Gamifying the Classroom for the Acquisition of Skills Associated with Machine Learning: A Two-Year Case Study

Machine learning (ML) is the field of science that combines knowledge from artificial intelligence, statistics and mathematics intending to give computers the ability to learn from data without being explicitly programmed to do so. It falls under the umbrella of Data Science and is usually developed by Computer Engineers becoming what is known as Data Scientists. Developing the necessary competences in this field is not a trivial task, and applying innovative methodologies such as gamification can smooth the initial learning curve. In this context, communities offering platforms for open competitions such as Kaggle can be used as a motivating element. The main objective of this work is to gamify the classroom with the idea of providing students with valuable hands-on experience by means of addressing a real problem, as well as the possibility to cooperate and compete simultaneously to acquire ML competences. The innovative teaching experience carried out during two years meant a great motivation, an improvement of the learning capacity and a continuous recycling of knowledge to which Computer Engineers are faced to

Empowering the Data Scientist professional profile through competition dynamics

La Ciencia de Datos es el área que comprende el desarrollo de métodos científicos, procesos y sistemas para extraer conocimiento a partir de datos recopilados previamente, con el objetivo de analizar los procedimientos llevados a cabo actualmente. El perfil profesional asociado a este campo es el del Científico de Datos, generalmente llevado a cabo por Ingenieros Informáticos gracias a que las aptitudes y competencias adquiridas durante su formación se ajustan perfectamente a lo requerido en este puesto laboral. Debido a la necesidad de formación de nuevos Científicos de Datos, entre otros fines, surgen plataformas en las que éstos pueden adquirir una amplia experiencia, como es el caso de Kaggle. El principal objetivo de esta experiencia docente es proporcionar al alumnado una experiencia práctica con un problema real, así como la posibilidad de cooperar y competir al mismo tiempo. Así, la adquisición y el desarrollo de las competencias necesarias en Ciencia de Datos se realiza en un entorno altamente motivador. La realización de actividades relacionadas con este perfil ha tenido una repercusión directa sobre el alumnado, siendo fundamental la motivación, la capacidad de aprendizaje y el reciclaje continuo de conocimientos a los que se someten los Ingenieros Informáticos.Data Science is the area that comprises the development of scientific methods, processes, and systems for extracting knowledge from previously collected data, aiming to analyse the procedures being carried out currently. The professional profile associated with this field is the Data Scientist, generally carried out by Computer Engineers as the skills and competencies acquired during their training are perfectly suited to what this job requires. Due to the need for training new Data Scientists, among other goals, there are different emerging platforms where they can acquire extensive experience, such as Kaggle. The main objective of this teaching experience is to provide students with practical experience on a real problem, as well as the possibility of cooperating and competing at the same time. Thus, the acquisition and development of the necessary competencies in Data Science are carried out in a highly motivating environment. The development of activities related to this profile has had a direct impact on the students, being fundamental the motivation, the learning capacity and the continuous recycling of knowledge to which Computer Engineers are subjected

Genome-wide association analysis of dementia and its clinical endophenotypes reveal novel loci associated with Alzheimer's disease and three causality networks : The GR@ACE project

Introduction: Large variability among Alzheimer's disease (AD) cases might impact genetic discoveries and complicate dissection of underlying biological pathways. Methods: Genome Research at Fundacio ACE (GR@ACE) is a genome-wide study of dementia and its clinical endophenotypes, defined based on AD's clinical certainty and vascular burden. We assessed the impact of known AD loci across endophenotypes to generate loci categories. We incorporated gene coexpression data and conducted pathway analysis per category. Finally, to evaluate the effect of heterogeneity in genetic studies, GR@ACE series were meta-analyzed with additional genome-wide association study data sets. Results: We classified known AD loci into three categories, which might reflect the disease clinical heterogeneity. Vascular processes were only detected as a causal mechanism in probable AD. The meta-analysis strategy revealed the ANKRD31-rs4704171 and NDUFAF6-rs10098778 and confirmed SCIMP-rs7225151 and CD33-rs3865444. Discussion: The regulation of vasculature is a prominent causal component of probable AD. GR@ACE meta-analysis revealed novel AD genetic signals, strongly driven by the presence of clinical heterogeneity in the AD series

Salud de los trabajadores

Actividad física y su relación con los factores de riesgo cardiovascular de carteros chilenosAnálisis de resultados: riesgos psicosociales en el trabajo Suceso-Istas 21 en Cesfam QuellónAusentismo laboral por enfermedades oftalmológicas, Chile 2009Brote de diarreas por norovirus, posterremoto-tsunami, Constitución, Región del MauleCalidad de vida en profesionales de la salud pública chilenaCaracterización del reposo laboral en personal del SSMN durante el primer semestre de 2010Concentración de nicotina en pelo en trabajadores no fumadores expuestos a humo de tabaco ambientalCondiciones de trabajo y bienestar/malestar docente en profesores de enseñanza media de SantiagoDisfunción auditiva inducida por exposición a xilenoErgonomía aplicada al estudio del síndrome de dolor lumbar en el trabajoEstimación de la frecuencia de factores de riesgo cardiovascular en trabajadores de una empresa mineraExposición a plaguicidas inhibidores de la acetilcolinesterasa en Colombia, 2006-2009Factores de riesgo y daños de salud en conductores de una empresa peruana de transporte terrestre, 2009Las consecuencias de la cultura en salud y seguridad ocupacional en una empresa mineraPercepción de cambios en la práctica médica y estrategias de afrontamientoPercepción de la calidad de vida en la Universidad del BiobíoPesos máximos aceptables para tareas de levantamiento manual de carga en población laboral femeninaRiesgo coronario en trabajadores mineros según la función de Framingham adaptada para la población chilenaTrastornos emocionales y riesgo cardiovascular en trabajadores de la salu

Genomic Characterization of Host Factors Related to SARS-CoV-2 Infection in People with Dementia and Control Populations: The GR@ACE/DEGESCO Study

Emerging studies have suggested several chromosomal regions as potential host genetic factors involved in the susceptibility to SARS-CoV-2 infection and disease outcome. We nested a COVID-19 genome-wide association study using the GR@ACE/DEGESCO study, searching for susceptibility factors associated with COVID-19 disease. To this end, we compared 221 COVID-19 confirmed cases with 17,035 individuals in whom the COVID-19 disease status was unknown. Then, we performed a meta-analysis with the publicly available data from the COVID-19 Host Genetics Initiative. Because the APOE locus has been suggested as a potential modifier of COVID-19 disease, we added sensitivity analyses stratifying by dementia status or by disease severity. We confirmed the existence of the 3p21.31 region (LZTFL1, SLC6A20) implicated in the susceptibility to SARS-CoV-2 infection and TYK2 gene might be involved in COVID-19 severity. Nevertheless, no statistically significant association was observed in the COVID-19 fatal outcome or in the stratified analyses (dementia-only and non-dementia strata) for the APOE locus not supporting its involvement in SARS-CoV-2 pathobiology or COVID-19 prognosis

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

Newer generations of multi-target CAR and STAb-T immunotherapeutics: NEXT CART Consortium as a cooperative effort to overcome current limitations

Adoptive T cellular immunotherapies have emerged as relevant approaches for treating cancer patients who have relapsed or become refractory (R/R) to traditional cancer treatments. Chimeric antigen receptor (CAR) T-cell therapy has improved survival in various hematological malignancies. However, significant limitations still impede the widespread adoption of these therapies in most cancers. To advance in this field, six research groups have created the “NEXT Generation CART MAD Consortium” (NEXT CART) in Madrid’s Community, which aims to develop novel cell-based immunotherapies for R/R and poor prognosis cancers. At NEXT CART, various basic and translational research groups and hospitals in Madrid concur to share and synergize their basic expertise in immunotherapy, gene therapy, and immunological synapse, and clinical expertise in pediatric and adult oncology. NEXT CART goal is to develop new cell engineering approaches and treatments for R/R adult and pediatric neoplasms to evaluate in multicenter clinical trials. Here, we discuss the current limitations of T cell-based therapies and introduce our perspective on future developments. Advancement opportunities include developing allogeneic products, optimizing CAR signaling domains, combining cellular immunotherapies, multi-targeting strategies, and improving tumor-infiltrating lymphocytes (TILs)/T cell receptor (TCR) therapy. Furthermore, basic studies aim to identify novel tumor targets, tumor molecules in the tumor microenvironment that impact CAR efficacy, and strategies to enhance the efficiency of the immunological synapse between immune and tumor cells. Our perspective of current cellular immunotherapy underscores the potential of these treatments while acknowledging the existing hurdles that demand innovative solutions to develop their potential for cancer treatment fully

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BACKGROUND: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. METHODS: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. FINDINGS: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. INTERPRETATION: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic. FUNDING: Bill & Melinda Gates Foundation