57 research outputs found

    Análisis económico financiero de Bodegas Riojanas S.A.

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    Con el objeto de realizar un análisis económico financiero de una empresa vitivinícola a través de sus cuentas anuales, se ha elegido la sociedad Bodegas Riojanas S.A. Para llevar a cabo el estudio, se procederá a explicar brevemente el Estado de Flujos de Efectivo, partiendo de lo general, y posteriormente se centrará en los datos de la bodega para llevar a cabo dicho análisis. Se trata de una bodega que se dedica a la elaboración de diferentes tipos de vino, de la que analizaremos especialmente el Estado de Flujos de Efectivo, centrándonos en los flujos de explotación, de inversión y de financiación y posteriormente se realizará un análisis conjunto de ellos, así como de la variación neta de efectivo de un periodo de 5 años. Se procederá además al estudio del fondo de maniobra de la empresa, y de una serie de ratios de liquidez, de tesorería, de rentabilidad económica y de rentabilidad financiera, entre otros. Para finalizar, se comparará la empresa con el sector, obteniendo dichos datos de la Central de Balances del Banco de España.In order to carry out an economic and financial analysis of a wine business using its anual accounts, we have chosen the Company Bodegas Riojanas S.A. For this purpose, first of all, we will explain briefly the cash flow statement, going from the general to specific data of the wine cellar. We will focus on operating cash flows, on investment flows, and on fiancial flows. Then, we will carry out a joint analysis of all of them, as well as, of net cash flow over a five-years period. Furthermore, we will study the operating working capital, liquidity ratios, treasury ratios, economic profitability, financial return, among others. Finally, we will compare the Company with the sector, obtaining these data from the Central de Balances del Banco de España.Departamento de Economía Financiera y ContabilidadGrado en Administración y Dirección de Empresa

    Detection of label-free cancer biomarkers using nickel nanoislands and quartz crystal microbalance

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    We present a technique for the label-free detection and recognition of cancer biomarkers using metal nanoislands intended to be integrated in a novel type of nanobiosensor. His-tagged (scFv)-F7N1N2 is the antibody fragment which is directly immobilized, by coordinative bonds, onto ~5 nm nickel islands, then deposited on the surface of a quartz crystal of a quartz crystal microbalance (QCM) to validate the technique. Biomarker GTPase RhoA was investigated because it has been found to be overexpressed in various tumors and because we have recently isolated and characterized a new conformational scFv which selectively recognizes the active form of RhoA. We implemented a surface chemistry involving an antibiofouling coating of polyethylene glycol silane (PEG-silane) (<2 nm thick) and Ni nanoislands to reach a label-free detection of the active antigen conformation of RhoA, at various concentrations. The methodology proposed here proves the viability of the concept by using Ni nanoislands as an anchoring surface layer enabling the detection of a specific conformation of a protein, identified as a potential cancer biomarker. Hence, this novel methodology can be transferred to a nanobiosensor to detect, at lower time consumption and with high sensitivity, specific biomolecules

    Machine Learning Improves Risk Stratification in Myelofibrosis: An Analysis of the Spanish Registry of Myelofibrosis

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    Myelofibrosis (MF) is a myeloproliferative neoplasm (MPN) with heterogeneous clinical course. Allogeneic hematopoietic cell transplantation remains the only curative therapy, but its morbidity and mortality require careful candidate selection. Therefore, accurate disease risk prognostication is critical for treatment decision-making. We obtained registry data from patients diagnosed with MF in 60 Spanish institutions (N = 1386). These were randomly divided into a training set (80%) and a test set (20%). A machine learning (ML) technique (random forest) was used to model overall survival (OS) and leukemia-free survival (LFS) in the training set, and the results were validated in the test set. We derived the AIPSS-MF (Artificial Intelligence Prognostic Scoring System for Myelofibrosis) model, which was based on 8 clinical variables at diagnosis and achieved high accuracy in predicting OS (training set c-index, 0.750; test set c-index, 0.744) and LFS (training set c-index, 0.697; test set c-index, 0.703). No improvement was obtained with the inclusion of MPN driver mutations in the model. We were unable to adequately assess the potential benefit of including adverse cytogenetics or high-risk mutations due to the lack of these data in many patients. AIPSS-MF was superior to the IPSS regardless of MF subtype and age range and outperformed the MYSEC-PM in patients with secondary MF. In conclusion, we have developed a prediction model based exclusively on clinical variables that provides individualized prognostic estimates in patients with primary and secondary MF. The use of AIPSS-MF in combination with predictive models that incorporate genetic information may improve disease risk stratification

    Status and Recent Results of the Acoustic Neutrino Detection Test System AMADEUS

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    The AMADEUS system is an integral part of the ANTARES neutrino telescope in the Mediterranean Sea. The project aims at the investigation of techniques for acoustic neutrino detection in the deep sea. Installed at a depth of more than 2000m, the acoustic sensors of AMADEUS are based on piezo-ceramics elements for the broad-band recording of signals with frequencies ranging up to 125kHz. AMADEUS was completed in May 2008 and comprises six "acoustic clusters", each one holding six acoustic sensors that are arranged at distances of roughly 1m from each other. The clusters are installed with inter-spacings ranging from 15m to 340m. Acoustic data are continuously acquired and processed at a computer cluster where online filter algorithms are applied to select a high-purity sample of neutrino-like signals. 1.6 TB of data were recorded in 2008 and 3.2 TB in 2009. In order to assess the background of neutrino-like signals in the deep sea, the characteristics of ambient noise and transient signals have been investigated. In this article, the AMADEUS system will be described and recent results will be presented.Comment: 7 pages, 8 figures. Proceedings of ARENA 2010, the 4th International Workshop on Acoustic and Radio EeV Neutrino Detection Activitie

    Measurement of Atmospheric Neutrino Oscillations with the ANTARES Neutrino Telescope

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    The data taken with the ANTARES neutrino telescope from 2007 to 2010, a total live time of 863 days, are used to measure the oscillation parameters of atmospheric neutrinos. Muon tracks are reconstructed with energies as low as 20 GeV. Neutrino oscillations will cause a suppression of vertical upgoing muon neutrinos of such energies crossing the Earth. The parameters determining the oscillation of atmospheric neutrinos are extracted by fitting the event rate as a function of the ratio of the estimated neutrino energy and reconstructed flight path through the Earth. Measurement contours of the oscillation parameters in a two-flavour approximation are derived. Assuming maximum mixing, a mass difference of Δm322=(3.1±0.9)103\Delta m_{32}^2=(3.1\pm 0.9)\cdot 10^{-3} eV2^2 is obtained, in good agreement with the world average value.Comment: 9 pages, 5 figure

    COVID-19 Severity and Survival over Time in Patients with Hematologic Malignancies: A Population-Based Registry Study

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    Mortality rates for COVID-19 have declined over time in the general population, but data in patients with hematologic malignancies are contradictory. We identified independent prognostic factors for COVID-19 severity and survival in unvaccinated patients with hematologic malignancies, compared mortality rates over time and versus non-cancer inpatients, and investigated post COVID-19 condition. Data were analyzed from 1166 consecutive, eligible patients with hematologic malignancies from the population-based HEMATO-MADRID registry, Spain, with COVID-19 prior to vaccination roll-out, stratified into early (February–June 2020; n = 769 (66%)) and later (July 2020–February 2021; n = 397 (34%)) cohorts. Propensity-score matched non-cancer patients were identified from the SEMI-COVID registry. A lower proportion of patients were hospitalized in the later waves (54.2%) compared to the earlier (88.6%), OR 0.15, 95%CI 0.11–0.20. The proportion of hospitalized patients admitted to the ICU was higher in the later cohort (103/215, 47.9%) compared with the early cohort (170/681, 25.0%, 2.77; 2.01–3.82). The reduced 30-day mortality between early and later cohorts of non-cancer inpatients (29.6% vs. 12.6%, OR 0.34; 0.22–0.53) was not paralleled in inpatients with hematologic malignancies (32.3% vs. 34.8%, OR 1.12; 0.81–1.5). Among evaluable patients, 27.3% had post COVID-19 condition. These findings will help inform evidence-based preventive and therapeutic strategies for patients with hematologic malignancies and COVID-19 diagnosis.Depto. de MedicinaFac. de MedicinaTRUEFundación Madrileña de Hematología y HemoterapiaFundación Leucemia y LinfomaAsociación Madrileña de Hematología y Hemoterapiapu

    A First Search for coincident Gravitational Waves and High Energy Neutrinos using LIGO, Virgo and ANTARES data from 2007

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    We present the results of the first search for gravitational wave bursts associated with high energy neutrinos. Together, these messengers could reveal new, hidden sources that are not observed by conventional photon astronomy, particularly at high energy. Our search uses neutrinos detected by the underwater neutrino telescope ANTARES in its 5 line configuration during the period January - September 2007, which coincided with the fifth and first science runs of LIGO and Virgo, respectively. The LIGO-Virgo data were analysed for candidate gravitational-wave signals coincident in time and direction with the neutrino events. No significant coincident events were observed. We place limits on the density of joint high energy neutrino - gravitational wave emission events in the local universe, and compare them with densities of merger and core-collapse events.Comment: 19 pages, 8 figures, science summary page at http://www.ligo.org/science/Publication-S5LV_ANTARES/index.php. Public access area to figures, tables at https://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=p120000

    The evolution of the ventilatory ratio is a prognostic factor in mechanically ventilated COVID-19 ARDS patients

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    Background: Mortality due to COVID-19 is high, especially in patients requiring mechanical ventilation. The purpose of the study is to investigate associations between mortality and variables measured during the first three days of mechanical ventilation in patients with COVID-19 intubated at ICU admission. Methods: Multicenter, observational, cohort study includes consecutive patients with COVID-19 admitted to 44 Spanish ICUs between February 25 and July 31, 2020, who required intubation at ICU admission and mechanical ventilation for more than three days. We collected demographic and clinical data prior to admission; information about clinical evolution at days 1 and 3 of mechanical ventilation; and outcomes. Results: Of the 2,095 patients with COVID-19 admitted to the ICU, 1,118 (53.3%) were intubated at day 1 and remained under mechanical ventilation at day three. From days 1 to 3, PaO2/FiO2 increased from 115.6 [80.0-171.2] to 180.0 [135.4-227.9] mmHg and the ventilatory ratio from 1.73 [1.33-2.25] to 1.96 [1.61-2.40]. In-hospital mortality was 38.7%. A higher increase between ICU admission and day 3 in the ventilatory ratio (OR 1.04 [CI 1.01-1.07], p = 0.030) and creatinine levels (OR 1.05 [CI 1.01-1.09], p = 0.005) and a lower increase in platelet counts (OR 0.96 [CI 0.93-1.00], p = 0.037) were independently associated with a higher risk of death. No association between mortality and the PaO2/FiO2 variation was observed (OR 0.99 [CI 0.95 to 1.02], p = 0.47). Conclusions: Higher ventilatory ratio and its increase at day 3 is associated with mortality in patients with COVID-19 receiving mechanical ventilation at ICU admission. No association was found in the PaO2/FiO2 variation

    Cross-disease Meta-analysis of Genome-wide Association Studies for Systemic Sclerosis and Rheumatoid Arthritis Reveals IRF4 as a New Common Susceptibility Locus

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    Objectives: Systemic sclerosis (SSc) and rheumatoid arthritis (RA) are autoimmune diseases that share clinical and immunological characteristics. To date, several shared SSc- RA loci have been identified independently. In this study, we aimed to systematically search for new common SSc-RA loci through an inter-disease meta-GWAS strategy. Methods: We performed a meta-analysis combining GWAS datasets of SSc and RA using a strategy that allowed identification of loci with both same-direction and opposingdirection allelic effects. The top single-nucleotide polymorphisms (SNPs) were followed-up in independent SSc and RA case-control cohorts. This allowed us to increase the sample size to a total of 8,830 SSc patients, 16,870 RA patients and 43,393 controls. Results: The cross-disease meta-analysis of the GWAS datasets identified several loci with nominal association signals (P-value < 5 x 10-6), which also showed evidence of association in the disease-specific GWAS scan. These loci included several genomic regions not previously reported as shared loci, besides risk factors associated with both diseases in previous studies. The follow-up of the putatively new SSc-RA loci identified IRF4 as a shared risk factor for these two diseases (Pcombined = 3.29 x 10-12). In addition, the analysis of the biological relevance of the known SSc-RA shared loci pointed to the type I interferon and the interleukin 12 signaling pathways as the main common etiopathogenic factors. Conclusions: Our study has identified a novel shared locus, IRF4, for SSc and RA and highlighted the usefulness of cross-disease GWAS meta-analysis in the identification of common risk loci
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