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3,399 results on '"Armero A"'

1. Bayesian network approach to building an affective module for a driver behavioural model

Author

Młynarczyk, Dorota, Calvo, Gabriel, Palmi-Perales, Francisco, Armero, Carmen, Gómez-Rubio, Virgilio, and Martinez-Iranzo, Ursula

Subjects
Statistics - Applications
Abstract

This paper focuses on the affective component of a Driver Behavioural Model (DBM), specifically modelling some driver's mental states, such as mental load and active fatigue, which may affect driving performance. We used Bayesian networks (BNs) to explore the dependencies between various relevant variables and estimate the probability that a driver was in a particular mental state based on their physiological and demographic conditions. Through this approach, our goal is to improve our understanding of driver behaviour in dynamic environments, with potential applications in traffic safety and autonomous vehicle technologies.

Published
2025

2. Bayesian competing risks survival modeling for assessing the cause of death of patients with heart failure

Author

Gutiérrez-Botella, Jesús, Armero, Carmen, Kneib, Thomas, Pata, María P., and García-Seara, Javier

Subjects
Statistics - Applications
Abstract

Competing risk models are survival models with several events of interest acting in competition and whose occurrence is only observed for the event that occurs first in time. This paper presents a Bayesian approach to these models in which the issue of model selection is treated in a special way by proposing generalizations of some of the Bayesian procedures used in univariate survival analysis. This research is motivated by a study on the survival of patients with hearth failure undergoing cardiac resynchronization therapy, a procedure which involves the implant of a device to stabilize the heartbeat. Two different causes of causes of death have been considered: cardiovascular and non-cardiovascular, and a set of baseline covariates are examined in order to better understand their relationship with both causes of death. Model selection procedures and model checking analyses have been implemented and assessed. The posterior distribution of some relevant outputs such as transition probabilities have been computed and discussed.

Published
2024

5. Bayesian regularization for flexible baseline hazard functions in Cox survival models

Author

Lázaro, Elena, Armero, Carmen, and Alvares, Danilo

Subjects
Statistics - Methodology
Abstract

Fully Bayesian methods for Cox models specify a model for the baseline hazard function. Parametric approaches generally provide monotone estimations. Semi-parametric choices allow for more flexible patterns but they can suffer from overfitting and instability. Regularization methods through prior distributions with correlated structures usually give reasonable answers to these types of situations. We discuss Bayesian regularization for Cox survival models defined via flexible baseline hazards specified by a mixture of piecewise constant functions and by a cubic B-spline function. For those "semiparametric" proposals, different prior scenarios ranging from prior independence to particular correlated structures are discussed in a real study with micro-virulence data and in an extensive simulation scenario that includes different data sample and time axis partition sizes in order to capture risk variations. The posterior distribution of the parameters was approximated using Markov chain Monte Carlo methods. Model selection was performed in accordance with the Deviance Information Criteria and the Log Pseudo-Marginal Likelihood. The results obtained reveal that, in general, Cox models present great robustness in covariate effects and survival estimates independent of the baseline hazard specification. In relation to the "semi-parametric" baseline hazard specification, the B-splines hazard function is less dependent on the regularization process than the piecewise specification because it demands a smaller time axis partition to estimate a similar behaviour of the risk., Comment: Accepted version. First published in Biometrical Journal on 03 September 2020. Published in Biometrical Journal, 63(1), 7-26

Published
2024
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6. A versatile and efficient method to isolate nuclei from low-input cryopreserved tissues for single-nuclei transcriptomics

Author

Cristopher Segovia, Vincent Desrosiers, Fatemeh Khadangi, Karine Robitaille, Victoria Saavedra Armero, Myreille D’Astous, Gabriel Khelifi, Alain Bergeron, Samer Hussein, Maxime Richer, Yohan Bossé, Yves Fradet, Vincent Fradet, and Steve Bilodeau

Subjects
Nuclei isolation, Tissue heterogeneity, Transcriptomics, Cancer, Tissue homogenization, Nuclei sorting, Medicine, Science
Abstract

Abstract Clinical samples are vital for understanding diseases, but their scarcity requires refined research methods. Emerging single-cell technologies offer detailed views of tissue heterogeneity but need sufficient fully characterized tissues. We developed an optimized single-nuclei RNA sequencing (snRNA-seq) protocol to extract nuclei from just 15 mg of cryopreserved human tissue. Applied to four cancer tissues (brain, bladder, lung, prostate), it profiled 1550–7468 nuclei per tissue, revealing heterogeneity comparable to public single-cell atlases. This method enhances the use and sharing of rare, cryopreserved biospecimens, supporting research where sample quantity is limited and full tissue characterization is needed.

Published
2025
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7. Comparative analysis of the yields of dicentrics and chromosomal translocations

Author

Młynarczyk, Dorota, Puig, Pedro, Barquinero, Joan Francesc, Armero, Carmen, and Gómez-Rubio, Virgilio

Subjects
Physics - Medical Physics
Abstract

Purpose: Chromosomal dicentrics and translocations are commonly employed as biomarkers to estimate radiation doses. The main goal of this article is to perform a comparative analysis of yields of both types of aberrations. The objective is to determine if there are relevant distinctions between both yields, allowing for a comprehensive assessment of their respective suitability and accuracy in the estimation of radiation doses. Materials and Methods: The analysis involved data from a partial-radiation simulation study with the calibration data obtained through two scoring methods: conventional and PAINT modified. Subsequently, a Bayesian bivariate zero-inflated Poisson model was employed to compare the posterior marginal density of the mean of dicentrics and translocations and assess the differences between them. Results: When employing the conventional method of scoring, the findings indicate that there is no notable disparity between the yield of observed translocations and dicentrics. However, when utilizing the PAINT modified method, a notable discrepancy is observed for higher doses, indicating a relevant difference in the mean number of the two types aberrations. Conclusions: The choice of scoring method significantly influences the analysis of radiation-induced aberrations, especially when distinguishing between complex and simple chromosomal formations. Further research and analysis are necessary to gain a deeper understanding of the factors and mechanisms impacting the formation of dicentrics and translocations., Comment: 13 pages, 4 figures

Published
2023

8. Selecting the best compositions of a wheelchair basketball team: a data-driven approach

Author

Calvo, Gabriel, Armero, Carmen, Grimm, Bernd, and Ley, Christophe

Subjects
Statistics - Applications
Abstract

Wheelchair basketball, regulated by the International Wheelchair Basketball Federation, is a sport designed for individuals with physical disabilities. This paper presents a data-driven tool that effectively determines optimal team line-ups based on past performance data and metrics for player effectiveness. Our proposed methodology involves combining a Bayesian longitudinal model with an integer linear problem to optimise the line-up of a wheelchair basketball team. To illustrate our approach, we use real data from a team competing in the Rollstuhlbasketball Bundesliga, namely the Doneck Dolphins Trier. We consider three distinct performance metrics for each player and incorporate uncertainty from the posterior predictive distribution of the longitudinal model into the optimisation process. The results demonstrate the tool's ability to select the most suitable team compositions and calculate posterior probabilities of compatibility or incompatibility among players on the court.

Published
2023

9. A Bayesian hidden Markov model for assessing the hot hand phenomenon in basketball shooting performance

Author

Calvo, Gabriel, Armero, Carmen, and Spezia, Luigi

Subjects
Statistics - Applications
Abstract

Sports data analytics is a relevant topic in applied statistics that has been growing in importance in recent years. In basketball, a player or team has a hot hand when their performance during a match is better than expected or they are on a streak of making consecutive shots. This phenomenon has generated a great deal of controversy with detractors claiming its non-existence while other authors indicate its evidence. In this work, we present a Bayesian longitudinal hidden Markov model that analyses the hot hand phenomenon in consecutive basketball shots, each of which can be either missed or made. Two possible states (cold or hot) are assumed in the hidden Markov chains of events, and the probability of success for each throw is modelled by considering both the corresponding hidden state and the distance to the basket. This model is applied to a real data set, the Miami Heat team in the season 2005-2006 of the USA National Basketball Association. We show that this model is a powerful tool for assessing the overall performance of a team during a match or a season, and, in particular, for quantifying the magnitude of the team streaks in probabilistic terms.

Published
2023

10. Erradicación de Helicobacter pylori con tratamiento de primera línea en un hospital de alta complejidad del suroccidente colombiano

Author

Mauricio Sepúlveda Copete, Nelson Enrique Rojas Rojas, Carlos Julio Vargas Potes, Carolina Agudelo Gutierrez, Heidy Lizeth Benavides Armero, Ana Fernanda Mejía Hurtado, David Alejandro Pantoja Castro, Leidy Johanna Hurtado Bermúdez, Stefania Cruz Calderón, Michelle González Hurtado, and Carlos Arturo Rojas Rodríguez

Subjects
Helicobacter pylori, Erradicación, Prueba de aliento, Farmacorresistencia microbiana, Adherencia al tratamiento, Diseases of the digestive system. Gastroenterology, RC799-869
Abstract

Introducción y objetivos: confirmar la erradicación de Helicobacter pylori es esencial debido al aumento de la resistencia antimicrobiana a diferentes esquemas de tratamiento. El objetivo principal del estudio es determinar el porcentaje de erradicación de H. pylori por medio de la prueba de aliento con carbono 14 (14C). Materiales y métodos: se realizó un estudio transversal con componente analítico, con recolección retrospectiva de la información mediante la revisión de historias clínicas de pacientes que recibieron tratamiento erradicador para H. pylori y tuvieron una posterior confirmación de la erradicación mediante la prueba de aliento con 14C en el Hospital Universitario Fundación Valle del Lili entre enero de 2019 y junio de 2022. Resultados: un total de 360 pacientes cumplieron con los criterios de inclusión. El 66,9% de pacientes fueron mujeres, con una mediana de edad de 51 años (rango intercuartílico [RIC]: 39-61), el porcentaje de la prueba de aliento con 14C negativo fue de 84,4% y la mediana de tiempo entre la finalización del tratamiento y la realización de la prueba fue de 8 semanas (RIC: 5-12). Casi todos los pacientes recibieron 14 días de tratamiento. Conclusiones: en nuestro medio se presenta un porcentaje de erradicación aceptable, inclusive con la terapia triple estándar (la cual sigue siendo la más utilizada). Se requieren estudios de susceptibilidad antimicrobiana para lograr tratamientos basados en la epidemiología local.

Published
2024
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11. Changes in entire acute bronchiolitis seasons before, during, and after the COVID-19 pandemic in Spain

Author

Juan Manuel Rius-Peris, María del Carmen Vicent Castelló, Marta Pareja León, Sara Pons Morales, Ana Amat Madramany, Jorge Pantoja-Martínez, Raquel Gil Piquer, Nuria Roda Martínez, Alicia Coret Sinisterra, Francisca Castillo Ochando, Francisco Javier Caballero Mora, María Teresa Moya Díaz-Pintado, J.M. Rius-Peris, A.I. Maraña Pérez, A. Valiente Armero, L. Guardia Nieto, J. Torrecilla Cañas, E.M. Cueto Calvo, C. Marcilla Vázquez, M. Pareja León, N. Roda Martínez, N. Molini Menchón, E. Felipe Almira, A. Párraga Cifuentes, J.M. Sequí-Canet, J.M. Olmos García, A. Martínez Bayo, P. Escrivá Tomás, S. Povo Martín, J. Pantoja-Martínez, F.J. Caballero Mora, L. García Maset, A. Coret Sinisterra, F. Castillo Ochando, M.J. Garrido Sánchez, A. Edo Tena, L. Vázquez Álvarez, L. Rabasco Álvarez, M.T. Moya Díaz-Pintado, I. Cardete Pascual, S. García Candel, A. Amat Madramany, M. Moreno López, S. Pons Morales, M.C. Vicent Castelló, A.M. Rivera Figueiras, A. Herrero Galiana, J. González de Dios, A. Domingo Pla, and R. Gil Piquer

Subjects
Acute bronchiolitis, Infant, COVID-19, Epidemic season, RSV, Infectious and parasitic diseases, RC109-216, Public aspects of medicine, RA1-1270
Abstract

Summary: Background: Paediatric acute bronchiolitis normally occurs from October to April in the temperate northern hemisphere, peaking in January. Nonpharmacological measures to control the spread of COVID-19 resulted in a decrease in the number of cases of bronchiolitis during the 2020–21 season. The discontinuation of these measures created an uncertain scenario. Aim: To describe the epidemiological evolution of acute bronchiolitis seasons and the changes in the demographics of the affected population before, during, and after the implementation of nonpharmacological interventions for COVID-19 in Spain. Methods: This was a multicentre and descriptive study. A total of 6,334 infants aged up to 12 months who were diagnosed with acute bronchiolitis were recruited from sixteen Spanish hospitals. We collected data from participants from September 1st, 2021, through August 31st, 2023, as part of the ECEALHBA research project. The study periods were before (P1), during (P2), and after (P3) the COVID-19 pandemic. Findings: In P2 and after the discontinuation of nonpharmacological interventions, an unexpected increase in the number of acute bronchiolitis cases was observed from June–August 2021, resulting in an out-of-season peak. A subsequent peak was observed in November 2021, earlier than expected for the 2021-22 season. In the 2022-23 season, admissions followed a historical trend, with a greater number of cases than in the two previous seasons. Statistically significant differences in the length of stay (p

Published
2024
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13. A Bayesian multivariate spatial approach for illness-death survival models

Author

Llopis-Cardona, Fran, Armero, Carmen, and Sanfélix-Gimeno, Gabriel

Subjects
Statistics - Applications, Statistics - Methodology
Abstract

Illness-death models are a class of stochastic models inside the multi-state framework. In those models, individuals are allowed to move over time between different states related to illness and death. They are of special interest when working with non-terminal diseases, as they not only consider the competing risk of death but also allow to study progression from illness to death. The intensity of each transition can be modelled including both fixed and random effects of covariates. In particular, spatially structured random effects or their multivariate versions can be used to assess spatial differences between regions and among transitions. We propose a Bayesian methodological framework based on an illness-death model with a multivariate Leroux prior for the random effects. We apply this model to a cohort study regarding progression after osteoporotic hip fracture in elderly patients. From this spatial illness-death model we assess the geographical variation in risks, cumulative incidences, and transition probabilities related to recurrent hip fracture and death. Bayesian inference is done via the integrated nested Laplace approximation (INLA)., Comment: 22 pages, 9 figures

Published
2022

14. Bayes factors for longitudinal model assessment via power posteriors

Author

Calvo, Gabriel, Armero, Carmen, Spezia, Luigi, and Pennino, Maria Grazia

Subjects
Statistics - Methodology
Abstract

Bayes factor, defined as the ratio of the marginal likelihood functions of two competing models, is the natural Bayesian procedure for model selection. Marginal likelihoods are usually computationally demanding and complex. This scenario is particularly cumbersome in linear mixed models (LMMs) because marginal likelihood functions involve integrals of large dimensions determined by the number of parameters and the number of random effects, which in turn increase with the number of individuals in the sample. The power posterior is an attractive proposal in the context of the Markov chain Monte Carlo algorithms that allows expressing marginal likelihoods as one-dimensional integrals over the unit range. This paper explores the use of power posteriors in LMMs and discusses their behaviour through two simulation studies and a real data set on European sardine landings in the Mediterranean Sea.

Published
2022

15. The contribution of historical processes to contemporary extinction risk in placental mammals

Author

Wilder, Aryn P, Supple, Megan A, Subramanian, Ayshwarya, Mudide, Anish, Swofford, Ross, Serres-Armero, Aitor, Steiner, Cynthia, Koepfli, Klaus-Peter, Genereux, Diane P, Karlsson, Elinor K, Lindblad-Toh, Kerstin, Marques-Bonet, Tomas, Munoz Fuentes, Violeta, Foley, Kathleen, Meyer, Wynn K, Ryder, Oliver A, Shapiro, Beth, Andrews, Gregory, Armstrong, Joel C, Bianchi, Matteo, Birren, Bruce W, Bredemeyer, Kevin R, Breit, Ana M, Christmas, Matthew J, Clawson, Hiram, Damas, Joana, Di Palma, Federica, Diekhans, Mark, Dong, Michael X, Eizirik, Eduardo, Fan, Kaili, Fanter, Cornelia, Foley, Nicole M, Forsberg-Nilsson, Karin, Garcia, Carlos J, Gatesy, John, Gazal, Steven, Goodman, Linda, Grimshaw, Jenna, Halsey, Michaela K, Harris, Andrew J, Hickey, Glenn, Hiller, Michael, Hindle, Allyson G, Hubley, Robert M, Hughes, Graham M, Johnson, Jeremy, Juan, David, Kaplow, Irene M, Keough, Kathleen C, Kirilenko, Bogdan, Korstian, Jennifer M, Kowalczyk, Amanda, Kozyrev, Sergey V, Lawler, Alyssa J, Lawless, Colleen, Lehmann, Thomas, Levesque, Danielle L, Lewin, Harris A, Li, Xue, Lind, Abigail, Mackay-Smith, Ava, Marinescu, Voichita D, Mason, Victor C, Meadows, Jennifer RS, Moore, Jill E, Moreira, Lucas R, Moreno-Santillan, Diana D, Morrill, Kathleen M, Muntané, Gerard, Murphy, William J, Navarro, Arcadi, Nweeia, Martin, Ortmann, Sylvia, Osmanski, Austin, Paten, Benedict, Paulat, Nicole S, Pfenning, Andreas R, Phan, BaDoi N, Pollard, Katherine S, Pratt, Henry E, Ray, David A, Reilly, Steven K, Rosen, Jeb R, Ruf, Irina, Ryan, Louise, Sabeti, Pardis C, Schäffer, Daniel E, Serres, Aitor, Smit, Arian FA, Springer, Mark, and Srinivasan, Chaitanya

Subjects
Biological Sciences, Evolutionary Biology, Genetics, Behavioral and Social Science, Human Genome, Basic Behavioral and Social Science, Life on Land, Animals, Female, Pregnancy, Eutheria, Extinction, Biological, Genetic Variation, Genome, Population Density, Risk, Zoonomia Consortium‡, General Science & Technology
Abstract

Species persistence can be influenced by the amount, type, and distribution of diversity across the genome, suggesting a potential relationship between historical demography and resilience. In this study, we surveyed genetic variation across single genomes of 240 mammals that compose the Zoonomia alignment to evaluate how historical effective population size (Ne) affects heterozygosity and deleterious genetic load and how these factors may contribute to extinction risk. We find that species with smaller historical Ne carry a proportionally larger burden of deleterious alleles owing to long-term accumulation and fixation of genetic load and have a higher risk of extinction. This suggests that historical demography can inform contemporary resilience. Models that included genomic data were predictive of species' conservation status, suggesting that, in the absence of adequate census or ecological data, genomic information may provide an initial risk assessment.

Published
2023

16. A constitutive interferon-high immunophenotype defines response to immunotherapy in colorectal cancer

Author

Acha-Sagredo, Amelia, Andrei, Pietro, Clayton, Kalum, Taggart, Emma, Antoniotti, Carlotta, Woodman, Chloé A., Afrache, Hassnae, Fourny, Constance, Armero, Maria, Moinudeen, Hafsa Kaja, Green, Mary, Bhardwaj, Nisha, Mikolajczak, Anna, Rodriguez-Lopez, Maria, Crawford, Marg, Connick, Emma, Lim, Steven, Hobson, Philip, Linares, Josep, Ignatova, Ekaterina, Pelka, Diana, Smyth, Elizabeth C., Diamantis, Nikolaos, Sosnowska, Dominika, Carullo, Martina, Ciraci, Paolo, Bergamo, Francesca, Intini, Rossana, Nye, Emma, Barral, Patricia, Mishto, Michele, Arnold, James N., Lonardi, Sara, Cremolini, Chiara, Fontana, Elisa, Rodriguez-Justo, Manuel, and Ciccarelli, Francesca D.

Published
2025
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17. Improving radiation dose estimation using the gamma-H2AX biomarker

Author

Młynarczyk, Dorota, Puig, Pedro, Armero, Carmen, Gómez-Rubio, Virgilio, Barquinero, Joan F., and Pujol-Canadell, Mònica

Subjects
Statistics - Applications
Abstract

To predict the health effects of accidental or therapeutic radiation exposure, one must estimate the radiation dose that person received. A well-known ionising radiation biomarker, phosphorylated gamma-H2AX protein, is used to evaluate cell damage and is thus suitable for the dose estimation process. In this paper, we present new Bayesian methods that, in contrast to approaches where estimation is carried out at predetermined post-irradiation times, allow for uncertainty regarding the time since radiation exposure and, as a result, produce more precise results. We also use the Laplace approximation method, which drastically cuts down on the time needed to get results. Real data are used to illustrate the methods, and analyses indicate that the models might be a practical choice for the gamma-H2AX biomarker dose estimation process.

Published
2022

19. Abstract 4141333: Predictors of venous thromboembolism in hospitalized patients with COVID-19

Author

Scimeca, Giovanni, Krishnathasan, Darsiya, Rashedi, Sina, Sato, Alyssa, Lan, Zhou, Hamade, Nada, Bejjani, Antoine, Khairani, Candrika, Davies, Julia, Porio, Nicole, Assi, Ali, Armero, Andre, Tristani, Anthony, Ortiz-Rios, Marcos, Nauffal, Victor, Almarzooq, Zaid, Wei, Eric, Zuluaga-Sanchez, Valeria, Zarghami, Mehrdad, Achanta, Aditya, Jesudasen, Sirus, Tiu, Bruce, Merli, Geno, Fanikos, John, Leiva, Orly, Sharma, Aditya, Rizzo, Samantha, Pfeferman, Mariana, Morrison, Ruth, Vishnevsky, Alec, Hsia, Judith, Nehler, Mark, Welker, James, Bonaca, Marc, Carroll, Brett, Goldhaber, Samuel, Campia, Umberto, Bikdeli, Behnood, and Piazza, Gregory

Published
2024
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21. Polygenic inheritance and its interplay with smoking history in predicting lung cancer diagnosis: a French-Canadian case-control cohortResearch in context

Author

Véronique Boumtje, Hasanga D. Manikpurage, Zhonglin Li, Nathalie Gaudreault, Victoria Saavedra Armero, Dominique K. Boudreau, Sébastien Renaut, Cyndi Henry, Christine Racine, Aida Eslami, Stéphanie Bougeard, Evelyne Vigneau, Mathieu Morissette, Benoit J. Arsenault, Catherine Labbé, Anne-Sophie Laliberté, Simon Martel, François Maltais, Christian Couture, Patrice Desmeules, Patrick Mathieu, Sébastien Thériault, Philippe Joubert, and Yohan Bossé

Subjects
Lung cancer, Polygenic risk score, Genetic risk, Smoking, GWAS, Medicine, Medicine (General), R5-920
Abstract

Summary: Background: The most near-term clinical application of genome-wide association studies in lung cancer is a polygenic risk score (PRS). Methods: A case-control dataset was generated consisting of 4002 lung cancer cases from the LORD project and 20,010 ethnically matched controls from CARTaGENE. A genome-wide PRS including >1.1 million genetic variants was derived and validated in UK Biobank (n = 5419 lung cancer cases). The predictive ability and diagnostic discrimination performance of the PRS was tested in LORD/CARTaGENE and benchmarked against previous PRSs from the literature. Stratified analyses were performed by smoking status and genetic risk groups defined as low (80th percentile) PRS. Findings: The phenotypic variance explained and the effect size of the genome-wide PRS numerically outperformed previous PRSs. Individuals with high genetic risk had a 2-fold odds of lung cancer compared to low genetic risk. The PRS was an independent predictor of lung cancer beyond conventional clinical risk factors, but its diagnostic discrimination performance was incremental in an integrated risk model. Smoking increased the odds of lung cancer by 7.7-fold in low genetic risk and by 11.3-fold in high genetic risk. Smoking with high genetic risk was associated with a 17-fold increase in the odds of lung cancer compared to individuals who never smoked and with low genetic risk. Interpretation: Individuals at low genetic risk are not protected against the smoking-related risk of lung cancer. The joint multiplicative effect of PRS and smoking increases the odds of lung cancer by nearly 20-fold. Funding: This work was supported by the CQDM and the IUCPQ Foundation owing to a generous donation from Mr. Normand Lord.

Published
2024
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22. The Effect of After-School Extracurricular Robotic Classes on Elementary Students' Computational Thinking

Author

Merino-Armero, José Miguel, González-Calero, José Antonio, and Cózar-Gutiérrez, Ramón

Abstract

In modern society technology is widely used and, with the digitization of many services, this is an upward trend. Therefore, computational thinking (CT) is an increasingly important concept; an aspect that is being reflected on educational policies and the extracurricular offer of different countries. This study aims to look at the efficacy of private after-school extracurricular robotics activities, controlling fluid intelligence (Gf), a determining aspect in solving novel problems. A sample of 112 fifth-grade Spanish students was chosen, who completed two tests, the computational thinking test (CTt) (Román-González, 2016) and the KBIT fluid intelligence subtest (Kaufman, 1990). The results showed a great influence of Gf on the prediction of CT and significant differences between the students that had not attended after-school extracurricular classes and those that had attended for two or more years. Thus, this study substantiates the effectiveness of private extracurricular classes in promoting CT in the long term. Given the importance of CT nowadays, legislators should consider to include CT in compulsory education because private extracurricular classes could promote inequity.

Published
2023
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23. Nanoparticles Stokes radius assessment through permeability coefficient determination within a new stratified epithelium on-chip model

Author

E. Fernandez-Carro, R. Salomon-Cambero, L. Armero, H. A. Castro-Abril, J. Ayensa-Jiménez, Miguel A. Martínez, I. Ochoa, C. Alcaine, I. García, and J. Ciriza

Subjects
Skin on chip, microfluidic devices, permeability, stokes radius, nanoparticles, Biotechnology, TP248.13-248.65, Medical technology, R855-855.5
Abstract

AbstractTissue barrier permeability plays a crucial role in determining the selective transport of substances across epithelial tissues, including drugs, cosmetic substances, and chemicals. The ability of these substances to cross through tissue barriers affects their absorption into the bloodstream and ultimately their effectiveness. Therefore, the determination of their permeability on these type of tissue barriers represents a useful tool for pharmaceutical and cosmetic industries as well as for toxicological studies.In this regard, microfluidic devices and organ-on-chip technologies are becoming more important to generate reliable data. We have designed and performed an alternative new stratified epithelia-on-chip model that allows to correlate the Stokes radius and the diffusion of molecules and/or nanoformulations through the in vitro generated barrier and establish a system suitable for the analysis of diffusion through stratified epithelium. Thus, extrapolating from experimental data we can predict the Stokes radius for unknown fluorescent labelled particles within a molecular size range, such as gold nanoparticles.

Published
2023
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26. Embolization of percutaneous left atrial appendage closure devices: Timing, management and clinical outcomes

Author

Eppinger, Sophie, Piayda, Kerstin, Galea, Roberto, Sandri, Marcus, Maarse, Moniek, Güner, Ahmet, Karabay, Can Y., Pershad, Ashish, Ding, Wern Y., Aminian, Adel, Akin, Ibrahim, Davtyan, Karapet V., Chugunov, Ivan A., Marijon, Eloi, Rosseel, Liesbeth, Schmidt, Thomas Robert, Amabile, Nicolas, Korsholm, Kasper, Lund, Juha, Guerios, Enio, Amat-Santos, Ignacio J., Boccuzzi, Giacomo, Ellis, Christopher R., Sabbag, Avi, Ebelt, Henning, Clapp, Brian, Assa, Hana Vaknin, Levi, Amos, Ledwoch, Jakob, Lehmann, Sonja, Lee, Oh-Hyun, Mark, George, Schell, Wendy, della Rocca, Domenico G., Natale, Andrea, de Backer, Ole, Kefer, Joelle, Esteban, Pablo P., Abelson, Mark, Ram, Pradhum, Moceri, Pamela, Galache Osuna, Jose G., Alvarez, Xavier Millán, Cruz-Gonzalez, Ignacio, de Potter, Tom, Ghassan, Moubarak, Osadchiy, Andrey, Chen, Weita, Goyal, Sandeep K., Giannini, Francesco, Rivero-Ayerza, Máximo, Afzal, Shazia, Jung, Christian, Skurk, Carsten, Langel, Martin, Spence, Mark, Merkulov, Evgeny, Lempereur, Mathieu, Shin, Seung Y., Mesnier, Jules, McKinney, Heather L., Schuler, Brian T., Armero, Sebastien, Gheorghe, Livia, Ancona, Marco B.M., Santos, Lino, Mansourati, Jacques, Nombela-Franco, Luis, Nappi, Francesco, Kühne, Michael, Gaspardone, Achille, van der Pals, Jesper, Montorfano, Matteo, Fernández-Armenta, Juan, Harvey, James E., Rodés-Cabau, Josep, Klein, Norbert, Sabir, Sajjad A., Kim, Jung-Sun, Cook, Stephane, Kornowski, Ran, Saraste, Antti, Nielsen-Kudsk, Jens E., Gupta, Dhiraj, Boersma, Lucas, Räber, Lorenz, Sievert, Kolja, Sievert, Horst, and Bertog, Stefan

Published
2024
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27. Bayesian hierarchical nonlinear modelling of intra-abdominal volume during pneumoperitoneum for laparoscopic surgery

Author

Calvo, Gabriel, Armero, Carmen, Gómez-Rubio, Virgilio, and Mazzinari, Guido

Subjects
Statistics - Applications, 62P10, 62F25
Abstract

Laparoscopy is an operation carried out in the abdomen or pelvis through small incisions with external visual control by a camera. This technique needs the abdomen to be insufflated with carbon dioxide to obtain a working space for surgical instruments' manipulation. Identifying the critical point at which insufflation should be limited is crucial to maximizing surgical working space and minimizing injurious effects. Bayesian nonlinear growth mixed-effects models are applied to data coming from a repeated measures design. This study allows to assess the relationship between the insufflation pressure and the intra--abdominal volume.

Published
2021
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28. Reflection on modern methods: competing risks versus multi-state models

Author

Llopis-Cardona, Fran, Armero, Carmen, and Sanfélix-Gimeno, Gabriel

Subjects
Statistics - Applications
Abstract

Survival competing risks models are very useful for studying the incidence of diseases whose occurrence competes with other possible diseases or health conditions. These models perform properly when working with terminal events, such as death, that imply the conclusion of the corresponding study. But they do not allow the treatment of scenarios with non-terminal competing events that may occur sequentially. Multi-state models are complex survival models. They focus on pathways defined by the temporal and sequential occurrence of numerous events of interest and thus they are suitable for connecting competing non-terminal events as well as to manage other survival scenarios with higher complexity. We discuss competing risks within the framework of multi-state models and clarify the usefulness of both models for analysing epidemiological data. We highlight the power of multi-state models through a real-world study of recurrent hip fracture from Bayesian inferential methodology., Comment: 14 pages, 5 figures

Published
2021

29. Low absolute risk of thrombotic and cardiovascular events in outpatient pregnant women with COVID-19

Author

Bikdeli, Behnood, Krishnathasan, Darsiya, Khairani, Candrika D., Bejjani, Antoine, Davies, Julia, Porio, Nicole, Tristani, Anthony, Armero, Andre, Assi, Ali A., Nauffal, Victor, Campia, Umberto, Almarzooq, Zaid, Wei, Eric, Ortiz-Rios, Marcos D., Zuluaga-Sánchez, Valeria, Achanta, Aditya, Jesudasen, Sirus J., Tiu, Bruce, Merli, Geno J., Leiva, Orly, Fanikos, John, Grandone, Elvira, Sharma, Aditya, Rizzo, Samantha, Pfeferman, Mariana B., Morrison, Ruth B., Vishnevsky, Alec, Hsia, Judith, Nehler, Mark R., Welker, James, Bonaca, Marc P., Carroll, Brett, Goldhaber, Samuel Z., Lan, Zhou, and Piazza, Gregory

Published
2024
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30. Bayesian analysis of population health data

Author

Młynarczyk, Dorota, Armero, Carmen, Gómez-Rubio, Virgilio, and Puig, Pedro

Subjects
Statistics - Applications
Abstract

The analysis of population-wide datasets can provide insight on the health status of large populations so that public health officials can make data-driven decisions. The analysis of such datasets often requires highly parameterized models with different types of fixed and randoms effects to account for risk factors, spatial and temporal variations, multilevel effects and other sources on uncertainty. To illustrate the potential of Bayesian hierarchical models, a dataset of about 500 000 inhabitants released by the Polish National Health Fund containing information about ischemic stroke incidence for a 2-year period is analyzed using different types of models. Spatial logistic regression and survival models are considered for analyzing the individual probabilities of stroke and the times to the occurrence of an ischemic stroke event. Demographic and socioeconomic variables as well as drug prescription information are available at an individual level. Spatial variation is considered by means of region-level random effects.

Published
2021

31. Bayesian classification for dating archaeological sites via projectile points

Author

Armero, Carmen, García-Donato, Gonzalo, Jiménez-Puerto, Joaquín, Pardo-Gordó, Salvador, and Bernabeu, Joan

Subjects
Statistics - Applications
Abstract

Dating is a key element for archaeologists. We propose a Bayesian approach to provide chronology to sites that have neither radiocarbon dating nor clear stratigraphy and whose only information comes from lithic arrowheads. This classifier is based on the Dirichlet-multinomial inferential process and posterior predictive distributions. The procedure is applied to predict the period of a set of undated sites located in the east of the Iberian Peninsula during the IVth and IIIrd millennium cal. BC., Comment: 12 pages, 5 figures, 3 tables

Published
2020

32. Bayesian shared-parameter models for analysing sardine fishing in the Mediterranean Sea

Author

Calvo, Gabriel, Armero, Carmen, Pennino, Maria Grazia, and Spezia, Luigi

Subjects
Statistics - Applications
Abstract

European sardine is experiencing an overfishing around the world. The dynamics of the industrial and artisanal fishing in the Mediterranean Sea from 1970 to 2014 by country was assessed by means of Bayesian joint longitudinal modelling that uses the random effects to generate an association structure between both longitudinal measures. Model selection was based on Bayes factors approximated through the harmonic mean.

Published
2020

33. Bayesian joint models for longitudinal and survival data

Author

Armero, Carmen

Subjects
Statistics - Methodology
Abstract

This paper takes a quick look at Bayesian joint models (BJM) for longitudinal and survival data. A general formulation for BJM is examined in terms of the sampling distribution of the longitudinal and survival processes, the conditional distribution of the random effects and the prior distribution. Next a basic BJM defined in terms of a mixed linear model and a Cox survival regression models is discussed and some extensions and other Bayesian topics are briefly outlined.

Published
2020

34. Bayesian survival analysis with BUGS

Author

Alvares, Danilo, Lázaro, Elena, Gómez-Rubio, Virgilio, and Armero, Carmen

Subjects
Statistics - Applications
Abstract

Survival analysis is one of the most important fields of statistics in medicine and the biological sciences. In addition, the computational advances in the last decades have favoured the use of Bayesian methods in this context, providing a flexible and powerful alternative to the traditional frequentist approach. The objective of this paper is to summarise some of the most popular Bayesian survival models, such as accelerated failure time, proportional hazards, mixture cure, competing risks, frailty, and joint models of longitudinal and survival data. Moreover, an implementation of each presented model is provided using a BUGS syntax that can be run with JAGS from the R programming language. Reference to other Bayesian R-packages are also discussed.

Published
2020

35. Bayesian longitudinal models for exploring European sardine fishing in the Mediterranean Sea

Author

Calvo, Gabriel, Armero, Carmen, Pennino, Maria Grazia, and Spezia, Luigi

Subjects
Statistics - Applications
Abstract

In the Mediterranean Sea, catches are dominated by small pelagic fish, representing nearly the 49\% of the total harvest. Among them, the European sardine (Sardina pilchardus) is one of the most commercially important species showing high over-exploitation rates in recent last years. In this study we analysed the European sardine landings in the Mediterranean Sea from 1970 to 2014. We made use of Bayesian longitudinal linear mixed models in order to assess differences in the temporal evolution of fishing between and within countries. Furthermore, we modelled the subsequent joint evolution of artisanal and industrial fisheries. Overall results confirmed that Mediterranean fishery time series were highly diverse along their dynamics and this heterogeneity was persistent throughout the time. In addition, results highlighted a positive relationship between the two types of fishing., Comment: 16 pages, 7 figures

Published
2020

38. Y chromosome sequence and epigenomic reconstruction across human populations

Author

Paula Esteller-Cucala, Marc Palmada-Flores, Lukas F. K. Kuderna, Claudia Fontsere, Aitor Serres-Armero, Marc Dabad, María Torralvo, Armida Faella, Luis Ferrández-Peral, Laia Llovera, Oscar Fornas, Eva Julià, Erika Ramírez, Irene González, Jochen Hecht, Esther Lizano, David Juan, and Tomàs Marquès-Bonet

Subjects
Biology (General), QH301-705.5
Abstract

Abstract Recent advances in long-read sequencing technologies have allowed the generation and curation of more complete genome assemblies, enabling the analysis of traditionally neglected chromosomes, such as the human Y chromosome (chrY). Native DNA was sequenced on a MinION Oxford Nanopore Technologies sequencing device to generate genome assemblies for seven major chrY human haplogroups. We analyzed and compared the chrY enrichment of sequencing data obtained using two different selective sequencing approaches: adaptive sampling and flow cytometry chromosome sorting. We show that adaptive sampling can produce data to create assemblies comparable to chromosome sorting while being a less expensive and time-consuming technique. We also assessed haplogroup-specific structural variants, which would be otherwise difficult to study using short-read sequencing data only. Finally, we took advantage of this technology to detect and profile epigenetic modifications among the considered haplogroups. Altogether, we provide a framework to study complex genomic regions with a simple, fast, and affordable methodology that could be applied to larger population genomics datasets.

Published
2023
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39. Paraoxonase I Activity and Its Relationship with Nutrition in Amyotrophic Lateral Sclerosis

Author

Belén Proaño, María Benlloch, Sandra Sancho-Castillo, Jesús Privado, Guillermo Bargues-Navarro, Claudia Emmanuela Sanchis-Sanchis, Palmira Martínez Bolós, Ana Belén Carriquí-Suárez, Laura Cubero-Plazas, Jose Luis Platero Armero, Dolores Escriva, Jose Joaquín Ceron, Asta Tvarijonaviciute, and Jose Enrique de la Rubia Ortí

Subjects
paraoxonase-1, nutrition, pulmonary function, high density lipoprotein, ALS, Therapeutics. Pharmacology, RM1-950
Abstract

Background: Amyotrophic lateral sclerosis (ALS) is characterized by progressive motor neuron degeneration, with oxidative stress playing a key role. Paraoxonase 1 (PON1) is an antioxidant enzyme that may influence ALS progression. This study aimed to establish a predictive model for the influence of PON1 activity on functionality in ALS patients and explore its relationship with nutrition. Methods: In this observational cross-sectional study, 70 ALS patients underwent assessments of PON1 activity, lipid profile, functional capacity, respiratory function, and heart rate variability. A structural equation model was developed to determine the relationships between variables. Nutritional intake was analyzed in 65 patients. Results: The predictive model showed that PON1 activity and LDL levels positively influenced functionality, both directly and indirectly through respiratory capacity. Heart rate variability moderately predicted functionality independently. HDL levels were not significantly associated with functionality. Weak to moderate correlations were found between PON1 activity and intake of certain nutrients, with positive associations for monounsaturated fats and vitamin D, and negative associations for carbohydrates, proteins, and some micronutrients. Conclusions: PON1 activity appears to play an important role in ALS patient functionality, both directly and through effects on respiratory capacity. However, its relationship with nutritional intake was not strongly evident in this sample population.

Published
2024
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40. Vegetación utilizada por aves dentro del Campus de la Universidad de El Salvador, El Salvador

Author

Rebeca Marleni Figueroa Eguizábal, Dora Alicia Armero Durán, and Fabiola Mayandi Guerra Mina

Subjects
Especies vegetales, aves urbanas, campus universitario, abundancia, monitoreo, Social Sciences
Abstract

El objetivo del estudio fue identificar las especies vegetales utilizadas por la avifauna dentro del campus de la Universidad de El Salvador durante los meses de abril, mayo y junio de 2022 mediante recorridos quincenales. Se empleó la metodología de búsqueda intensiva para identificar a las aves por medio de la inspección de sus características físicas y de cantos.Además se llevó el registro de las actividades realizadas. Un total de 47 especies de plantas, agrupadas en 43 géneros, 25 familias y 17 órdenes, fueron registradas siendo utilizadas por las aves durante los monitoreos. Las especies vegetales utilizadas de forma más frecuente por las aves fueron mango (Mangifera indica) y casuarina (Casuarina equisetifolia). Del total de la vegetación usada por la avifauna urbana dentro del campus universitario, el 49 % fue utilizada para alimentación, 62 % se empleó para percha y 15 % como sitio de anidación. En relación a las aves se reportaron 48 especies dentro del campus de la Universidad de El Salvador, agrupadas en 43 géneros y 21 familias. Las tres especies más dominantes: zorzal pardo (Turdus grayi), zanate mexicano (Quiscalus mexicanus) y paloma aliblanca (Zenaida asiatica). Este estudio destaca la importancia que tiene la vegetación presente dentro de la Universidad de El Salvador como sitio de descanso para las poblaciones de aves residentes y migratorias visitantes.

Published
2023
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41. Patterns of oral anticoagulant use and outcomes in Asian patients with atrial fibrillation: a post-hoc analysis from the GLORIA-AF Registry

Author

Abban, Dzifa Wosornu, Abdul, Nasser, Abud, Atilio Marcelo, Adams, Fran, Addala, Srinivas, Adragão, Pedro, Ageno, Walter, Aggarwal, Rajesh, Agosti, Sergio, Agostoni, Piergiuseppe, Aguilar, Francisco, Linares, Julio Aguilar, Aguinaga, Luis, Ahmed, Jameel, Aiello, Allessandro, Ainsworth, Paul, Aiub, Jorge Roberto, Al-Dallow, Raed, Alderson, Lisa, Aldrete Velasco, Jorge Antonio, Alexopoulos, Dimitrios, Manterola, Fernando Alfonso, Aliyar, Pareed, Alonso, David, Alves da Costa, Fernando Augusto, Amado, José, Amara, Walid, Amelot, Mathieu, Amjadi, Nima, Ammirati, Fabrizio, Andrade, Marianna, Andrawis, Nabil, Annoni, Giorgio, Ansalone, Gerardo, Ariani, M.Kevin, Arias, Juan Carlos, Armero, Sébastien, Arora, Chander, Aslam, Muhammad Shakil, Asselman, M., Audouin, Philippe, Augenbraun, Charles, Aydin, S., Ayryanova, Ivaneta, Aziz, Emad, Backes, Luciano Marcelo, Badings, E., Bagni, Ermentina, Baker, Seth H., Bala, Richard, Baldi, Antonio, Bando, Shigenobu, Banerjee, Subhash, Bank, Alan, Esquivias, Gonzalo Barón, Barr, Craig, Bartlett, Maria, Kes, Vanja Basic, Baula, Giovanni, Behrens, Steffen, Bell, Alan, Benedetti, Raffaella, Mazuecos, Juan Benezet, Benhalima, Bouziane, Bergler-Klein, Jutta, Berneau, Jean-Baptiste, Bernstein, Richard A., Berrospi, Percy, Berti, Sergio, Berz, Andrea, Best, Elizabeth, Bettencourt, Paulo, Betzu, Robert, Bhagwat, Ravi, Bhatta, Luna, Biscione, Francesco, Bisignani, Giovanni, Black, Toby, Bloch, Michael J., Bloom, Stephen, Blumberg, Edwin, Bo, Mario, Bøhmer, Ellen, Bollmann, Andreas, Bongiorni, Maria Grazia, Boriani, Giuseppe, Boswijk, D.J., Bott, Jochen, Bottacchi, Edo, Kalan, Marica Bracic, Bradman, Drew, Brautigam, Donald, Breton, Nicolas, Brouwers, P.J.A.M., Browne, Kevin, Cortada, Jordi Bruguera, Bruni, A., Brunschwig, Claude, Buathier, Hervé, Buhl, Aurélie, Bullinga, John, Cabrera, Jose Walter, Caccavo, Alberto, Cai, Shanglang, Caine, Sarah, Calò, Leonardo, Calvi, Valeria, Sánchez, Mauricio Camarillo, Candeias, Rui, Capuano, Vincenzo, Capucci, Alessandro, Caputo, Ronald, Rizo, Tatiana Cárdenas, Cardona, Francisco, Carlos da Costa Darrieux, Francisco, Duarte Vera, Yan Carlos, Carolei, Antonio, Carreño, Susana, Carvalho, Paula, Cary, Susanna, Casu, Gavino, Cavallini, Claudio, Cayla, Guillaume, Celentano, Aldo, Cha, Tae-Joon, Cha, Kwang Soo, Chae, Jei Keon, Chalamidas, Kathrine, Challappa, Krishnan, Chand, Sunil Prakash, Chandrashekar, Harinath, Chartier, Ludovic, Chatterjee, Kausik, Chavez Ayala, Carlos Antero, Cheema, Aamir, Cheema, Amjad, Chen, Lin, Chen, Shih-Ann, Chen, Jyh Hong, Chiang, Fu-Tien, Chiarella, Francesco, Chih-Chan, Lin, Cho, Yong Keun, Choi, Jong-Il, Choi, Dong Ju, Chouinard, Guy, Hoi-Fan Chow, Danny, Chrysos, Dimitrios, Chumakova, Galina, José Roberto, Eduardo Julián, Valenzuela, Chuquiure, Nica, Nicoleta Cindea, Cislowski, David J., Clay, Anthony, Clifford, Piers, Cohen, Andrew, Cohen, Michael, Cohen, Serge, Colivicchi, Furio, Collins, Ronan, Colonna, Paolo, Compton, Steve, Connolly, Derek, Conti, Alberto, Buenostro, Gabriel Contreras, Coodley, Gregg, Cooper, Martin, Coronel, Julian, Corso, Giovanni, Sales, Juan Cosín, Cottin, Yves, Covalesky, John, Cracan, Aurel, Crea, Filippo, Crean, Peter, Crenshaw, James, Cullen, Tina, Darius, Harald, Dary, Patrick, Dascotte, Olivier, Dauber, Ira, Davalos, Vicente, Davies, Ruth, Davis, Gershan, Davy, Jean-Marc, Dayer, Mark, De Biasio, Marzia, De Bonis, Silvana, De Caterina, Raffaele, De Franceschi, Teresiano, de Groot, J.R., De Horta, José, De La Briolle, Axel, Topete, Gilberto de la Pena, Vicenzo de Paola, Angelo Amato, de Souza, Weimar, de Veer, A., De Wolf, Luc, Decoulx, Eric, Deepak, Sasalu, Defaye, Pascal, Del-Carpio Munoz, Freddy, Brkljacic, Diana Delic, Deumite, N. Joseph, Di Legge, Silvia, Diemberger, Igor, Dietz, Denise, Dionísio, Pedro, Dong, Qiang, Rossi dos Santos, Fabio, Dotcheva, Elena, Doukky, Rami, D'Souza, Anthony, Dubrey, Simon, Ducrocq, Xavier, Dupljakov, Dmitry, Duque, Mauricio, Dutta, Dipankar, Duvilla, Nathalie, Duygun, A., Dziewas, Rainer, Eaton, Charles B., Eaves, William, Ebels-Tuinbeek; Clifford Ehrlich, L.A., Eichinger-Hasenauer, Sabine, Eisenberg, Steven J., El Jabali, Adnan, El Shahawy, Mahfouz, Hernandes, Mauro Esteves, Izal, Ana Etxeberria, Evonich, Rudolph, III, Evseeva, Oksana, Ezhov, Andrey, Fahmy, Raed, Fang, Quan, Farsad, Ramin, Fauchier, Laurent, Favale, Stefano, Fayard, Maxime, Fedele, Jose Luis, Fedele, Francesco, Fedorishina, Olga, Fera, Steven R., Gomes Ferreira, Luis Gustavo, Ferreira, Jorge, Ferri, Claudio, Ferrier, Anna, Ferro, Hugo, Finsen, Alexandra, First, Brian, Fischer, Stuart, Fonseca, Catarina, Almeida, Luísa Fonseca, Forman, Steven, Frandsen, Brad, French, William, Friedman, Keith, Friese, Athena, Fruntelata, Ana Gabriela, Fujii, Shigeru, Fumagalli, Stefano, Fundamenski, Marta, Furukawa, Yutaka, Gabelmann, Matthias, Gabra, Nashwa, Gadsbøll, Niels, Galinier, Michel, Gammelgaard, Anders, Ganeshkumar, Priya, Gans, Christopher, Quintana, Antonio Garcia, Gartenlaub, Olivier, Gaspardone, Achille, Genz, Conrad, Georger, Frédéric, Georges, Jean-Louis, Georgeson, Steven, Giedrimas, Evaldas, Gierba, Mariusz, Ortega, Ignacio Gil, Gillespie, Eve, Giniger, Alberto, Giudici, Michael C., Gkotsis, Alexandros, Glotzer, Taya V., Gmehling, Joachim, Gniot, Jacek, Goethals, Peter, Goldbarg, Seth, Goldberg, Ronald, Goldmann, Britta, Golitsyn, Sergey, Gómez, Silvia, Mesa, Juan Gomez, Gonzalez, Vicente Bertomeu, Gonzalez Hermosillo, Jesus Antonio, González López, Víctor Manuel, Gorka, Hervé, Gornick, Charles, Gorog, Diana, Gottipaty, Venkat, Goube, Pascal, Goudevenos, Ioannis, Graham, Brett, Greer, G. Stephen, Gremmler, Uwe, Grena, Paul G., Grond, Martin, Gronda, Edoardo, Grönefeld, Gerian, Gu, Xiang, Torres Torres, Ivett Guadalupe, Guardigli, Gabriele, Guevara, Carolina, Guignier, Alexandre, Gulizia, Michele, Gumbley, Michael, Günther, Albrecht, Ha, Andrew, Hahalis, Georgios, Hakas, Joseph, Hall, Christian, Han, Bing, Han, Seongwook, Hargrove, Joe, Hargroves, David, Harris, Kenneth B., Haruna, Tetsuya, Hayek, Emil, Healey, Jeff, Hearne, Steven, Heffernan, Michael, Heggelund, Geir, Heijmeriks, J.A., Hemels, Maarten, Hendriks, I., Henein, Sam, Her, Sung-Ho, Hermany, Paul, Hernández Del Río, Jorge Eduardo, Higashino, Yorihiko, Hill, Michael, Hisadome, Tetsuo, Hishida, Eiji, Hoffer, Etienne, Hoghton, Matthew, Hong, Kui, Hong, Suk keun, Horbach, Stevie, Horiuchi, Masataka, Hou, Yinglong, Hsing, Jeff, Huang, Chi-Hung, Huckins, David, Hughes, kathy, Huizinga, A., Hulsman, E.L., Hung, Kuo-Chun, Hwang, Gyo-Seung, Ikpoh, Margaret, Imberti, Davide, Ince, Hüseyin, Indolfi, Ciro, Inoue, Shujiro, Irles, Didier, Iseki, Harukazu, Israel, C. Noah, Iteld, Bruce, Iyer, Venkat, Jackson-Voyzey, Ewart, Jaffrani, Naseem, Jäger, Frank, James, Martin, Jang, Sung-Won, Jaramillo, Nicolas, Jarmukli, Nabil, Jeanfreau, Robert J., Jenkins, Ronald D., Sánchez, Carlos Jerjes, Jimenez, Javier, Jobe, Robert, Joen-Jakobsen, Tomas, Jones, Nicholas, Moura Jorge, Jose Carlos, Jouve, Bernard, Jung, Byung Chun, Jung, Kyung Tae, Jung, Werner, Kachkovskiy, Mikhail, Kafkala, Krystallenia, Kalinina, Larisa, Kallmünzer, Bernd, Kamali, Farzan, Kamo, Takehiro, Kampus, Priit, Kashou, Hisham, Kastrup, Andreas, Katsivas, Apostolos, Kaufman, Elizabeth, Kawai, Kazuya, Kawajiri, Kenji, Kazmierski, John F., Keeling, P., Kerr Saraiva, José Francisco, Ketova, Galina, Khaira, Ajit Singh, Khripun, Aleksey, Kim, Doo-Il, Kim, Young Hoon, Kim, Nam Ho, Kim, Dae Kyeong, Kim, Jeong Su, Kim, June Soo, Kim, Ki Seok, Kim, Jin bae, Kinova, Elena, Klein, Alexander, Kmetzo, James J., Kneller, G. Larsen, Knezevic, Aleksandar, Angela Koh, Su Mei, Koide, Shunichi, Kollias, Anastasios, Kooistra, J.A., Koons, Jay, Koschutnik, Martin, Kostis, William J., Kovacic, Dragan, Kowalczyk, Jacek, Koziolova, Natalya, Kraft, Peter, Kragten, Johannes A., Krantz, Mori, Krause, Lars, Krenning, B.J., Krikke, F., Kromhout, Z., Krysiak, Waldemar, Kumar, Priya, Kümler, Thomas, Kuniss, Malte, Kuo, Jen-Yuan, Küppers, Achim, Karla Kurrelmeyer, Kwak, Choong Hwan, Laboulle, Bénédicte, Labovitz, Arthur, Lai, Wen Ter, Lam, Andy, Lam, Yat Yin, Zanetti, Fernando Lanas, Landau, Charles, Landini, Giancarlo, Figueiredo, Estêvão Lanna, Larsen, Torben, Lavandier, Karine, LeBlanc, Jessica, Lee, Moon Hyoung, Lee, Chang-Hoon, Lehman, John, Leitão, Ana, Lellouche, Nicolas, Lelonek, Malgorzata, Lenarczyk, Radoslaw, Lenderink, T., González, Salvador León, Leong-Sit, Peter, Leschke, Matthias, Ley, Nicolas, Li, Zhanquan, Li, Xiaodong, Li, Weihua, Li, Xiaoming, Lichy, Christhoh, Lieber, Ira, Limon Rodriguez, Ramon Horacio, Lin, Hailong, Lip, Gregory Y.H., Liu, Feng, Liu, Hengliang, Esperon, Guillermo Llamas, Navarro, Nassip Llerena, Lo, Eric, Lokshyn, Sergiy, López, Amador, López-Sendón, José Luís, Lorga Filho, Adalberto Menezes, Lorraine, Richard S., Luengas, Carlos Alberto, Luke, Robert, Luo, Ming, Lupovitch, Steven, Lyrer, Philippe, Ma, Changsheng, Ma, Genshan, Madariaga, Irene, Maeno, Koji, Magnin, Dominique, Maid, Gustavo, Mainigi, Sumeet K., Makaritsis, Konstantinos, Malhotra, Rohit, Manning, Rickey, Manolis, Athanasios, Manrique Hurtado, Helard Andres, Mantas, Ioannis, Jattin, Fernando Manzur, Maqueda, Vicky, Marchionni, Niccolo, Ortuno, Francisco Marin, Santana, Antonio Martín, Martinez, Jorge, Maskova, Petra, Hernandez, Norberto Matadamas, Matsuda, Katsuhiro, Maurer, Tillmann, Mauro, Ciro, May, Erik, Mayer, Nolan, McClure, John, McCormack, Terry, McGarity, William, McIntyre, Hugh, McLaurin, Brent, Medina Palomino, Feliz Alvaro, Melandri, Francesco, Meno, Hiroshi, Menzies, Dhananjai, Mercader, Marco, Meyer, Christian, Meyer, Beat J., Miarka, Jacek, Mibach, Frank, Michalski, Dominik, Michel, Patrik, Chreih, Rami Mihail, Mikdadi, Ghiath, Mikus, Milan, Milicic, Davor, Militaru, Constantin, Minaie, Sedi, Minescu, Bogdan, Mintale, Iveta, Mirault, Tristan, Mirro, Michael J., Mistry, Dinesh, Miu, Nicoleta Violeta, Miyamoto, Naomasa, Moccetti, Tiziano, Mohammed, Akber, Nor, Azlisham Mohd, Mollerus, Michael, Molon, Giulio, Mondillo, Sergio, Moniz, Patrícia, Mont, Lluis, Montagud, Vicente, Montaña, Oscar, Monti, Cristina, Moretti, Luciano, Mori, Kiyoo, Moriarty, Andrew, Morka, Jacek, Moschini, Luigi, Moschos, Nikitas, Mügge, Andreas, Mulhearn, Thomas J., Muresan, Carmen, Muriago, Michela, Musial, Wlodzimierz, Musser, Carl W., Musumeci, Francesco, Nageh, Thuraia, Nakagawa, Hidemitsu, Nakamura, Yuichiro, Nakayama, Toru, Nam, Gi-Byoung, Nanna, Michele, Natarajan, Indira, Nayak, Hemal M., Naydenov, Stefan, Nazlić, Jurica, Cristian Nechita, Alexandru, Nechvatal, Libor, Negron, Sandra Adela, Neiman, James, Neuenschwander, Fernando Carvalho, Neves, David, Neykova, Anna, Miguel, Ricardo Nicolás, Nijmeh, George, Nizov, Alexey, Campos, Rodrigo Noronha, Nossan, Janko, Novikova, Tatiana, Nowalany-Kozielska, Ewa, Nsah, Emmanuel, Nunez Fragoso, Juan Carlos, Nurgalieva, Svetlana, Nuyens, Dieter, Nyvad, Ole, Odin de Los Rios Ibarra, Manuel, O'Donnell, Philip, O'Donnell, Martin, Oh, Seil, Oh, Yong Seog, Oh, Dongjin, O'Hara, Gilles, Oikonomou, Kostas, Olivares, Claudia, Oliver, Richard, Ruiz, Rafael Olvera, Olympios, Christoforos, omaszuk-Kazberuk, Anna, Asensi, Joaquín Osca, Jose, eena Padayattil, Padilla Padilla, Francisco Gerardo, Rios, Victoria Padilla, Pajes, Giuseppe, Pandey, Shekhar, Paparella, Gaetano, Paris, F., Park, Hyung Wook, Park, Jong Sung, Parthenakis, Fragkiskos, Passamonti, Enrico, Patel, Rajesh J., Patel, Jaydutt, Patel, Mehool, Patrick, Janice, Jimenez, Ricardo Pavón, Paz, Analía, Pengo, Vittorio, Pentz, William, Pérez, Beatriz, Pérez Ríos, Alma Minerva, Pérez-Cabezas, Alejandro, Perlman, Richard, Persic, Viktor, Perticone, Francesco, Peters, Terri K., Petkar, Sanjiv, Pezo, Luis Felipe, Pflücke, Christian, Pham, David N., Phillips, Roland T., Phlaum, Stephen, Pieters, Denis, Pineau, Julien, Pinter, Arnold, Pinto, Fausto, Pisters, R., Pivac, Nediljko, Pocanic, Darko, Podoleanu, Cristian, Politano, Alessandro, Poljakovic, Zdravka, Pollock, Stewart, Garcéa, Jose Polo, Poppert, Holger, Porcu, Maurizio, Reino, Antonio Pose, Prasad, Neeraj, Précoma, Dalton Bertolim, Prelle, Alessandro, Prodafikas, John, Protasov, Konstantin, Pye, Maurice, Qiu, Zhaohui, Quedillac, Jean-Michel, Raev, Dimitar, Raffo Grado, Carlos Antonio, Rahimi, Sidiqullah, Raisaro, Arturo, Rama, Bhola, Ramos, Ricardo, Ranieri, Maria, Raposo, Nuno, Rashba, Eric, Rauch-Kroehnert, Ursula, Reddy, Ramakota, Renda, Giulia, Reza, Shabbir, Ria, Luigi, Richter, Dimitrios, Rickli, Hans, Rieker, Werner, Vera, Tomas Ripolil, Ritt, Luiz Eduardo, Roberts, Douglas, Briones, Ignacio Rodriguez, Rodriguez Escudero, Aldo Edwin, Pascual, Carlos Rodríguez, Roman, Mark, Romeo, Francesco, Ronner, E., Roux, Jean-Francois, Rozkova, Nadezda, Rubacek, Miroslav, Rubalcava, Frank, Russo, Andrea M., Rutgers, Matthieu Pierre, Rybak, Karin, Said, Samir, Sakamoto, Tamotsu, Salacata, Abraham, Salem, Adrien, Bodes, Rafael Salguero, Saltzman, Marco A., Salvioni, Alessandro, Vallejo, Gregorio Sanchez, Fernández, Marcelo Sanmartín, Saporito, Wladmir Faustino, Sarikonda, Kesari, Sasaoka, Taishi, Sati, Hamdi, Savelieva, Irina, Scala, Pierre-Jean, Schellinger, Peter, Scherr, Carlos, Schmitz, Lisa, Schmitz, Karl-Heinz, Schmitz, Bettina, Schnabel, Teresa, Schnupp, Steffen, Schoeniger, Peter, Schön, Norbert, Schwimmbeck, Peter, Seamark, Clare, Searles, Greg, Seidl, Karl-Heinz, Seidman, Barry, Sek, Jaroslaw, Sekaran, Lakshmanan, Serrati, Carlo, Shah, Neerav, Shah, Vinay, Shah, Anil, Shah, Shujahat, Sharma, Vijay Kumar, Shaw, Louise, Sheikh, Khalid H., Shimizu, Naruhito, Shimomura, Hideki, Shin, Dong-Gu, Shin, Eun-Seok, Shite, Junya, Sibilio, Gerolamo, Silver, Frank, Sime, Iveta, Simmers, Tim A., Singh, Narendra, Siostrzonek, Peter, Smadja, Didier, Smith, David W., Snitman, Marcelo, Filho, Dario Sobral, Soda, Hassan, Sofley, Carl, Sokal, Adam, Oi Yan, Yannie Soo, Sotolongo, Rodolfo, Ferreira de Souza, Olga, Sparby, Jon Arne, Spinar, Jindrich, Sprigings, David, Spyropoulos, Alex C., Stakos, Dimitrios, Steinwender, Clemens, Stergiou, Georgios, Stiell, Ian, Stoddard, Marcus, Stoikov, Anastas, Streb, Witold, Styliadis, Ioannis, Su, Guohai, Su, Xi, Sudnik, Wanda, Sukles, Kai, Sun, Xiaofei, Swart, H., Szavits-Nossan, Janko, Taggeselle, Jens, Takagi, Yuichiro, Singh Takhar, Amrit Pal, Tamm, Angelika, Tanaka, Katsumi, Tanawuttiwat, Tanyanan, Tang, Sherman, Tang, Aylmer, Tarsi, Giovanni, Tassinari, Tiziana, Tayal, Ashis, Tayebjee, Muzahir, Berg, J.M. ten, Tesloianu, Dan, The, Salem H.K., Thomas, Dierk, Timsit, Serge, Tobaru, Tetsuya, Tomasik, Andrzej R., Torosoff, Mikhail, Touze, Emmanuel, Trendafilova, Elina, Tsai, W. Kevin, Tse, Hung Fat, Tsutsui, Hiroshi, Tu, Tian Ming, Tuininga, Ype, Turakhia, Minang, Turk, Samir, Turner, Wayne, Tveit, Arnljot, Tytus, Richard, Valadão, C., van Bergen, P.F.M.M., van de Borne, Philippe, van den Berg, B.J., van der Zwaan, C., Van Eck, M., Vanacker, Peter, Vasilev, Dimo, Vasilikos, Vasileios, Vasilyev, Maxim, Veerareddy, Srikar, Miño; Asok Venkataraman, Mario Vega, Verdecchia, Paolo, Versaci, Francesco, Vester, Ernst Günter, Vial, Hubert, Victory, Jason, Villamil, Alejandro, Vincent, Marc, Vlastaris, Anthony, Dahl, Jürgen vom, Vora, Kishor, Vranian, Robert B., Wakefield, Paul, Wang, Ningfu, Wang, Mingsheng, Wang, Xinhua, Wang, Feng, Wang, Tian, Warner, Alberta L., Watanabe, Kouki, Wei, Jeanne, Weimar, Christian, Weiner, Stanislav, Weinrich, Renate, Wen, Ming-Shien, Wiemer, Marcus, Wiggers, Preben, Wilke, Andreas, Williams, David, Williams, Marcus L., Witzenbichler, Bernhard, Wong, Brian, Lawrence Wong, Ka Sing, Wozakowska-Kaplon, Beata, Wu, Shulin, Wu, Richard C., Wunderlich, Silke, Wyatt, Nell, Wylie, John (Jack), Xu, Yong, Xu, Xiangdong, Yamanoue, Hiroki, Yamashita, Takeshi, Bryan Yan, Ping Yen, Yang, Tianlun, Yao, Jing, Yeh, Kuo-Ho, Yin, Wei Hsian, Yotov, Yoto, Zahn, Ralf, Zarich, Stuart, Zenin, Sergei, Zeuthen, Elisabeth Louise, Zhang, Huanyi, Zhang, Donghui, Zhang, Xingwei, Zhang, Ping, Zhang, Jun, Zhao, Shui Ping, Zhao, Yujie, Zhao, Zhichen, Zheng, Yang, Zhou, Jing, Zimmermann, Sergio, Zini, Andrea, Zizzo, Steven, Zong, Wenxia, Zukerman, L. Steven, Romiti, Giulio Francesco, Corica, Bernadette, Proietti, Marco, Mei, Davide Antonio, Frydenlund, Juliane, Bisson, Arnaud, Olshansky, Brian, Chan, Yi-Hsin, Huisman, Menno V., and Chao, Tze-Fan

Published
2023
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42. Anticoagulation-Associated Adverse Drug Events in Hospitalized Patients Across Two Time Periods

Author

Fanikos, John, Tawfik, Yahya, Almheiri, Danya, Sylvester, Katelyn, Buckley, Leo F., Dew, Chris, Dell'Orfano, Heather, Armero, Andre, Bejjani, Antoine, Bikdeli, Behnood, Campia, Umberto, Davies, Julia, Fiumara, Karen, Hogan, Heather, Khairani, Candrika Dini, Krishnathasan, Darsiya, Lou, Junyang, Makawi, Alaa, Morrison, Ruth H., Porio, Nicole, Tristani, Anthony, Connors, Jean M., Goldhaber, Samuel Z., and Piazza, Gregory

Published
2023
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44. The N-glycome regulates the endothelial-to-hematopoietic transition

Author

Kasper, Dionna M, Hintzen, Jared, Wu, Yinyu, Ghersi, Joey J, Mandl, Hanna K, Salinas, Kevin E, Armero, William, He, Zhiheng, Sheng, Ying, Xie, Yixuan, Heindel, Daniel W, Park, Eon Joo, Sessa, William C, Mahal, Lara K, Lebrilla, Carlito, Hirschi, Karen K, and Nicoli, Stefania

Subjects
Biological Sciences, Medicinal and Biomolecular Chemistry, Chemical Sciences, Hematology, Stem Cell Research, Regenerative Medicine, Genetics, Stem Cell Research - Nonembryonic - Non-Human, Aetiology, 2.1 Biological and endogenous factors, ADAM10 Protein, Animals, Animals, Genetically Modified, Cell Lineage, Cell Transdifferentiation, Endothelial Cells, Genes, Reporter, Glycomics, Glycoproteins, Glycosylation, Hematopoietic Stem Cells, Mannosyltransferases, MicroRNAs, Polysaccharides, Sialyltransferases, Zebrafish, beta-Galactoside alpha-2, 3-Sialyltransferase, General Science & Technology
Abstract

Definitive hematopoietic stem and progenitor cells (HSPCs) arise from the transdifferentiation of hemogenic endothelial cells (hemECs). The mechanisms of this endothelial-to-hematopoietic transition (EHT) are poorly understood. We show that microRNA-223 (miR-223)-mediated regulation of N-glycan biosynthesis in endothelial cells (ECs) regulates EHT. miR-223 is enriched in hemECs and in oligopotent nascent HSPCs. miR-223 restricts the EHT of lymphoid-myeloid lineages by suppressing the mannosyltransferase alg2 and sialyltransferase st3gal2, two enzymes involved in protein N-glycosylation. ECs that lack miR-223 showed a decrease of high mannose versus sialylated sugars on N-glycoproteins such as the metalloprotease Adam10. EC-specific expression of an N-glycan Adam10 mutant or of the N-glycoenzymes phenocopied miR-223 mutant defects. Thus, the N-glycome is an intrinsic regulator of EHT, serving as a key determinant of the hematopoietic fate.

Published
2020

45. Self-injury and suicidal behavior in children and youth population: Learning from the pandemic

Author

Paula Vázquez López, Paula Armero Pedreira, Lidia Martínez-Sánchez, José Miguel García Cruz, Concha Bonetde Luna, Félix Notario Herrero, Ana Rosa Sánchez Vázquez, Pedro Javier Rodríguez Hernández, and Azucena Díez Suárez

Subjects
Autolesiones, Suicidio, Salud mental, Adolescentes, Pediatrics, RJ1-570
Abstract

Introduction: Suicidal behaviour and self-harm are increasing in children and adolescents. Non-suicidal self-harm are a dysfunctional method of emotional regulation, and it must be distinguished from suicidal behaviours. Methods: Narrative review of the current situation on suicide and self-harm in Spain. Descriptive study of suicidal behaviours in paediatric emergencies. Results: Mental health consultations were analysed (March-2019 to March-2020 and March-2020 to March-2021) in a multicentric study of the SEUP (Spanish Society of Pediatric Emergencies), finding a 122 % increase of the diagnosis of ''non-accidental drug intoxication” and 56 % of “suicide/suicide attempt/suicidal ideation”. In another prospective analysis, 281 attempts were recorded, with the patient profile being: female (90.1 %), 14.8 years old, 34.9 % without previous psychiatric diagnosis; 57.7% with previous suicidal behaviour. The presence of psychiatric disorders, especially depression, and previous attempts, are the best-known risk factors for suicidal behaviour, although other factors are involved (family, personal or social). Pediatricians should be trained to deal with questions about suicide and acquire the skills to conduct an interview with a supportive and empathetic attitude. In Spain, suicide prevention plans are heterogeneous among communities, and there is not a unified national suicide prevention plan. Conclusions: Primary, hospital and mental health care resources for paediatric population should be strengthened to prevent suicidal behaviours. Specific training for school staff, and child and adolescent psychiatry training for paediatricians and nurses are crucial in the prevention of suicide in children and adolescent population. Resumen: Introducción: Las conductas suicidas y las autolesiones están aumentando en niños y adolescentes. Las autolesiones no suicidas suponen un método disfuncional de regulación emocional. Es importante aprender a distinguirlas de las conductas suicidas. Material y métodos: Revisión narrativa de la situación actual sobre suicidio y autolesiones en España. Estudio descriptivo conductas suicidas en urgencias pediátricas. Resultados: En un estudio multicéntrico de la SEUP (sociedad Española de Urgencias Pediátricas) se analizaron las consultas por salud mental (marzo-2019 a marzo-2020 y marzo-2020 a marzo-2021), encontrándose un aumento de 122% del diagnóstico “intoxicación no accidental por fármacos” y de 56% en “suicidio/ intento de suicidio/ideación autolítica”. En otro análisis prospectivo, se registraron 281 tentativas, siendo el perfil de paciente: sexo femenino (90,1%), 14,8 años, 34,9% sin diagnóstico psiquiátrico previo, 57,7% con conductas suicidas anteriormente. La presencia de trastornos psiquiátricos, en especial de depresión, y de intentos previos, son los factores de riesgo más implicados en la conducta suicida, aunque existen otros de índole diversa (familiares, personales o sociales). Los pediatras deben estar formados para atender consultas sobre suicidio, y adquirir habilidades para realizar una entrevista con actitud de apoyo y empatía. En España los planes de prevención de suicidio son heterogéneos y no existe un plan nacional de prevención del suicidio. Conclusiones: Se deben reforzar los recursos de atención primaria, hospitalaria y de salud mental de población pediátrica. Los centros escolares y la formación en psiquiatría infantil y adolescente para médicos y enfermeras resultan cruciales en la prevención del suicidio en niños y adolescentes.

Published
2023
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46. Computational Thinking in K-12 Education. An Insight through Meta-Analysis

Author

Merino-Armero, José Miguel, González-Calero, José Antonio, and Cózar-Gutiérrez, Ramón

Abstract

The interest in computational thinking development at pre-university education stage is increasing. In this study, a meta-analysis was conducted to address two main objectives: (a) to analyze the effectiveness of empirical interventions in K-12 education for the development of Computational Thinking (CT); and (b) to identify and evaluate the variables that influences the effectiveness of the interventions. The analysis was especially focused on the intra-group effect sizes. Interventions show large effect size in the development of CT in the comparison between pre- and post-tests (g = 1.044). Among the different types of interventions, programming is the most efficient learning tool.

Published
2022
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47. DNA methylation clocks for dogs and humans

Author

Horvath, Steve, Lu, Ake T., Haghani, Amin, Zoller, Joseph A., Li, Caesar Z., Lim, Andrea R., Brooke, Robert T., Raj, Ken, Serres-Armero, Aitor, Dreger, Dayna L., Hogan, Andrew N., Plassais, Jocelyn, and Ostrander, Elaine A.

Published
2022

48. Major cardiovascular events after COVID-19, event rates post-vaccination, antiviral or anti-inflammatory therapy, and temporal trends: Rationale and methodology of the CORONA-VTE-Network study

Author

Bikdeli, Behnood, Khairani, Candrika D., Krishnathasan, Darsiya, Bejjani, Antoine, Armero, Andre, Tristani, Anthony, Davies, Julia, Porio, Nicole, Assi, Ali A., Nauffal, Victor, Campia, Umberto, Almarzooq, Zaid, Wei, Eric, Achanta, Aditya, Jesudasen, Sirus J., Tiu, Bruce C., Merli, Geno J., Leiva, Orly, Fanikos, John, Sharma, Aditya, Vishnevsky, Alec, Hsia, Judith, Nehler, Mark R., Welker, James, Bonaca, Marc P., Carroll, Brett J., Lan, Zhou, Goldhaber, Samuel Z., and Piazza, Gregory

Published
2023
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