La Industria del Videojuego en España: Mercury Steam

En el presente trabajo se estudia un sector muy potente que se encuentra en constante crecimiento: la industria del videojuego. En su contenido se muestra la historia del videojuego y la situación e importancia en el mundo empresarial y económico del sector. También se detalla la evolución de una empresa española dedicada a esta industria: Mercury Steam. Toda la información recopilada tiene el objetivo de facilitar la comprensión de la situación actual de una industria que cambia y se renueva constantemente y de cómo está evolucionando el sector en España en una industria que se encuentra en pleno crecimiento en nuestro país

Physical fitness, rating perceived exertion and academic performance in primary school

Existen estudios que han conseguido establecer una relación entre el rendimiento cognitivo y académico de los alumnos y sus niveles de condición física. Los objetivos de esta investigación son estudiar la correlación existente entre el nivel de condición física y la composición corporal con el rendimiento académico, así como analizar la correlación entre dichas variables y la percepción subjetiva del esfuerzo (RPE) por género en alumnos de Educación Primaria. Un total de 69 alumnos de Educación Primaria participaron en el estudio (edad= 12,33±0,47 años, 55,9% niñas y 44,1% niños). La condición física y la composición corporal se evaluaron siguiendo los test de la ALPHA Fitness test Battery para niños y adolescentes. El rendimiento académico se estudió mediante el promedio de notas de las asignaturas instrumentales de Educación Primaria. La RPE se registró en las clases de EF y actividades físicas escolares mediante el uso de la escala RPE de Borg (0-10). Se establecieron correlaciones significativas entre la RPE y el peso de los chicos (r= 0,406, p= 0.02) y las chicas (r= 0,643, p< 0.001) y también con respecto al IMC, chicos (r= 0,508, p= 0.004), chicas (r= 0,621, p< 0.001). Existió una correlación negativa significativa entre el test de la Course Navette y la RPE en el caso de los niños (r= -0,633, p< 0.001) y de las niñas (r= -0,452, p= 0.004). La RPE se correlacionó significativamente con los palieres del test de Course Navette (correlación inversa) y las variables antropométricas, como son el peso y el IMC.There are studies in which it has been possible to establish a relationship between the cognitive and academic performance of students and their levels of physical condition. The objectives of this research are to study the correlation between the physical fitness level and body composition with the academic performance, as well as to analyze the correlation between such variables and the Rating of Perceived Exertion (RPE) of elementary school students by gender. A total of 69 primary school students participated in the study (age= 12.33±0.47 years, 55.9% girls and 44,1% boys). The physical fitness and body composition were evaluated according to the ALPHA Fitness test Battery for children and adolescents. The academic performance was studied by means of the average of notes of the instrumental subjects of primary education. The RPE was recorded in PE classes and school physical activities by using the Borg RPE scale (0-10). Significant correlations were established between the RPE and the weight of the boys (r= 0,406, p= 0.02) and girls (r= 0,643, p< 0.001) and also with respect to the BMI, boys (r= 0,508, p= 0.004), girls (r= 0,621, p< 0.001). There was a significant negative correlation between the Course Navette test and the RPE in the case of boys (r= -0,633, p< 0.001) and girls (r= -0,452, p= 0.004). The RPE correlated significantly with the stages of the Course Navette test (inverse correlation) and with the body composition variables, such as weight and BMI

A Mathematical Description of the Bone Marrow Dynamics during CAR T-Cell Therapy in B-Cell Childhood Acute Lymphoblastic Leukemia

Chimeric Antigen Receptor (CAR) T-cell therapy has demonstrated high rates of response in recurrent B-cell Acute Lymphoblastic Leukemia in children and young adults. Despite this success, a fraction of patients' experience relapse after treatment. Relapse is often preceded by recovery of healthy B cells, which suggests loss or dysfunction of CAR T-cells in bone marrow. This site is harder to access, and thus is not monitored as frequently as peripheral blood. Understanding the interplay between B cells, leukemic cells, and CAR T-cells in bone marrow is paramount in ascertaining the causes of lack of response. In this paper, we put forward a mathematical model representing the interaction between constantly renewing B cells, CAR T-cells, and leukemic cells in the bone marrow. Our model accounts for the maturation dynamics of B cells and incorporates effector and memory CAR T-cells. The model provides a plausible description of the dynamics of the various cellular compartments in bone marrow after CAR T infusion. After exploration of the parameter space, we found that the dynamics of CAR T product and disease were independent of the dose injected, initial B-cell load, and leukemia burden. We also show theoretically the importance of CAR T product attributes in determining therapy outcome, and have studied a variety of possible response scenarios, including second dosage schemes. We conclude by setting out ideas for the refinement of the model.This work was partially supported by the Fundacion Espanola para la Ciencia y la Tecnologia (UCA PR214), the Asociacion Pablo Ugarte (APU, Spain), Junta de Comunidades de Castilla-La Mancha (SBPLY/17/180501/000154), Ministry of Science and Technology, Spain (PID2019110895RB-I00), and Inversion Territorial Integrada de la Provincia de Cadiz (ITI-0038-2019)

High-Dimensional Analysis of Single-Cell Flow Cytometry Data Predicts Relapse in Childhood Acute Lymphoblastic Leukaemia

B-cell Acute Lymphoblastic Leukaemia is one of the most common cancers in childhood, with 20% of patients eventually relapsing. Flow cytometry is routinely used for diagnosis and follow-up, but it currently does not provide prognostic value at diagnosis. The volume and the high-dimensional character of this data makes it ideal for its exploitation by means of Artificial Intelligence methods. We collected flow cytometry data from 56 patients from two hospitals. We analysed differences in intensity of marker expression in order to predict relapse at the moment of diagnosis. We finally correlated this data with biomolecular information, constructing a classifier based on CD38 expression. Artificial intelligence methods may help in unveiling information that is hidden in high-dimensional oncological data. Flow cytometry studies of haematological malignancies provide quantitative data with the potential to be used for the construction of response biomarkers. Many computational methods from the bioinformatics toolbox can be applied to these data, but they have not been exploited in their full potential in leukaemias, specifically for the case of childhood B-cell Acute Lymphoblastic Leukaemia. In this paper, we analysed flow cytometry data that were obtained at diagnosis from 56 paediatric B-cell Acute Lymphoblastic Leukaemia patients from two local institutions. Our aim was to assess the prognostic potential of immunophenotypical marker expression intensity. We constructed classifiers that are based on the Fisher's Ratio to quantify differences between patients with relapsing and non-relapsing disease. We also correlated this with genetic information. The main result that arises from the data was the association between subexpression of marker CD38 and the probability of relapse

Surrogate indices of insulin resistance using the Matsuda index as reference in adult men—a computational approach

Background: Overweight and obesity, high blood pressure, hyperglycemia, hyperlipidemia, and insulin resistance (IR) are strongly associated with non-communicable diseases (NCDs), including type 2 diabetes, cardiovascular disease, stroke, and cancer. Different surrogate indices of IR are derived and validated with the euglycemic–hyperinsulinemic clamp (EHC) test. Thus, using a computational approach to predict IR with Matsuda index as reference, this study aimed to determine the optimal cutoff value and diagnosis accuracy for surrogate indices in non-diabetic young adult men. Methods: A cross-sectional descriptive study was carried out with 93 young men (ages 18–31). Serum levels of glucose and insulin were analyzed in the fasting state and during an oral glucose tolerance test (OGTT). Additionally, clinical, biochemical, hormonal, and anthropometric characteristics and body composition (DEXA) were determined. The computational approach to evaluate the IR diagnostic accuracy and cutoff value using difference parameters was examined, as well as other statistical tools to make the output robust. Results: The highest sensitivity and specificity at the optimal cutoff value, respectively, were established for the Homeostasis model assessment of insulin resistance index (HOMA-IR) (0.91; 0.98; 3.40), the Quantitative insulin sensitivity check index (QUICKI) (0.98; 0.96; 0.33), the triglyceride-glucose (TyG)-waist circumference index (TyG-WC) (1.00; 1.00; 427.77), the TyG-body mass index (TyG-BMI) (1.00; 1.00; 132.44), TyG-waist-to-height ratio (TyG-WHtR) (0.98; 1.00; 2.48), waist-to-height ratio (WHtR) (1.00; 1.00; 0.53), waist circumference (WC) (1.00; 1.00; 92.63), body mass index (BMI) (1.00; 1.00; 28.69), total body fat percentage (TFM) (%) (1.00; 1.00; 31.07), android fat (AF) (%) (1.00; 0.98; 40.33), lipid accumulation product (LAP) (0.84; 1.00; 45.49), leptin (0.91; 1.00; 16.08), leptin/adiponectin ratio (LAR) (0.84; 1.00; 1.17), and fasting insulin (0.91; 0.98; 16.01). Conclusions: The computational approach was used to determine the diagnosis accuracy and the optimal cutoff value for IR to be used in preventive healthcare.Fil: Malagón Soriano, Víctor Antonio. Universidad Nacional de Colombia; ColombiaFil: Ledezma Forero, Andres Julian. Universidad Nacional de Colombia; ColombiaFil: Espinel Pachon, Cristian Felipe. Universidad Nacional de Colombia. Facultad de Medicina; ColombiaFil: Burgos Cárdenas, Álvaro Javier. Universidad Nacional de Colombia. Facultad de Medicina; ColombiaFil: Garces, Maria Fernanda. Universidad Nacional de Colombia. Facultad de Medicina; ColombiaFil: Ortega Ramírez, Gustavo Eduardo. Universidad Nacional de Colombia. Facultad de Medicina; ColombiaFil: Franco Vega, Roberto. Universidad Nacional de Colombia. Facultad de Medicina; ColombiaFil: Peralta Franco, Jhon Jairo. Universidad Nacional de Colombia. Facultad de Medicina; ColombiaFil: Maldonado Acosta, Luis Miguel. Universidad Nacional de Colombia. Facultad de Medicina; ColombiaFil: Rubio Romero, Jorge Andres. Universidad Nacional de Colombia. Facultad de Medicina; ColombiaFil: Mercado Pedroza, Manuel Esteban. Universidad Nacional de Colombia. Facultad de Medicina; ColombiaFil: Caminos Cepeda, Sofia Alexandra. Universitat Pompeu Fabra; EspañaFil: Lacunza, Ezequiel. Universidad Nacional de La Plata. Facultad de Ciencias Médicas. Centro de Investigaciones Inmunológicas Básicas y Aplicadas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Rivera Moreno, Carlos Armando. Universidad Nacional de Colombia. Facultad de Medicina; ColombiaFil: Darghan Contreras, Aquiles Enrique. Universidad Nacional de Colombia. Facultad de Medicina; ColombiaFil: Ruiz Parra, Ariel Iván. Universidad Nacional de Colombia. Facultad de Medicina; ColombiaFil: Caminos, Jorge E.. Universidad Nacional de Colombia. Facultad de Medicina; Colombi

DVINO: A RISC-V vector processor implemented in 65nm technology

This paper describes the design, verification, implementation and fabrication of the Drac Vector IN-Order (DVINO) processor, a RISC-V vector processor capable of booting Linux jointly developed by BSC, CIC-IPN, IMB-CNM (CSIC), and UPC. The DVINO processor includes an internally developed two-lane vector processor unit as well as a Phase Locked Loop (PLL) and an Analog-to-Digital Converter (ADC). The paper summarizes the design from architectural as well as logic synthesis and physical design in CMOS 65nm technology.The DRAC project is co-financed by the European Union Regional Development Fund within the framework of the ERDF Operational Program of Catalonia 2014-2020 with a grant of 50% of total eligible cost. The authors are part of RedRISCV which promotes activities around open hardware. The Lagarto Project is supported by the Research and Graduate Secretary (SIP) of the Instituto Politecnico Nacional (IPN) from Mexico, and by the CONACyT scholarship for Center for Research in Computing (CIC-IPN).Peer ReviewedArticle signat per 43 autors/es: Guillem Cabo∗, Gerard Candón∗, Xavier Carril∗, Max Doblas∗, Marc Domínguez∗, Alberto González∗, Cesar Hernández†, Víctor Jiménez∗, Vatistas Kostalampros∗, Rubén Langarita∗, Neiel Leyva†, Guillem López-Paradís∗, Jonnatan Mendoza∗, Francesco Minervini∗, Julian Pavón∗, Cristobal Ramírez∗, Narcís Rodas∗, Enrico Reggiani∗, Mario Rodríguez∗, Carlos Rojas∗, Abraham Ruiz∗, Víctor Soria∗, Alejandro Suanes‡, Iván Vargas∗, Roger Figueras∗, Pau Fontova∗, Joan Marimon∗, Víctor Montabes∗, Adrián Cristal∗, Carles Hernández∗, Ricardo Martínez‡, Miquel Moretó∗§, Francesc Moll∗§, Oscar Palomar∗§, Marco A. Ramírez†, Antonio Rubio§, Jordi Sacristán‡, Francesc Serra-Graells‡, Nehir Sonmez∗, Lluís Terés‡, Osman Unsal∗, Mateo Valero∗§, Luís Villa† // ∗Barcelona Supercomputing Center (BSC), Barcelona, Spain. Email: [email protected]; †Centro de Investigación en Computación, Instituto Politécnico Nacional (CIC-IPN), Mexico City, Mexico; ‡ Institut de Microelectronica de Barcelona, IMB-CNM (CSIC), Spain. Email: [email protected]; §Universitat Politecnica de Catalunya (UPC), Barcelona, Spain. Email: [email protected] (author's final draft

Surrogate indices of insulin resistance using the Matsuda index as reference in adult men—a computational approach

BackgroundOverweight and obesity, high blood pressure, hyperglycemia, hyperlipidemia, and insulin resistance (IR) are strongly associated with non-communicable diseases (NCDs), including type 2 diabetes, cardiovascular disease, stroke, and cancer. Different surrogate indices of IR are derived and validated with the euglycemic–hyperinsulinemic clamp (EHC) test. Thus, using a computational approach to predict IR with Matsuda index as reference, this study aimed to determine the optimal cutoff value and diagnosis accuracy for surrogate indices in non-diabetic young adult men.MethodsA cross-sectional descriptive study was carried out with 93 young men (ages 18–31). Serum levels of glucose and insulin were analyzed in the fasting state and during an oral glucose tolerance test (OGTT). Additionally, clinical, biochemical, hormonal, and anthropometric characteristics and body composition (DEXA) were determined. The computational approach to evaluate the IR diagnostic accuracy and cutoff value using difference parameters was examined, as well as other statistical tools to make the output robust.ResultsThe highest sensitivity and specificity at the optimal cutoff value, respectively, were established for the Homeostasis model assessment of insulin resistance index (HOMA-IR) (0.91; 0.98; 3.40), the Quantitative insulin sensitivity check index (QUICKI) (0.98; 0.96; 0.33), the triglyceride-glucose (TyG)-waist circumference index (TyG-WC) (1.00; 1.00; 427.77), the TyG-body mass index (TyG-BMI) (1.00; 1.00; 132.44), TyG-waist-to-height ratio (TyG-WHtR) (0.98; 1.00; 2.48), waist-to-height ratio (WHtR) (1.00; 1.00; 0.53), waist circumference (WC) (1.00; 1.00; 92.63), body mass index (BMI) (1.00; 1.00; 28.69), total body fat percentage (TFM) (%) (1.00; 1.00; 31.07), android fat (AF) (%) (1.00; 0.98; 40.33), lipid accumulation product (LAP) (0.84; 1.00; 45.49), leptin (0.91; 1.00; 16.08), leptin/adiponectin ratio (LAR) (0.84; 1.00; 1.17), and fasting insulin (0.91; 0.98; 16.01).ConclusionsThe computational approach was used to determine the diagnosis accuracy and the optimal cutoff value for IR to be used in preventive healthcare

Long-Term Real-World Effectiveness and Safety of Ustekinumab in Crohn’s Disease Patients: The SUSTAIN Study

Background Large real-world-evidence studies are required to confirm the durability of response, effectiveness, and safety of ustekinumab in Crohn’s disease (CD) patients in real-world clinical practice. Methods A retrospective, multicentre study was conducted in Spain in patients with active CD who had received ≥1 intravenous dose of ustekinumab for ≥6 months. Primary outcome was ustekinumab retention rate; secondary outcomes were to identify predictive factors for drug retention, short-term remission (week 16), loss of response and predictive factors for short-term efficacy and loss of response, and ustekinumab safety. Results A total of 463 patients were included. Mean baseline Harvey-Bradshaw Index was 8.4. A total of 447 (96.5%) patients had received prior biologic therapy, 141 (30.5%) of whom had received ≥3 agents. In addition, 35.2% received concomitant immunosuppressants, and 47.1% had ≥1 abdominal surgery. At week 16, 56% had remission, 70% had response, and 26.1% required dose escalation or intensification; of these, 24.8% did not subsequently reduce dose. After a median follow-up of 15 months, 356 (77%) patients continued treatment. The incidence rate of ustekinumab discontinuation was 18% per patient-year of follow-up. Previous intestinal surgery and concomitant steroid treatment were associated with higher risk of ustekinumab discontinuation, while a maintenance schedule every 12 weeks had a lower risk; neither concomitant immunosuppressants nor the number of previous biologics were associated with ustekinumab discontinuation risk. Fifty adverse events were reported in 39 (8.4%) patients; 4 of them were severe (2 infections, 1 malignancy, and 1 fever). Conclusions Ustekinumab is effective and safe as short- and long-term treatment in a refractory cohort of CD patients in real-world clinical practice

Using Interpretable Machine Learning to Identify Baseline Predictive Factors of Remission and Drug Durability in Crohn’s Disease Patients on Ustekinumab

Ustekinumab has shown efficacy in Crohn's Disease (CD) patients. To identify patient profiles of those who benefit the most from this treatment would help to position this drug in the therapeutic paradigm of CD and generate hypotheses for future trials. The objective of this analysis was to determine whether baseline patient characteristics are predictive of remission and the drug durability of ustekinumab, and whether its positioning with respect to prior use of biologics has a significant effect after correcting for disease severity and phenotype at baseline using interpretable machine learning. Patients' data from SUSTAIN, a retrospective multicenter single-arm cohort study, were used. Disease phenotype, baseline laboratory data, and prior treatment characteristics were documented. Clinical remission was defined as the Harvey Bradshaw Index <= 4 and was tracked longitudinally. Drug durability was defined as the time until a patient discontinued treatment. A total of 439 participants from 60 centers were included and a total of 20 baseline covariates considered. Less exposure to previous biologics had a positive effect on remission, even after controlling for baseline disease severity using a non-linear, additive, multivariable model. Additionally, age, body mass index, and fecal calprotectin at baseline were found to be statistically significant as independent negative risk factors for both remission and drug survival, with further risk factors identified for remission