Evaluación de la obtención de aceite de girasol a partir de extracción acuosa enzimática usando enzimas proteasa

The aim of this work was to maximize the enzymatic aqueous extraction (EAE) of sunflower seed oil using protease enzymes from the evaluation of various temperatures, pH and enzyme concentrations, using a Box-Behnken experimental design. The effect of a thermal pre-treatment of sunflower seeds on free oil yield (FOY) and oil quality was also determined. In the experimental range adopted, a lower temperature (40 °C) provided higher FOY values, as well as the intermediate pH (8.00) and maximum enzyme concentration (9% v/v). Thermal pre-treatment provided an increase in FOY in the initial extraction times (60 to 180 min) and decreased of the extraction time of 4 to 3 h to obtain the highest FOY value (~16%). The fatty acid composition of the oils obtained showed a predominance of oleic (~47.5%) and linoleic acids (~39.5%). The total phytosterol content in the samples was hardly affected by the heat pre-treatment of the seeds, while the fatty acid profile, tocopherol content and oxidative stability were not altered.El objetivo de este trabajo fue maximizar la extracción acuosa enzimática (EAE) de aceite de semillas de girasol utilizando la enzima proteasa a partir de la evaluación de las variables temperatura, pH y concentración de la enzima, utilizando un diseño experimental de Box-Behnken. Además, se determinó el efecto del pretratamiento térmico de las semillas de girasol sobre el rendimiento (RA) y la calidad del aceite. En el rango experimental adoptado, las temperaturas más bajas (40 °C) proporcionaron valores de RA más altos, así como el pH intermedio (8,00) y la concentración máxima de enzima (9% v/v). El pretratamiento térmico proporcionó un aumento del RA en los tiempos de extracción iniciales (60 a 180 min) y una disminución del tiempo de extracción de 4 a 3 h para obtener el valor de RA más alto (~ 16%). La composición en ácidos grasos de los aceites obtenidos mostró predominio de los ácidos oleico (~47,5%) y linoleico (~39,5%). El contenido total de fitosteroles en las muestras se vio poco afectado por el pretratamiento térmico de las semillas, mientras que el perfil de ácidos grasos, el contenido de tocoferoles y la estabilidad oxidativa no se vieron afectados

Sloan Digital Sky Survey IV: mapping the Milky Way, nearby galaxies, and the distant universe

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median ). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July

Sloan Digital Sky Survey IV: mapping the Milky Way, nearby galaxies, and the distant universe

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median ). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease