possible their use as depollutant agent in waters that contains dissolved metallic ions as alternative methods when others methods of recycle are unusable. In this report a chromium removal study from a plating wastewater, using scenedesmus obliquus culture was made. The removal efficiency of Cr (VI) was 12 % and Cr (III) was 27 % and for condition of algae's immobilization removal of Cr (III) was 95 %.Peer reviewe

Genome Scale Modeling to Study the Metabolic Competition between Cells in the Tumor Microenvironment

The tumor’s physiology emerges from the dynamic interplay of numerous cell types, such as cancer cells, immune cells and stromal cells, within the tumor microenvironment. Immune and cancer cells compete for nutrients within the tumor microenvironment, leading to a metabolic battle between these cell populations. Tumor cells can reprogram their metabolism to meet the high demand of building blocks and ATP for proliferation, and to gain an advantage over the action of immune cells. The study of the metabolic reprogramming mechanisms underlying cancer requires the quantification of metabolic fluxes which can be estimated at the genome-scale with constraint-based or kinetic modeling. Constraint-based models use a set of linear constraints to simulate steady-state metabolic fluxes, whereas kinetic models can simulate both the transient behavior and steady-state values of cellular fluxes and concentrations. The integration of cell- or tissue-specific data enables the construction of context-specific models that reflect cell-type- or tissue-specific metabolic properties. While the available modeling frameworks enable limited modeling of the metabolic crosstalk between tumor and immune cells in the tumor stroma, future developments will likely involve new hybrid kinetic/stoichiometric formulations