Shine on you crazy diamond: Symbolism and social use of fluorite ornaments in Iberia’s late prehistory

Fluorite ornaments have been recorded in different sites of Europe since Upper Paleolithic. Due to its visual appearance and physical properties, some translucent or transparent mineralogies like fluorite were searched for or casually acquired by late prehistory’s human communities. After intensive research on archaeological contexts from the Iberian Peninsula with personal ornaments from 4th to 2nd millennia BCE, we have recently identified and characterized for the first time an important number of fluorite ornaments, confronting a previous background where little attention was paid. Our work has been carried out in different archaeological collections and museums from the whole Iberian Peninsula by non-destructive techniques (Raman spectroscopy, portable X-ray fluorescence (p-XRF) and X-ray Diffraction (XRD), that revealed the nature of fluorite ornaments and points to its consideration as scarce and highly symbolic items during late prehistory. A total of 36 fluorite beads from 23 sites are here recorded and studied, many of them unpublished or wrong catalogued as other mineralogies. These adornments could have important roles in trade and use among the communities of Iberia from the 4th millennium BCE onwards, because of their scarcity and its recurrent association with important funerary complex and exotic materials. Fluorite ornaments could have been significant and special symbols in the development of new and exclusive raw materials in the context of increasing social complexity and inequality

Novel loci and Mapuche genetic ancestry are associated with pubertal growth traits in Chilean boys

Puberty is a complex developmental process that varies considerably among individuals and populations. Genetic factors explain a large proportion of the variability of several pubertal traits. Recent genome-wide association studies (GWAS) have identified hundreds of variants involved in traits that result from body growth, like adult height. However, they do not capture many genetic loci involved in growth changes over distinct growth phases. Further, such GWAS have been mostly performed in Europeans, but it is unknown how these findings relate to other continental populations. In this study, we analyzed the genetic basis of three pubertal traits; namely, peak height velocity (PV), age at PV (APV) and height at APV (HAPV). We analyzed a cohort of 904 admixed Chilean children and adolescents with European and Mapuche Native American ancestries. Height was measured on roughly a 6−month basis from childhood to adolescence between 2006 and 2019. We predict that, in average, HAPV is 4.3 cm higher in European than in Mapuche adolescents (P = 0.042), and APV is 0.73 years later in European compared with Mapuche adolescents (P = 0.023). Further, by performing a GWAS on 774, 433 single-nucleotide polymorphisms, we identified a genetic signal harboring 3 linked variants significantly associated with PV in boys (P <5×10−8). This signal has never been associated with growth-related traits

Protein removal from waste brines generated during ham salting through acidification and centrifugation

[EN] The salting step in food processes implies the production of large quantities of waste brines, having high organic load, high conductivity, and other pollutants with high oxygen demand. Direct disposal of the residual brine implies salinization of soil and eutrophication of water. Since most of the organic load of the waste brines comes from proteins leaked from the salted product, precipitation of dissolved proteins by acidification and removal by centrifugation is an operation to be used in waste brine cleaning. The aim of this study is optimizing the conditions for carrying out the separation of proteins from waste brines generated in the pork ham salting operation, by studying the influence of pH, centrifugal force, and centrifugation time. Models for determining the removal of proteins depending on the pH, centrifugal force, and time were obtained. The results showed a high efficacy of the proposed treatment for removing proteins, suggesting that this method could be used for waste brine protein removal. The best pH value to be used in an industrial process seems to be 3, while the obtained results indicate that almost 90% of the proteins from the brine can be removed by acidification followed by centrifugation. A further protein removal from the brine should have to be achieved using filtrating techniques, which efficiency could be highly improved as a consequence of the previous treatment through acidification and centrifugation. Practical Application Waste brines from meat salting have high organic load and electrical conductivity. Proteins can be removed from the waste brine by acidification and centrifugation. The total protein removal can be up to 90% of the initial content of the waste brine. Protein removal is highly dependent on pH, centrifugation rate, and time.We would like to thank the Spanish Government (MCYT) and the EU (FEDER program) for the financial support of the project (AGL2004-05064-C02).Gutiérrez-Martínez, MDR.; Muñoz Guerrero, HP.; Alcaina-Miranda, MI.; Barat Baviera, JM. (2014). Protein removal from waste brines generated during ham salting through acidification and centrifugation. Journal of Food Science. 79(3):326-332. https://doi.org/10.1111/1750-3841.12373S32633279

Revisiting stellar properties of star-forming galaxies with stellar and nebular spectral modelling

Spectral synthesis is a powerful tool for interpreting the physical properties of galaxies by decomposing their spectral energy distributions into the main luminosity contributors (e.g. stellar populations or ionised gas). However, the impact nebular emission has on the inferred properties of star-forming (SF) galaxies has been largely overlooked over the years. The objective of this work is to estimate the relations between stellar properties of SF galaxies from SDSS DR7 by simultaneously fitting the stellar and nebular continua with FADO and comparing them to the results derived using STARLIGHT, a representative of purely stellar population synthesis codes. Differences between codes regarding average mass, mean age and mean metallicity values can go as high as $\sim$0.06 dex for the overall population of galaxies and $\sim$0.12 dex for SF galaxies (galaxies with EW(H$\alpha$)>3 \AA), with the most prominent difference between both codes in the light-weighted mean stellar age. A closer look into the average light- and mass-weighted star formation histories of intensively SF galaxies (EW(H$\alpha$)>75 \AA) suggests that STARLIGHT is underestimating the average light-weighted age of intensively SF galaxies by up to $\sim$0.17 dex and overestimating the light-weighted metallicity by up to $\sim$0.13 dex compared to FADO (or vice versa). The comparison between the average stellar properties of passive, SF and intensively SF galaxy samples also reveals that differences between codes increase with increasing EW(H$\alpha$) and decreasing total stellar mass. This work finds indirect evidence that a purely stellar population synthesis approach negatively impacts the inferred stellar properties of galaxies with relatively high star formation rates. In turn, this can bias interpretations of fundamental relations such as the mass-age or mass-metallicity.Comment: 27 pages, 25 figures. Accepted for publication in Astronomy & Astrophysic

Inteligencia artificial para evaluar asociación de parámetros sistémicos y clínicos a los diferentes grados de severidad y nivel de secuela de pacientes que cursaron COVID-19

78 p.La enfermedad de coronavirus 2019 (COVID-19) es una enfermedad infecciosa causada por el coronavirus del síndrome respiratorio agudo severo 2 (SARS-CoV 2), la cual se ha extendido a 192 países, incluido el nuestro, logrando 268.484.455 contagios confirmados y un total de 5.286.786 muertes a nivel mundial. Esta enfermedad se ha caracterizado por presentar diversos síntomas de acuerdo con la gravedad del cuadro infeccioso, pudiendo éste presentarse de forma asintomática, leve, moderada o severa, llegando incluso a causar un desenlace fatal. Además, se ha demostrado que los pacientes que logran sobrevivir presentan diversas secuelas que persisten meses posteriores al término de la etapa aguda de la enfermedad. Actualmente, no está del todo clara la relación entre las características que presenta un paciente diagnosticado con COVID-19 con el grado de severidad que presentará durante la infección del virus, así como las posibles secuelas que pueda desarrollar una vez haya cursado la enfermedad. El objetivo de este trabajo fue analizar diferentes parámetros clínicos, experimentales y demográficos para determinar su asociación a los distintos grados se severidad y nivel de secuela de pacientes que cursaron COVID-19. La metodología para abordar este proyecto fue a partir de información obtenida de 60 pacientes con diagnóstico confirmado de infección por SARS-CoV-2 que cursaron la patología con sintomatología leve (n=18), moderada (n=17) y severa (n=25). En primera instancia se configuró el conjunto de datos a partir de la información obtenida de cada participante. A continuación, y mediante métodos de selección de características, se determinó aquellos parámetros que tienen mayor relevancia al momento de asociarlos a los distintos grados de severidad y nivel de secuela. Finalmente, se realizó la evaluación de diferentes modelos supervisados de inteligencia artificial que permitieron clasificar grado de severidad y nivel de secuela en pacientes que cursaron COVID-19. A partir de este trabajo se obtuvieron parámetros que tienen mayor influencia en el desarrollo de niveles de severidad y secuela como lo son información clínica, de Tomografía Axial Computarizada (TAC), cuestionarios, espirometría y citoquinas plasmáticas. Además, se lograron generar modelos de clasificación con un desempeño de hasta 100% a partir de los métodos 8 de Random Forest y XGBoost, logrando aportar al análisis de información generado por la pandemia de COVID-19. En conclusión, métodos de inteligencia artificial permitieron identificar patrones y las características más relevantes que están asociadas al grado de severidad y nivel de secuela en pacientes que cursaron COVID-19. // ABSTRACT: The coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). This virus has spread to 192 countries, including ours, and so far, 268,484,455 infections and 5,286,786 deaths worldwide have been confirmed. Asymptomatic infection or mild, moderate, severe or critical symptoms during infection have been reported in COVID-19 patients. In addition, it has been shown that patients who survive exhibit diverse sequelae, which persist for months after the acute stage of the disease. Currently, the relationship between COVID-19 patient characteristics and the degree of severity and sequelae during and after viral infection is not entirely clear. Thus, the aim of this study was to analyze different clinical, experimental and demographic parameters to determine their association at different levels of severity and sequelae in COVID-19 patients. Clinical, experimental, and demographic data obtained from 60 patients with a confirmed diagnosis of mild (n = 18), moderate (n = 17) and severe (n = 25) SARS-CoV-2 infection was obtained. The dataset was configured from the information obtained from each participant. Subsequently, and through methods of characteristics’ selection, those parameters that are most relevant when associating them with the different levels of severity and sequelae were determined. Then, the evaluation of different supervised artificial intelligence models was carried out that allow classifying the degree of severity and level of sequelae in patients who had COVID-19. Our results revealed that the most important features in the modeling of the degree of severity and sequelae were clinical information, Computerized Axial Tomography (CT), questionnaires, spirometry, and plasma cytokines. In addition, classification models with a performance of up to 100% was generated using the Random Forest and XGBoost methods, contributing to the analysis of information generated by the COVID-19 pandemic. In summary, artificial intelligence methods made it possible to identify patterns and the most relevant characteristics that are associated with the degree of severity and level of sequelae in patients with COVID-19

Role of age and comorbidities in mortality of patients with infective endocarditis

[Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Enfermedades crónicas

Adherencia al tratamiento farmacol&oacute;gico y relaci&oacute;n con el control metab&oacute;lico en pacientes con DM2Aluminio en pacientes con terapia de reemplazo renal cr&oacute;nico con hemodi&aacute;lisis en Bogot&aacute;, ColombiaAmputaci&oacute;n de extremidades inferiores: &iquest;est&aacute;n aumentando las tasas?Consumo de edulcorantes artificiales en j&oacute;venes universitariosC&oacute;mo crecen ni&ntilde;os normales de 2 a&ntilde;os que son sobrepeso a los 7 a&ntilde;osDiagn&oacute;stico con enfoque territorial de salud cardiovascular en la Regi&oacute;n MetropolitanaEfecto a corto plazo de una intervenci&oacute;n con ejercicio f&iacute;sico, en ni&ntilde;os con sobrepesoEfectos de la cirug&iacute;a bari&aacute;trica en pacientes con s&iacute;ndrome metab&oacute;lico e IMC &lt; 35 KG/M2Encuesta mundial de tabaquismo en estudiantes de profesiones de saludEnfermedades cr&oacute;nicas no transmisibles: Consecuencias sociales-sanitarias de comunidades rurales en ChileEpidemiolog&iacute;a de las muertes hospitalarias por patolog&iacute;as relacionadas a muerte encef&aacute;lica, Chile 2003-2007Estado nutricional y conductas alimentarias en adolescentes de 4&ordm; medio de la Regi&oacute;n de CoquimboEstudio de calidad de vida en una muestra del plan piloto para hepatitis CEvaluaci&oacute;n del proceso asistencial y de resultados de salud del GES de diabetes mellitus 2Factores de riesgo cardiovascular en poblaci&oacute;n universitaria de la Facsal, universidad de Tarapac&aacute;Implicancias psicosociales en la g&eacute;nesis, evoluci&oacute;n y tratamiento de pacientes con hipertensi&oacute;n arterial esencialInfarto agudo al miocardio (IAM): Realidad en el Hospital de Puerto Natales, 2009-2010Introducci&oacute;n de nuevas TIC y mejor&iacute;a de la asistencia a un programa de saludNi&ntilde;os obesos atendidos en el Cesfam de Puerto Natales y su entorno familiarPerfil de la mortalidad por c&aacute;ncer de cuello uterino en R&iacute;o de JaneiroPerfil del paciente primo-consultante del Programa de Salud Cardiovascular, Consultorio Cordillera Andina, Los AndesPrevalencia de automedicaci&oacute;n en mujeres beneficiarias del Hospital Comunitario de Til-TiPrevalencia de caries en poblaci&oacute;n preescolar y su relaci&oacute;n con malnutrici&oacute;n por excesoPrevalencia de retinopat&iacute;a diab&eacute;tica en comunas dependientes del Servicio de Salud Metropolitano Occidente (SSMOC)Problemas de adherencia farmacol&oacute;gica antihipertensiva en poblaci&oacute;n mapuche: Un estudio cualitativoRol biol&oacute;gico de los antioxidantes innatos en pacientes portadores de VIH/SidaSobrepeso en empleados de un restaurante de una universidad p&uacute;blica del estado de S&atilde;o Paul

Local hydrological conditions influence tree diversity and composition across the Amazon basin

Tree diversity and composition in Amazonia are known to be strongly determined by the water supplied by precipitation. Nevertheless, within the same climatic regime, water availability is modulated by local topography and soil characteristics (hereafter referred to as local hydrological conditions), varying from saturated and poorly drained to well-drained and potentially dry areas. While these conditions may be expected to influence species distribution, the impacts of local hydrological conditions on tree diversity and composition remain poorly understood at the whole Amazon basin scale. Using a dataset of 443 1-ha non-flooded forest plots distributed across the basin, we investigate how local hydrological conditions influence 1) tree alpha diversity, 2) the community-weighted wood density mean (CWM-wd) – a proxy for hydraulic resistance and 3) tree species composition. We find that the effect of local hydrological conditions on tree diversity depends on climate, being more evident in wetter forests, where diversity increases towards locations with well-drained soils. CWM-wd increased towards better drained soils in Southern and Western Amazonia. Tree species composition changed along local soil hydrological gradients in Central-Eastern, Western and Southern Amazonia, and those changes were correlated with changes in the mean wood density of plots. Our results suggest that local hydrological gradients filter species, influencing the diversity and composition of Amazonian forests. Overall, this study shows that the effect of local hydrological conditions is pervasive, extending over wide Amazonian regions, and reinforces the importance of accounting for local topography and hydrology to better understand the likely response and resilience of forests to increased frequency of extreme climate events and rising temperatures

Mapping density, diversity and species-richness of the Amazon tree flora

Using 2.046 botanically-inventoried tree plots across the largest tropical forest on Earth, we mapped tree species-diversity and tree species-richness at 0.1-degree resolution, and investigated drivers for diversity and richness. Using only location, stratified by forest type, as predictor, our spatial model, to the best of our knowledge, provides the most accurate map of tree diversity in Amazonia to date, explaining approximately 70% of the tree diversity and species-richness. Large soil-forest combinations determine a significant percentage of the variation in tree species-richness and tree alpha-diversity in Amazonian forest-plots. We suggest that the size and fragmentation of these systems drive their large-scale diversity patterns and hence local diversity. A model not using location but cumulative water deficit, tree density, and temperature seasonality explains 47% of the tree species-richness in the terra-firme forest in Amazonia. Over large areas across Amazonia, residuals of this relationship are small and poorly spatially structured, suggesting that much of the residual variation may be local. The Guyana Shield area has consistently negative residuals, showing that this area has lower tree species-richness than expected by our models. We provide extensive plot meta-data, including tree density, tree alpha-diversity and tree species-richness results and gridded maps at 0.1-degree resolution

Geographic patterns of tree dispersal modes in Amazonia and their ecological correlates

Aim: To investigate the geographic patterns and ecological correlates in the geographic distribution of the most common tree dispersal modes in Amazonia (endozoochory, synzoochory, anemochory and hydrochory). We examined if the proportional abundance of these dispersal modes could be explained by the availability of dispersal agents (disperser-availability hypothesis) and/or the availability of resources for constructing zoochorous fruits (resource-availability hypothesis). Time period: Tree-inventory plots established between 1934 and 2019. Major taxa studied: Trees with a diameter at breast height (DBH) ≥ 9.55 cm. Location: Amazonia, here defined as the lowland rain forests of the Amazon River basin and the Guiana Shield. Methods: We assigned dispersal modes to a total of 5433 species and morphospecies within 1877 tree-inventory plots across terra-firme, seasonally flooded, and permanently flooded forests. We investigated geographic patterns in the proportional abundance of dispersal modes. We performed an abundance-weighted mean pairwise distance (MPD) test and fit generalized linear models (GLMs) to explain the geographic distribution of dispersal modes. Results: Anemochory was significantly, positively associated with mean annual wind speed, and hydrochory was significantly higher in flooded forests. Dispersal modes did not consistently show significant associations with the availability of resources for constructing zoochorous fruits. A lower dissimilarity in dispersal modes, resulting from a higher dominance of endozoochory, occurred in terra-firme forests (excluding podzols) compared to flooded forests. Main conclusions: The disperser-availability hypothesis was well supported for abiotic dispersal modes (anemochory and hydrochory). The availability of resources for constructing zoochorous fruits seems an unlikely explanation for the distribution of dispersal modes in Amazonia. The association between frugivores and the proportional abundance of zoochory requires further research, as tree recruitment not only depends on dispersal vectors but also on conditions that favour or limit seedling recruitment across forest types