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375 results on '"Jesus, Alejandro"'

1. ALMA Survey of Orion Planck Galactic Cold Clumps (ALMASOP): Nested Morphological and Kinematic Structures of Outflows Revealed in SiO and CO Emission

Author

Liu, Chun-Fan, Shang, Hsien, Johnstone, Doug, Ai, Tsung-Han, Lee, Tsz Ming, Krasnopolsky, Ruben, Hirano, Naomi, Dutta, Somnath, Hsu, Shih-Ying, López-Vázquez, Jesús Alejandro, Liu, Sheng-Yuan, Liu, Tie, Tatematsu, Ken'ichi, Zhang, Qizhou, Rawlings, Mark G., Eden, David, Ren, Zhiyuan, Sanhueza, Patricio, Kwon, Woojin, Lee, Chang Won, Kuan, Yi-Jehng, Bandopadhyay, Somdeb, Väisälä, Miikka S., Lee, Chin-Fei, and Das, Indrani

Subjects
Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

The Atacama Large Millimeter/submillimeter Array Survey of Orion Planck Galactic Cold Clumps (ALMASOP) reveals complex nested morphological and kinematic features of molecular outflows through the CO (J = 2 - 1) and SiO (J = 5 - 4) emission. We characterize the jet and outflow kinematics of the ALMASOP sample in four representative sources (HOPS 10, 315, 358, and G203.21-11.20W2) through channel maps and position-velocity diagrams (PVDs) parallel and transverse to the outflow axes. The combined CO and SiO emission exhibits the coexistence of the conventional extremely-high-velocity (EHV) jets and shell-like low-velocity (LV) cavity walls and new features. More complex, nested bubble-like and filamentary structures in the images and channel maps, triangle-shaped regions near the base of the parallel PVDs, and regions composed of rhombus/oval shapes in the transverse PVDs, are also evident. Such features find natural explanations within the bubble structure of the unified model of jet, wind, and ambient medium. The reverse shock cavity is revealed on the PVD base regions, and other features naturally arise within the dynamic postshock region of magnetic interaction. The finer nested shells observed within the compressed wind region reveal previously unnoticed shocked emission between the jet and the conventional large cavity walls. These pseudopulse-produced filamentary features connect to the jet-like knotty blobs, creating an impression of episodicity in mass ejection. SiO emission is enhanced downstream of the reverse shock boundary, with jet-like excitation conditions. Combined, these observed features reveal the extended structures induced by the magnetic interplay between a jet-bearing magnetized wide-angle wind and its ambient magnetized surrounding medium., Comment: 27 pages, 11 figures, accepted by ApJ

Published
2024
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2. Risk Assessment for Autonomous Landing in Urban Environments using Semantic Segmentation

Author

Loera-Ponce, Jesús Alejandro, Mercado-Ravell, Diego A., Becerra-Durán, Israel, and Valentin-Coronado, Luis Manuel

Subjects
Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition
Abstract

In this paper, we address the vision-based autonomous landing problem in complex urban environments using deep neural networks for semantic segmentation and risk assessment. We propose employing the SegFormer, a state-of-the-art visual transformer network, for the semantic segmentation of complex, unstructured urban environments. This approach yields valuable information that can be utilized in smart autonomous landing missions, particularly in emergency landing scenarios resulting from system failures or human errors. The assessment is done in real-time flight, when images of an RGB camera at the Unmanned Aerial Vehicle (UAV) are segmented with the SegFormer into the most common classes found in urban environments. These classes are then mapped into a level of risk, considering in general, potential material damage, damaging the drone itself and endanger people. The proposed strategy is validated through several case studies, demonstrating the huge potential of semantic segmentation-based strategies to determining the safest landing areas for autonomous emergency landing, which we believe will help unleash the full potential of UAVs on civil applications within urban areas.

Published
2024

3. Risk Assessment for UAV Autonomous Landing in Urban Environments Using Semantic Segmentation

Author

Loera-Ponce, Jesús Alejandro, Mercado-Ravell, Diego A., Becerra, Israel, Valentin-Coronado, Luis Manuel, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Correia, Luís, editor, Rosá, Aiala, editor, and Garijo, Francisco, editor

Published
2025
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5. Episodic Accretion in Protostars -- An ALMA Survey of Molecular Jets in the Orion Molecular Cloud

Author

Dutta, Somnath, Lee, Chin-Fei, Johnstone, Doug, Lee, Jeong-Eun, Hirano, Naomi, Di Francesco, James, Moraghan, Anthony, Liu, Tie, Sahu, Dipen, Liu, Sheng-Yuan, Tatematsu, Kenichi, Lee, Chang Won, Li, Shanghuo, Eden, David, Juvela, Mika, Bronfman, Leonardo, Hsu, Shih-Ying, Kim, Kee-Tae, Kwon, Woojin, Sanhueza, Patricio, Lopez-Vazquez, Jesus Alejandro, Luo, Qiuyi, and Yi, Hee-Weon

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Solar and Stellar Astrophysics
Abstract

Protostellar outflows and jets are almost ubiquitous characteristics during the mass accretion phase, and encode the history of stellar accretion, complex-organic molecule (COM) formation, and planet formation. Episodic jets are likely connected to episodic accretion through the disk. Despite the importance, there is a lack of studies of a statistically significant sample of protostars via high-sensitivity and high-resolution observations. To explore episodic accretion mechanisms and the chronologies of episodic events, we investigated 42 fields containing protostars with ALMA observations of CO, SiO, and 1.3\,mm continuum emission. We detected SiO emission in 21 fields, where 19 sources are driving confirmed molecular jets with high abundances of SiO. Jet velocities, mass-loss rates, mass-accretion rates, and periods of accretion events are found to be dependent on the driving forces of the jet (e.g., bolometric luminosity, envelope mass). Next, velocities and mass-loss rates are positively correlated with the surrounding envelope mass, suggesting that the presence of high mass around protostars increases the ejection-accretion activity. We determine mean periods of ejection events of 20$-$175 years for our sample, which could be associated with perturbation zones of $\sim$ 2$-$25\,au extent around the protostars. Also, mean ejection periods are anti-correlated with the envelope mass, where high-accretion rates may trigger more frequent ejection events. The observed periods of outburst/ejection are much shorter than the freeze-out time scale of the simplest COMs like CH$_3$OH, suggesting that episodic events largely maintain the ice-gas balance inside and around the snowline., Comment: Submitted to Journal; 27 pages, 15 Figures and additional Appendix material

Published
2023

7. Robo-Surveillance of a Solar Park for a Workshop in Interdisciplinary Education

Author

Arriola-Ríos, Verónica E., Arzate Trujillo, Ricardo César, Franco Piña, Jesús Alejandro, Maldonado Vázquez, Alejandro, del Moral Morales, Francisco Emanuel, Liprandi Cortes, Rodrigo, Prado Oropeza, Karina Vianey, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ronzhin, Andrey, editor, Savage, Jesus, editor, and Meshcheryakov, Roman, editor

Published
2024
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8. Machine learning approaches for COVID-19 detection from chest X-ray imaging: A Systematic Review

Author

Arteaga-Arteaga, Harold Brayan, delaPava, Melissa, Mora-Rubio, Alejandro, Bravo-Ortíz, Mario Alejandro, Alzate-Grisales, Jesus Alejandro, Arias-Garzón, Daniel, López-Murillo, Luis Humberto, Buitrago-Carmona, Felipe, Villa-Pulgarín, Juan Pablo, Mercado-Ruiz, Esteban, Orozco-Arias, Simon, Hassaballah, M., de la Iglesia-Vaya, Maria, Cardona-Morales, Oscar, and Tabares-Soto, Reinel

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

There is a necessity to develop affordable, and reliable diagnostic tools, which allow containing the COVID-19 spreading. Machine Learning (ML) algorithms have been proposed to design support decision-making systems to assess chest X-ray images, which have proven to be useful to detect and evaluate disease progression. Many research articles are published around this subject, which makes it difficult to identify the best approaches for future work. This paper presents a systematic review of ML applied to COVID-19 detection using chest X-ray images, aiming to offer a baseline for researchers in terms of methods, architectures, databases, and current limitations.

Published
2022

9. Non-Linear Biomechanical Evaluation and Comparison in the Assessment of Three Different Piece Dental Implant Systems for the Molar Region: A Finite Element Study

Author

Jesus Alejandro Serrato-Pedrosa, Ignacio Villanueva-Fierro, Rodrigo Arturo Marquet-Rivera, Rosa Alicia Hernández-Vázquez, Salvador Cruz-Lopez, and Verónica Loera-Castañeda

Subjects
dental implant systems, finite element method, numerical approach, mechano-biological behavior, biomechanics, Biotechnology, TP248.13-248.65, Medicine (General), R5-920
Abstract

The widely available options of different manufacturers in dental implant systems have complicated the selection criteria process for periodontists, necessitating careful consideration of various factors when selecting suitable solutions for individual patient needs. Optimal implant selection requires careful consideration of the patient-specific factors, implant design, and surgical technique. Understanding the biomechanical behavior of implant–tissue interactions is crucial for achieving successful and long-lasting implant therapy. To adequately address this issue and improve the rigorous selection criteria from a biomechanically numerical approach, this research aims to analyze the stress distribution fields, strain patterns, and load transfer displacements within the implant system and the implant–biological interface (gingival and bony tissues) of titanium three-piece to two–one-piece ceramic implant systems. Thus, three different commercially available dental implants designed to be placed in the jaw molar region were considered for evaluation through the finite element method under both oblique and occlusal loading conditions. The results have exhibited an increasing trend to highlight the outstanding behavior of two-piece ceramic implants to dissipate the stress distribution better (6 and 2 times lower than the three- and one-piece systems under occlusal loads and almost 5 and 1.3 times more efficient for oblique loading, respectively), minimize peak stress values (below 100 MPa), and reduce strain peak patterns compared with the other two evaluated designs. On the other hand, the effects generated in biological tissues are strongly associated with implant geometry features. This biomechanical approach could provide a promising strategy for predicting micro-strains and micromotion in implant system pieces and geometries. Hence, these findings contribute to a deeper understanding of the biomechanics spectrum in the behavior of dental implant systems and emphasize the importance of carefully selecting appropriate material systems for accurate patient-specific biomechanical performance.

Published
2025
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12. Maternal Supplementation with Lacticaseibacillus rhamnosus GG Improves Glucose Tolerance and Modulates the Intestinal Microbiota of Offspring

Author

Dayane Correia Gomes, José Enrique Meza Alvarado, Jesus Alejandro Zamora Briseño, Cynthia Cano Sarmiento, Alberto Camacho Morales, and Rubi Viveros Contreras

Subjects
Lacticaseibacillus rhamnosus, maternal programming, metabolic syndrome, glucose intolerance, high-fat diet, Medicine
Abstract

Introduction: Consuming hypercaloric diets during pregnancy induces metabolic, immune, and maternal intestinal dysbiosis disorders. These conditions are transferred to the offspring through the placenta and breastfeeding, increasing susceptibility to metabolic diseases. We investigated the effect of L. rhamnosus GG supplementation on offspring maternally programmed with a hypercaloric diet. Methods: Our study involved sixteen female Wistar rats aged ten weeks, which were divided into four groups based on their diets: control (Ctrl), cafeteria (CAF), control + probiotic (PRO), and cafeteria + probiotic (CPRO). The control + probiotic and cafeteria + probiotic groups received a daily oral administration of 250 μL of L. rhamnosus GG cell suspension (equivalent to 109 UFC) for nine weeks. The body weight of the animals was recorded weekly, and their food intake was monitored every 24 h. An oral glucose tolerance test was conducted on the offspring at seven weeks of age. At the ninth week of age, animals were euthanized, and blood, tissues, and organs were collected. Results: Maternal supplementation with L. rhamnosus GG decreased food intake and the average birth weight, improved glucose sensitivity, and lowered the levels of LDL, cholesterol, triglycerides, and mesenteric adipose tissue in offspring compared with the control and cafeteria groups. Conclusions: Our findings indicate that supplementing with LGG during maternal programming could protect offspring from metabolic disruptions caused by a hypercaloric maternal diet.

Published
2024
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13. Isolated High-Gain DC-DC Converter with Nanocrystalline-Core Transformer: Achieving 1:16 Voltage Boost for Renewable Energy Applications

Author

Tania Sandoval-Valencia, Dante Ruiz-Robles, Jorge Ortíz-Marín, Jesus Alejandro Franco, Quetzalcoatl Hernandez-Escobedo, and Edgar Moreno-Goytia

Subjects
high voltage gain, isolated DC-DC converters, high efficiency, Technology
Abstract

This paper presents an isolated DC-DC converter with high voltage gain that features an advanced inter-built nanocrystalline-core medium-frequency transformer (NC-MFT). The isolated DC-DC converter with an NC-MFT is specifically designed for applications such as interconnect photovoltaic (PV) systems, DC microgrids, DC loads, and DC buses, where voltage gain is one of the essential issues to consider. The NC-MFT inside the DC-DC converter is designed with a new approach that not only provides isolation but also contributes to achieving high efficiency and a higher step-up ratio. The high efficiency of the converters contributes to the integration of PV systems into DC microgrids. The converter yields a high voltage conversion ratio of 16.17. The experimental results obtained at 41.8 V/676 V and 275 W for the prototype revealed high efficiency (95.63% at full load). The experimental results validate the theoretical analysis and simulation, confirming that the converter achieves the main objective of high voltage conversion and high efficiency. These results will contribute to the interest in the use of this type of energy and its impact on the reduction in CO2 emissions.

Published
2024
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14. SARS-CoV-2 Variants of Concern and Clinical Severity in the Mexican Pediatric Population

Author

Anahí Maldonado-Cabrera, Jesus Alejandro Colin-Vilchis, Ubydul Haque, Carlos Velazquez, Andrea Socorro Alvarez Villaseñor, Luis Eduardo Magdaleno-Márquez, Carlos Iván Calleros-Muñoz, Karen Fernanda Figueroa-Enríquez, Aracely Angulo-Molina, and Ana Lucía Gallego-Hernández

Subjects
children, COVID-19, severity, hospitalization, mortality, pediatrics, Other systems of medicine, RZ201-999
Abstract

The emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants of concern (VOCs) presents global heterogeneity, and their relative effect on pediatric severity is still limited. In this study, we associate VOCs with pediatric clinical severity outcomes in Mexico. Bioinformatics methods were used to characterize VOCs and single amino acid (aa) mutations in 75,348 SARS-CoV-2 genetic sequences from February 2020 to October 2022. High-predominance VOCs groups were calculated and subsequently associated with 372,989 COVID-19 clinical pediatric outcomes. We identified 21 high-frequency mutations related to Omicron lineages with an increased prevalence in pediatric sequences compared to adults. Alpha and the other lineages had a significant increase in case fatality rate (CFR), intensive critical unit (ICU) admission, and automated mechanical ventilation (AMV). Furthermore, a logistic model with age-adjusted variables estimated an increased risk of hospitalization, ICU/AMV, and death in Gamma and Alpha, in contrast to the other lineages. We found that, regardless of the VOCs lineage, infant patients presented the worst severity prognoses. Our findings improve the understanding of the impact of VOCs on pediatric patients across time, regions, and clinical outcomes. Enhanced understanding of the pediatric severity for VOCs would enable the development and improvement of public health strategies worldwide.

Published
2023
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15. A Novel Proposal in Wind Turbine Blade Failure Detection: An Integrated Approach to Energy Efficiency and Sustainability

Author

Jordan Abarca-Albores, Danna Cristina Gutiérrez Cabrera, Luis Antonio Salazar-Licea, Dante Ruiz-Robles, Jesus Alejandro Franco, Alberto-Jesus Perea-Moreno, David Muñoz-Rodríguez, and Quetzalcoatl Hernandez-Escobedo

Subjects
wind turbine, artificial intelligence, blade failures, energy, sustainability, Orange Data Mining, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

This paper presents a novel methodology for detecting faults in wind turbine blades using computational learning techniques. The study evaluates two models: the first employs logistic regression, which outperformed neural networks, decision trees, and the naive Bayes method, demonstrating its effectiveness in identifying fault-related patterns. The second model leverages clustering and achieves superior performance in terms of precision and data segmentation. The results indicate that clustering may better capture the underlying data characteristics compared to supervised methods. The proposed methodology offers a new approach to early fault detection in wind turbine blades, highlighting the potential of integrating different computational learning techniques to enhance system reliability. The use of accessible tools like Orange Data Mining underscores the practical application of these advanced solutions within the wind energy sector. Future work will focus on combining these methods to improve detection accuracy further and extend the application of these techniques to other critical components in energy infrastructure.

Published
2024
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16. Comparative Proteomic Analysis of Wild and Cultivated Amaranth Species Seeds by 2-DE and ESI-MS/MS

Author

Esaú Bojórquez-Velázquez, Jesus Alejandro Zamora-Briseño, Alberto Barrera-Pacheco, Eduardo Espitia-Rangel, Alfredo Herrera-Estrella, and Ana Paulina Barba de la Rosa

Subjects
Amaranthus, proteomics, two-dimensional gel electrophoresis, seed storage proteins, GBSSI, Botany, QK1-989
Abstract

Amaranth is a promising staple food that produces seeds with excellent nutritional quality. Although cultivated species intended for grain production have interesting agronomic traits, relatively little is known about wild species, which can prosper in diverse environments and could be a rich genetic source for crop improvement. This work focuses on the proteomic comparison between the seeds of wild and cultivated amaranth species using polarity-based protein extraction and two-dimensional gel electrophoresis. Differentially accumulated proteins (DAPs) showed changes in granule-bound starch synthases and a wide range of 11S globulin isoforms. The electrophoretic profile of these proteins suggests that they may contain significant phosphorylation as post-translational modifications (PTMs), which were confirmed via immunodetection. These PTMs may impact the physicochemical functionality of storage proteins, with potential implications for seed agronomic traits and food system applications. Low-abundant DAPs with highly variable accumulation patterns are also discussed; these were involved in diverse molecular processes, such as genic regulation, lipid storage, and stress response.

Published
2024
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17. Consensus document on acute-on-chronic liver failure (ACLF) established by the Mexican Association of Hepatology

Author

Torre, Aldo, Cisneros-Garza, Laura Esthela, Castillo-Barradas, Mauricio, Navarro-Alvarez, Nalu, Sandoval-Salas, Ricardo, González-Huezo, María Sarai, Pérez-Hernández, José Luís, Méndez-Guerrero, Osvely, Ruiz-Manríquez, Jesús Alejandro, Trejo-Estrada, Rafael, Chavez-Tapia, Norberto C., Solís-Gasca, Luis Carlos, Moctezuma-Velázquez, Carlos, Aguirre-Valádez, Jonathan, Flores-Calderón, Judith, Higuera-de-la-Tijera, Fatima, García-Juárez, Ignacio, Canedo-Castillo, Nancy Allin, Malé-Velázquez, René, Montalvo-Gordon, Iaarah, Vilatobá, Mario, Márquez-Guillén, Ernesto, Córdova-Gallardo, Jacqueline, Flores-García, Nayeli Cointa, Miranda-Zazueta, Godolfino, Martínez-Saldívar, Belinda Isela, Páez-Zayas, Víctor Manuel, Muñoz-Espinosa, Linda Elsa, and Solís-Galindo, Francisco Alfonso

Published
2023
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20. Association between use of enhanced recovery after surgery protocols and postoperative complications after gastric surgery for cancer (POWER 4): a nationwide, prospective multicentre study

Author

Farré, Mercè Güell, Font, Roser Farré, del Gobbo, Rafael Diaz, Jimenez, Raquel Sánchez, Reche, Isabel Pérez, Calvo, Belen Gil, García, Jordi Llorca, Sánchez, Laura Carrasco, Llimargas, Cristina Prat, García-Sánchez, Ana María, Martínez-Ragüés, Gema, Gómez-Fernández, María, del-Castillo-Criado, Álvaro, Martínez-Díaz, Ruth, Alegría-Rebollo, Sara, Ferrerode-Paz, Javier, García-Pérez, Cristina, Marcos-Contreras, Sergio, Fernández-García, Diana, Torío-Marcos, Maeva, Fernández, Omar Abdellah, Parreño-Manchado, Felipe Carlos, Martín, María Ángeles, Tena-Guerrero, José María, Palma-González, Estefanía, Flores-Flores, Gustavo, Zugasti-Echarte, Orreaga, Pérez-Bergara, Elena, Hernández-García, Susana, Martín-Vizcaíno, Marta, Yoldi-Murillo, Francisco Javier, Valencia-Alzueta, Maider, Chaveli-Díaz, Carlos, Miranda-Murua, Coro, Yárnoz-Irazábal, Concepción, Botella-Martínez, Sonsoles, López-Pardo, Rafael, Torres-Montalvo, Marta, Pinilla-Pico, Isabel, del-Cojo-Peces, Enrique, del Pilar Rodríguez-Chaparro, María, Gómez-Ríos, Manuel Ángel, del-Río-Regueira, Sara, Mosquera-Rodríguez, Eva, Hernández-Beslmeisl, Jessica, Perozo-Medina, María Alejandra, Darias-Delbey, Beneharo, del Carmen Martín-Lorenzo, María, González-Fariña, Vanessa, Rodríguez-Domínguez, Montserrat, Fernández-de-la-Vega-Medina, Jaime, Berrotarán-Ayub, Pilar, Valín-Martínez, José, Concepción-Santana, Laura, Cruz-Zorio, Raúl, Betancort-Gutiérrez Rodríguez, Dolores, Gómez-Viana, Leticia, Figueiredo, Olalla, Rodríguez, Ariadna, González, Manuel, Iglesias, David, Domínguez-Carrera, José Manuel, Olmo, Jorgedo, Del-Río-Fernández, Sabela, Dos-Santos-Carregal, Laura, Rodríguez-Forja, María Jesús, Campaña-Figueira, Olga, Álvarez-Escudero, Julián, Lesquereux-Martínez, Lucía, Parada-González, Purificación, Montenegro-Romero, Ricardo, Bustamante-Montalvo, Manuel, García-Placín, Ana Rosa, Carpintero-Rama, Carmen, Brea-Bahamonde, Sergio, Torres-Alfonso, José Ramón, Barragán-Serrano, Cristina, Posada-González, María, Salcedo-Cabañas, Gabriel, Vor-wald-Wolfgang, Peter, Otero-Martínez, Isabel, Jove-Alborés, Patricia, López-Otero, Marta, Pardellas-Rivera, Hermelinda, Maruri-Chimeno, Ignacio, González-Fernández, Sonia, Sánchez-Santos, Raquel, Luna-Mendoza, Luis, Lloria-Pons, Enrique, Gramuntell-Marco, Francisco, Cánovas-de-Lucas, Raúl, Sancho-Moya, Cristina, Risco, Raquel, Fernández-Esmerats, Anna, Sanahuja-Blasco, Josep Martí, López-Baamonde, Manuel, Ubré, Marta, Martínez-Pallí, Graciela, Momblán, Dulce, Rivas-Gallardo, Nuria, Sánchez-Martín, Rubén, Moral, Pedro, Navarro, Rosalía, Santé, Luis, Almenta, Esther, Muñoz-Hernández, Henar, Rodríguez-Jiménez, Rita Pilar, Ruiz, Nuria, Peláez, María Teresa, Rojo, Juan José, Gordaliza, Carlota, Jezieniecki, Carlos, Jimenez-Viñas, Carlos, Brugiotti, Carlo, Onchalos-Lopez, Ulices, Llácer-Pérez, Manuel, Batalla, Astrid, Azparren, Gonzalo, Bastitta, Micaela, Cueva, Luisa, Felipe, Mar, Giné, Marta, Gómez, Ana M., India, Inmaculada, Piñol, Santiago, Gimeno-Campos, Maria José, Moreno-Gázquez, Aurora, Llorens-Herrerías, Julio, Del-Castillo-Rodrigo, Gema, Herrero-Bogajo, María Luz, De Miguel-Cabrera, María Isabel, España-Pamplona, José Miguel, Gellida-Vilarroig, María, Jordá-Sanz, Laura, Gil-Trujillo, Silvia, Calatayud-Gómez, Laura, Valencia-Echeverri, Juan David, Baladrón-González, Víctor, Gil-Rendo, Aurora, Sanchez-García, Susana, García-Santos, Esther, Benito, Carmen, Lisbona, Cristina, Benito, Pilar, Correa-Chacón, Olga Cecilia, Alcázar-Urrea, Alejandro, Fernández-López, Ana Belén, Betancourt-Bastidas, Ramiro, Navarro-García, Inmaculada, Romera-Barba, Elena, Mira-Jovells, Nuria, Estevez-Perez, Liz Karime, Saludes-Serra, Judit, Olona-Casas, Carles, Vadillo-Bargalló, Jordi, Jorba-Martín, Rosa, Mojarro, Irene, Lorente, Juan Victor, Longo-Guridi, Pablo, Quintero-Moreno, Ana Maria, Soriano-López, David, de la Peña Gómez-Dominguez, Maria, Prieto-Candau, Cecilia, Hernández-Castillo, Marisol, Jarana, Irene, García-Andreu, Francisco, González-González, Jose, Díaz-Lara, María Dolores, Añón-Iranzo, Elena, Aguiló-Lucia, Javier, Fernandez-Martin, Maria Teresa, Guerra, Yessica, Gimeno-Fernández, Pablo, Iglesias-Morales, Carla, Villalba, Ana María Ríos, Nespereira-García, Paula, Castro-Neira, María José, Ochoa-Díez, María, García-Orallo, Silvia, Mozo-Segurado, Maialen, Gutiérrez-Cabezas, Jose Manuel, Gonzalo-González, Ruben, García-Álvarez, Raquel, Ramiro-Ruíz, Álvaro, González-Cofrade, María, Carvajal-Revuelta, Estefanía, Bellido-López, Ana, Redondo-Cristóbal, Guillermo, Amoza-Pais, Sonia, Díaz-Vico, Tamara, Moreno-Gijón, María, Sanz-Navarro, Sandra, Sanz-Álvarez, Lourdes M, Turienzo-Santos, Estrella Olga, Rodicio-Miravalles, Jose Luis, Rizzo-Ramos, Amaya, Cuéllar-Martínez, Ana, Álvarez-Fernández, Rosa Ana, Fernández-Seijo, Carmen, Álvarez-Barrial, Amelia, Gónzalez-Ortea, Carmen, Fernández-Rodriguez, Silvia, García-González, Nerea, Varela-Rodriguez, Lorena, Berzal-Canga, Elena, García-Díaz-Negrete, Ángela, García-Sánchez, Helena, Saenz-Abos, Javier, Ayuso-Iñigo, Beatriz, Vega-Colón, María, Palacios-Córdoba, Ángela Catalina, Quel-Collado, María Teresa, Olvera-García, Mercedes, Martinez-Sánchez, Agustina, Serrano-Alvarez, Carmen, Ganuza-Martínez, Eunate, Maroño-Boedo, María Jesús, Sánchez-Campos, Alberto, Escontrela-Rodríguez, Blanca Anuncia, Martínez-Ruiz, Alberto, Errazti-Olartecoechea, Gaizka, Rodeño-Esteban, Iratxe, Moreno-Allende, Tamara, Gutierrez-Grijalba, Oihane, Katary-niuk-Di-Costanzo, Yanina, Alvarez-Abad, Irene, Sendino-Cañizares, Patricia, Mifsut-Porcel, Patricia, Sarriugarte-Lasarte, Aingeru, Guerra-Lerma, Mikel, Logroño-Ejea, Margarita, Iturricastillo-Pérez, María Del Carmen, Gastaca-Abasolo, María, Muñoz-Sanz, María José, Iriarte-Zaranton, Ibai, Olea-De-La-Fuente, Erika, Mendiguren-Murua, Ana, Reka-Mediavilla, Lorena, Gastón-Moreno, Alberto, Martínez-De-Aragón-Remirez-De-Esparza, Gabriel Jesús, Sierra-Esteban, Valentín, Montero-Mejías, Gema, Pardo-Martínez, Claudia, Valadés-Periañez, Teresa, Marín-Moreno, Ana, Caro-González, Juan Ricardo, Rodríguez-Pérez, María José, Herrero-Herrero, José Carlos, Renedo-Corcóstegui, Pablo, Martín-Oliva, Alejandro, Fernández-Herrero, Ana Isabel, Andrieu-Estefanía, Nerea, Albaladejo-Magdalena, Javier, Álvarez-Rodriguez, María, Sosa-Rodríguez, Valentina, Fresnedo-Pérez, Raquel María, Gil-Lapetra, Cristina, Bolzoni-Marciel, Beatriz, Herrera-López, Maria Isabel, Setién-Moreno, Fernando, Castro-Costoya, Ana Zulema, Olarra-Nuel, José, De-Vega-Irañeta, Marta, Ugarte-Sierra, Bakarne, Vicente-Rodríguez, Irune, Fernández-Pablos, Francisco Javier, Abad-Alonso, Rafael Alberto, Maniega-Alba, Roberto, Ibáñez-Aguirre, Francisco Javier, Postigo-Morales, Susana, Intxaurraga-Fernández, Karmelo, Telletxea-Benguria, Sorkunde, Outón-Guerrero, Ángela, Acosta-Mérida, María Asunción, de la Plaza-Llamas, Roberto, García-Gil, José Manuel, Gemio-del-Rey, Ignacio Antonio, Cabellos-Olivares, Mercedes, Fernández-García, Raquel, Freitas, Lidia Castro, Alcorta, Beatriz Nacarino, Ayuso, María Martín, González, María Moral, Teruel, David García, Serrat-Puyol, Jordi, Molinas-Bruguera, Joan, Fernández, Sara, Peris-Tomás, Nuria, Díez-Ares, Jose Ángel, Periáñez-Gómez, Dolores, Gonzálvez-Guardiola, Paula, Trullenque-Juan, Ramón, Martínez-Mas, Ezequiel, Martínez, Estefanía, Martín, Julia, Higueras, Raquel, Cuenca, Sara, Martín-Vaquerizo, Beatriz, Espinosa-Moreno, Alma M., Sánchez-Merchante, Miriam, Alcañiz-Sobrino, Rebeca, Egea-Hita, Guillermo, García-del-Valle-y-Manzano, Santiago, Moreno-Blanco, Virginia, Bruna-Esteban, Marcos, Mingol-Navarro, Fernando, Vaqué-Urbaneja, Javier, Díaz-Cambronero, Óscar, Luján-Sandemetrio, Beatriz, Copariate-Piqueras, Bisila, Giménez-Salcedo, Sonia, Ripolles-Melchor, Javier, Abad-Motos, Ane, Abad-Gurumeta, Alfredo, Aracil-Escoda, Norma, Saez-Ruiz, Elena, Salva-chua-Fernandez, Rut, Paseiro-Crespo, Gloria, García-Nebreda, María, Toribio, Begoña, Ferrero-Celemin, Esther, García-Sancho-Téllez, Luis, Sánchez-López, José Daniel, Núñez O'Sullivan, Sara, Gar-cía-Virosta, Mariana, Rodriguez-Haro, Carmen, Hernández-O’Reilly, María, Suarez-de-la-Rica, Alejandro, Lopez-Martinez, Mercedes, Croes, Bryant, Mujica, Jaime, Maseda, Emilio, Alday-Muñoz, Enrique, Mata-Mena, Esperanza, García-Sanz, Iñigo, Marín, Cristina, Muñoz, Antonio Pedraza, Dominguez, Jorge Puertas, González-López, Rocío, Navarro-Quirós, Gisela, Pérez-Moreiras, M. Isabel, Conde-Rodriguez, María, Muinelo-Lorenzo, Manuel, Díez-Zapirain, Miren Jasone, Tejón-Pérez, Guillermo, Álvarez-Cebrián, María Asunción, Barrero-Ruiz, Eva, Capa-Fuertes, Eva, Carrillo-Rivas, Mariana, Hernandez-Sanchez, Isabel, Monteagudo-Cimiano, Valvanuz, Pascual-Casado, Ángela, Rábago-Morillón, Jose Luis, Martinez-Ubieto, Javier, Pascual-Bellosta, Ana, Ortega-Lucea, Sonia, Perez-Otal, Berta, Tardos-Ascaso, Lucia, Ligorred-Padilla, Luis Antonio, Tur-Martínez, Jaume, Rodríguez-Santiago, Joaquin, Pérez-Romero, Noelia, Puértolas-Rico, Noelia, Hernández-Giménez, Laura, Concepción-Martín, Vanessa, Molnar, Viktoria, Barbero, Macarena, San-Antonio, Belén, Pueyo, Alberto, Mayo-Ossorio, M de los Angeles, Bengoechea-Trujillo, Ander, Pacheco-Garcia, José Manuel, Diez-Remesal, Yolanda, Gonzalo-Millán, Alba, Berruezo-Camacho, Alberto, Alaez-Cortés, Azucena, Ortolá-Rocher, Begoña, Iglesias-Gallego, Berta, Martín-Montero, Eduardo, Arias-Cuesta, Gerardo, de la Hoz-Polo, Inés, Recuero-Torrijos, Isabel, Pereira-Torres, Lucia, Cañamas-Catalá, Maria, Martin-González, Maria C., Zambrana-García, Paloma, Llorente-Damas, Sergio, Aldecoa, Cesar, Perez-Gonzalez, Alba, Bolaño-Perez, Clara, Velasco-Andres, Delia, Aguado-Saster, Esther, Arranz, Irene, Mendez-Torrubiano, Itziar, Vaquero-Perez, Laura, Sanz-de-Leon, Maria Jesus, Rodicio, Pablo, Martin-Alfonso, Silvia, Martin-Tappi, David, Madrid-Tribano, Mario, Rioja-Garrido, Rocio, Morales-Jaquete, Borja, Vicente-Orgaz, Marta, Orozco-Vinasco, Adriana Carolina, Fraga-Casais, Gema, Miyagi-Yonamine, Any Minerva, Ramos-de-Castro, Raquel, Mejía-Arnaud, Rossel Alina, Saz-Castro, Rubén, Díaz-Peña, Patricia, Camps-Cervantes, Angels, Tormos-Perez, M Pilar, Galan-Menendez, Patricia, Esclapez-Sampere, Elena, Villarino-Villa, Laura, Loaiza-Aldeán, Yuri, Chocron-Dapratt, Ivette, Martinez-Silva, Olga, Matarin-Olmo, Silvia, Berges-Gutiérrez, Héctor, Pérez-Serrano, Macarena, Diaz-Castillo, Juan Javier, Sancho-Muñoz-de-Verger, Álvaro, Villanueva-Mena-Bernal, Jesús Alejandro, Gil-Gómez, Maria Lucia, Fernanz-Anton, Jesús, Marmaña-Mezquita, Sandra, Galofré-Pujol, Gonzalo, Jericó, Carlos, Motos-Micó, José Jacob, Orts-Micó, Francisco José, Serra-Díaz, Carlos, Arlandis-Félix, Francisco, Pérez-Climent, Nieves, Blanes-Pastor, Lorena, Jover-Pinillos, Jose Luis, Salvaterra, David, Linero, Manuel, Galipienzo, Javier, Alonso, Óscar, Ortega, Gloria, Gonzalez, Santiago, Lopez-Rojo, Irene, Ripollés-Melchor, Javier, Abdel-lah Fernández, Omar, Tormos-Pérez, María P., A Mayo-Ossorio, María, Gil-Gómez, Lucia, Parreño-Manchado, Felipe C, De-Miguel-Cabrera, María I, García-Erce, José A., Río-Fernández, Sabela del, Herrero-Bogajo, María L., Zorrilla-Vaca, Andrés, Vaquero-Pérez, Laura, Fernández-Martín, María T., Ferrando-Ortolà, Carlos, Ramírez-Rodríguez, José M., and Aldecoa, César

Published
2023
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21. Intravenous aviptadil and remdesivir for treatment of COVID-19-associated hypoxaemic respiratory failure in the USA (TESICO): a randomised, placebo-controlled trial

Author

Tierney, John, Vogel, Susan E., McNay, Laura A., Cahill, Kelly, Crew, Page, Sardana, Ratna, Segal Raim, Sharo, Shaw-Saliba, Katy, Atri, Negin, Miller, Mark, Vallee, David, Chung, Lucy, Delph, Yvette, Adam, Stacey J., Read, Sarah, Draghia-Akli, Ruxandra, Harrigan, Rachel, Carlsen, Amy, Carter, Anita, DuChene, Alain, Eckroth, Kate, Frase, Alex, Harrison, Merrie, Meger, Sue, Quan, Kien, Quan, Siu Fun, Reilly, Cavan, Thompson, Greg, Walski, Jamie, Moskowitz, Alan J., Bagiella, Emilia, Moquete, Ellen, O'Sullivan, Karen, Marks, Mary E., Accardi, Evan, Kinzel, Emily, Bedoya, Gabriela, Gupta, Lopa, Overbey, Jessica R., Padillia, Maria L., Santos, Milerva, Gillinov, Marc A., Miller, Marissa A., Taddei-Peters, Wendy C., Fenton, Kathleen, Smith, Peter K., Vekstein, Andrew M., Ko, Emily R., Al-Hegelan, Mashael S., McGowan, Lauren M., Motta, Mary, Howell, Shauna, Bent, Francine, Kalager, Rachel, Chan, Emmanuel, Aloor, Heather L., Griffin, S. Michelle, Covington, Anna, McLendon-Arvik, Beth, Bussadori, Barbara, Miller-Bell, Mary, Sampey, Cathy, Gaver, Vincent, Hollister, Beth A., Giangiacomo, Dana M., Pauley, Alena, Patel, Aashay, Classon, Chris, Frazier, Madison, Osborne, Robyn, Conlon, Debbi H., Joshi, Marybeth, Gottlieb, Robert L., Mack, Michael, Berhe, Mezgebe, Haley, Clinton, Dishner, Emma, Bettacchi, Christopher, Golden, Kevin, Duhaime, Erin, Ryan, Madison, Tallmadge, Catherine, Estrada, Lorie, Jones, Felecia, Villa, Samantha, Wang, Samantha, Robert, Raven, Coleman, Tanquinisha, Clariday, Laura, Baker, Rebecca, Hurutado-Rodriguez, Mariana, Iram, Nazia, Fresnedo, Michelle, Davis, Allyson, Leonard, Kiara, Ramierez, Noelia, Thammavong, Jon, Duque, Krizia, Turner, Emma, Fisher, Tammy, Robinson, Dianna, Ransom, Desirae, Maldonado, Nicholas, Lusk, Erica, Killian, Aaron, Palacios, Adriana, Solis, Edilia, Jerrow, Janet, Watts, Matthew, Whitacre, Heather, Cothran, Elizabeth, Bender, William, Miller, Jeffrey, Nugent, Katherine, Farrington, Woodrow, Baio, Kim T., McBride, Mary K., Fielding, Michele, Mathewson, Sonya, Porte, Kristina, Haley, Elizabeth, Rogers, Susan, Tyler, Derrick, Perin, Emerson, Costello, Briana, Postalian, Alexander, Sohail, Rizwan, Hinsu, Punit, Watson, Carolyn, Kappenman, Casey, Chen, James, Walker, Kim, Fink, Melyssa, Phillip, Gabrielle, Mahon, Kim, Sturgis, Lydia, Maher, Patrick, Rogers, Linda, Ng, Nicole, Marshall, Jason, Bassily-Marcus, Adel, Cohen, Ivy, Ramoo, Shamini, Malhotra, Aryan, Kessler, Jonathan, Goetz, Rebekah, Badhwar, Vinay, Hayanga, Jeremiah, Giblin Sutton, Lisa, Williams, Roger, Berry Bartolo, Elizabeth, Walker, Dmitry, Bunner, Robin, Glaze, Chad, Aucremanne, Tanja, Bishop, James, Kelley, Macey, Peterson, Autumn, Sauerborn, Erica, Reckart, Robin, Miller, Brittany, Mittel, Aaron, Darmanian, Anita, Rosen, Amanda, Madahar, Purnema, Schicchi, John, Gosek, Katarzyna, Dzierba, Amy, Wahab, Romina, Eng, Connie, Al-Saadi, Mukhtar, Zahiruddin, Faisal, Syed, Mohi, George, Michael, Patel, Varsha, Onwunyi, Chisom, Barroso da Costa, Rosa, North, Crystal, Ringwood, Nancy, Fitzgerald, Laura, Muzikansky, Ariela, Morse, Richard, Brower, Roy G., Reineck, Lora A., Bienstock, Karen, Hou, Peter, Steingrub, Jay S., Tidswell, Mark A., Kozikowski, Lori-Ann, Kardos, Cynthia, De Souza, Leslie, Talmor, Daniel, Shapiro, Nathan, Hibbert, Kathryn, Brait, Kelsey, Kone, Mamary, Hendey, Gregory, Kangelaris, Kirsten N., Ashktorab, Kimia, Gropper, Rachel, Agrawal, Anika, Timothy, Kelly, Zhou, Hanjing, Hughes, Alyssa, Garcia, Rebekah, Torres, Adrian, Hernandez-Almaraz, Maria Elena, Vojnik, Rosemary, Perez, Cynthia, McDowell, Jordan, Chang, Steven Y., Vargas, Julia, Moss, Marc, McKeehan, Jeffrey, Higgins, Carrie, Johnson, Emily, Slaughter, Suzanne, Wyles, David, Hiller, Terra, Oakes, Judy, Garcia, Ana, Gravitz, Stephanie, Lyle, Carolynn, Swanson, Diandra, Gong, Michelle Ng., Richardson, Lynnne D., Chen, Jen-Ting, Moskowitz, Ari, Mohamed, Amira, Lopez, Brenda, Amosu, Omowunmi, Tzehaie, Hiwet, Boujid, Sabah, Bixby, Billie, Lopez, Anitza A., Durley, JaVon, Gilson, Boris, Hite, R. Duncan, Wang, Henry, Wiedemann, Hebert P., Mehkri, Omar, Ashok, Kiran, King, Alexander, Brennan, Connery, Exline, Matthew C., Englert, Joshua A., Karow, Sarah, Schwartz, Elizabeth, So, Preston, So, Madison, Krol, Olivia F., Briceno Parra, Genesis I., Mills, Emmanuel Nii Lantei, Oh, Minn, Pena, Jose, Martínez, Jesús Alejandro, Jackman, Susan E., Bayoumi, Emad, Pascual, Ethan, Caudill, Antonina, Chen, Po-En, Richardson, Tabia, Clapham, Gregg J., Herrera, Lisa, Ojukwu, Cristabelle, Fine, Devin, Gomez, Millie J., Choi-Kuaea, Yunhee, Weissberg, Gwendolyn, Isip, Katherine, Mattison, Brittany, Tran, Dana, Emilov Dukov, Jennifer, Chung, Paul, Kang, Bo Ran, Escobar, Lauren, Tran, Trung, Baig, Saba, Wallick, Julie A., Duven, Alexandria M., Fletcher, Dakota D., Gundel, Stephanie, Fuentes, Megan, Newton, Maranda, Peterson, Emily, Jiang, Kelsey, Files, D. Clark, Miller, Chadwick, Lematty, Caitlin, Rasberry, April, Warden, Ashley, Bledsoe, Joseph, Knowlton, Kirk, Knox, Daniel B., Klippel, Carolyn, Armbruster, Brent P., Applegate, Darrin, Imel, Karah, Fergus, Melissa, Rahmati, Kasra, Jensen, Hannah, Aston, Valerie T., Jeppson, Joshua, Marshall, J. Hunter, Lumpkin, Jenna, Smith, Cassie, Burke, Tyler, Gray, Andrew, Paine, Robert, Callahan, Sean, Yamane, Misty, Waddoups, Lindsey, Rice, Todd W., Johnson, Jakea, Gray, Christopher, Hays, Margaret, Roth, Megan, Musick, Sarah, Miller, Karen, Semler, Matthew W., Popielski, Laura, Kambo, Amy, Viens, Kimberly, Turner, Melissa, Vjecha, Michael J., Denyer, Rachel, Khosla, Rahul, Rajendran, Bindu, Gonzales, Melissa, Moriarty, Theresa, Biswas, Kousick, Harrington, Cristin, Garcia, Amanda, Bremer, Tammy, Burke, Tara, Koker, Brittany, Pittman, David, Vasudeva, Shikha S., Anholm, James D., Specht, Lennard, Rodriguez, Aimee, Ngo, Han, Duong, Lien, Previte, Matthew, Raben, Dorthe, Nielsen, Charlotte B., Friis Larsen, Jakob, Peters, Lars, Matthews, Gail, Kelleher, Anthony, Polizzotto, Mark, Carey, Catherine, Chang, Christina, Dharan, Nila, Hough, Sally, Virachit, Sophie, Davidson, Sarah, Bice, Daniel J., Ognenovska, Katherine, Cabrera, Gesalit, Flynn, Ruth, Abdelghany, Mazin, Baseler, Beth, Teitelbaum, Marc, Holley, H. Preston, Jankelevich, Shirley, Adams, Amy, Becker, Nancy, Doleny, Suzanne, Hissey, Debbie, Simpson, Shelly, Kim, Mi Ha, Beeler, Joy, Harmon, Liam, Vanderpuye, Sharon, Yeon, Lindsey, Frye, Leanna, Rudzinski, Erin, Buehn, Molly, Eccard-Koons, Vanessa, Frary, Sadie, MacDonalad, Leah, Cash, Jennifer, Hoopengardner, Lisa, Linton, Jessica, Nelson, Michaela, Spinelli-Nadzam, Mary, Proffitt, Calvin, Lee, Christopher, Engel, Theresa, Fontaine, Laura, Osborne, CK, Hohn, Matt, Galcik, Michael, Thompson, DeeDee, Sandrus, Jen, Manchard, Jon, Giri, Jiwan, Kopka, Stacy, Chang, Weizhong, Sherman, Brad T., Rupert, Adam W., Highbarger, Helene, Baseler, Michael, Lallemand, Perrine, Rehman, Tauseef, Imamichi, Tom, Laverdure, Sylvain, Paudel, Sharada, Cook, Kyndal, Haupt, Kendra, Hazen, Allison, Badralmaa, Yunden, Highbarger, Jeroen, McCormack, Ashley, Gerry, Norman P., Smith, Kenneth, Patel, Bhakti, Domeraski, Nadia, Hoover, Marie L., DuChateau, Nadine, Flosi, Adam, Nelson, Rich, Stojanovic, Jelena, Wenner, Christine, Brown, Samuel M, Barkauskas, Christina E, Grund, Birgit, Sharma, Shweta, Phillips, Andrew N, Leither, Lindsay, Peltan, Ithan D, Lanspa, Michael, Gilstrap, Daniel L, Mourad, Ahmad, Lane, Kathleen, Beitler, Jeremy R, Serra, Alexis L, Garcia, Ivan, Almasri, Eyad, Fayed, Mohamed, Hubel, Kinsley, Harris, Estelle S, Middleton, Elizabeth A, Barrios, Macy A G, Mathews, Kusum S, Goel, Neha N, Acquah, Samuel, Mosier, Jarrod, Hypes, Cameron, Salvagio Campbell, Elizabeth, Khan, Akram, Hough, Catherine L, Wilson, Jennifer G, Levitt, Joseph E, Duggal, Abhijit, Dugar, Siddharth, Goodwin, Andrew J, Terry, Charles, Chen, Peter, Torbati, Sam, Iyer, Nithya, Sandkovsky, Uriel S, Johnson, Nicholas J, Robinson, Bryce R H, Matthay, Michael A, Aggarwal, Neil R, Douglas, Ivor S, Casey, Jonathan D, Hache-Marliere, Manuel, Georges Youssef, J, Nkemdirim, William, Leshnower, Brad, Awan, Omar, Pannu, Sonal, O'Mahony, Darragh Shane, Manian, Prasad, Awori Hayanga, J W, Wortmann, Glenn W, Tomazini, Bruno M, Miller, Robert F, Jensen, Jens-Ulrik, Murray, Daniel D, Bickell, Nina A, Zatakia, Jigna, Burris, Sarah, Higgs, Elizabeth S, Natarajan, Ven, Dewar, Robin L, Schechner, Adam, Kang, Nayon, Arenas-Pinto, Alejandro, Hudson, Fleur, Ginde, Adit A, Self, Wesley H, Rogers, Angela J, Oldmixon, Cathryn F, Morin, Haley, Sanchez, Adriana, Weintrob, Amy C, Cavalcanti, Alexandre Biasi, Davis-Karim, Anne, Engen, Nicole, Denning, Eileen, Taylor Thompson, B, Gelijns, Annetine C, Kan, Virginia, Davey, Victoria J, Lundgren, Jens D, Babiker, Abdel G, Neaton, James D, and Lane, H Clifford

Published
2023
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22. SAM-UNETR: Clinically Significant Prostate Cancer Segmentation Using Transfer Learning From Large Model

Author

Jesus Alejandro Alzate-Grisales, Alejandro Mora-Rubio, Francisco Garcia-Garcia, Reinel Tabares-Soto, and Maria De La Iglesia-Vaya

Subjects
Artificial intelligence, deep learning, prostate cancer, semantic segmentation, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Prostate cancer (PCa) is one of the leading causes of cancer-related mortality among men worldwide. Accurate and efficient segmentation of clinically significant prostate cancer (csPCa) regions from magnetic resonance imaging (MRI) plays a crucial role in diagnosis, treatment planning, and monitoring of the disease, however, this is a challenging task even for the specialized clinicians. This study presents SAM-UNETR, a novel model for segmenting csPCa regions from MRI images. SAM-UNETR combines a transformer-encoder from the Segment Anything Model (SAM), a versatile segmentation model trained on 11 million images, with a residual-convolution decoder inspired by UNETR. The model uses multiple image modalities and applies prostate zone segmentation, normalization, and data augmentation as preprocessing steps. The performance of SAM-UNETR is compared with three other models using the same strategy and preprocessing. The results show that SAM-UNETR achieves superior reliability and accuracy in csPCa segmentation, especially when using transfer learning for the image encoder. This demonstrates the adaptability of large-scale models for different tasks. SAM-UNETR attains a Dice Score of 0.467 and an AUROC of 0.77 for csPCa prediction.

Published
2023
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25. Green Energy HPC Data Centers to Improve Processing Cost Efficiency

Author

Lozoya Arandia, Jorge, Vega Gómez, Carlos Jesahel, Coronado, Alberto, Gonzalez Garcia, Jesus Alejandro, Robles Dueñas, Verónica Lizette, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Gitler, Isidoro, editor, Barrios Hernández, Carlos Jaime, editor, and Meneses, Esteban, editor

Published
2022
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26. Multi-subject Identification of Hand Movements Using Machine Learning

Author

Mora-Rubio, Alejandro, Alzate-Grisales, Jesus Alejandro, Arias-Garzón, Daniel, Buriticá, Jorge Iván Padilla, Varón, Cristian Felipe Jiménez, Bravo-Ortiz, Mario Alejandro, Arteaga-Arteaga, Harold Brayan, Hassaballah, Mahmoud, Orozco-Arias, Simon, Isaza, Gustavo, Tabares-Soto, Reinel, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Corchado, Juan M., editor, and Trabelsi, Saber, editor

Published
2022
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28. Comparative proteome analysis of the midgut of Rhipicephalus microplus (Acari: Ixodidae) strains with contrasting resistance to ivermectin reveals the activation of proteins involved in the detoxification metabolism

Author

Ruiz-May, Eliel, Álvarez-Sánchez, María Elizbeth, Aguilar-Tipacamú, Gabriela, Elizalde-Contreras, José M., Bojórquez-Velázquez, Esaú, Zamora-Briseño, Jesús Alejandro, Vázquez-Carrillo, Laura I., and López-Esparza, Areli

Published
2022
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29. Non-Linear Biomechanical Evaluation and Comparison in the Assessment of Three Different Piece Dental Implant Systems for the Molar Region: A Finite Element Study.

Author

Serrato-Pedrosa, Jesus Alejandro, Villanueva-Fierro, Ignacio, Marquet-Rivera, Rodrigo Arturo, Hernández-Vázquez, Rosa Alicia, Cruz-Lopez, Salvador, and Loera-Castañeda, Verónica

Subjects
DENTAL implants, FINITE element method, STRESS concentration, OPERATIVE surgery, TISSUES
Abstract

The widely available options of different manufacturers in dental implant systems have complicated the selection criteria process for periodontists, necessitating careful consideration of various factors when selecting suitable solutions for individual patient needs. Optimal implant selection requires careful consideration of the patient-specific factors, implant design, and surgical technique. Understanding the biomechanical behavior of implant–tissue interactions is crucial for achieving successful and long-lasting implant therapy. To adequately address this issue and improve the rigorous selection criteria from a biomechanically numerical approach, this research aims to analyze the stress distribution fields, strain patterns, and load transfer displacements within the implant system and the implant–biological interface (gingival and bony tissues) of titanium three-piece to two–one-piece ceramic implant systems. Thus, three different commercially available dental implants designed to be placed in the jaw molar region were considered for evaluation through the finite element method under both oblique and occlusal loading conditions. The results have exhibited an increasing trend to highlight the outstanding behavior of two-piece ceramic implants to dissipate the stress distribution better (6 and 2 times lower than the three- and one-piece systems under occlusal loads and almost 5 and 1.3 times more efficient for oblique loading, respectively), minimize peak stress values (below 100 MPa), and reduce strain peak patterns compared with the other two evaluated designs. On the other hand, the effects generated in biological tissues are strongly associated with implant geometry features. This biomechanical approach could provide a promising strategy for predicting micro-strains and micromotion in implant system pieces and geometries. Hence, these findings contribute to a deeper understanding of the biomechanics spectrum in the behavior of dental implant systems and emphasize the importance of carefully selecting appropriate material systems for accurate patient-specific biomechanical performance. [ABSTRACT FROM AUTHOR]

Published
2025
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30. Biomechanical Evaluation of Plantar Pressure Distribution towards a Customized 3D Orthotic Device: A Methodological Case Study through a Finite Element Analysis Approach

Author

Jesus Alejandro Serrato-Pedrosa, Guillermo Urriolagoitia-Sosa, Beatriz Romero-Ángeles, Guillermo Manuel Urriolagoitia-Calderón, Salvador Cruz-López, Alejandro Urriolagoitia-Luna, David Esaú Carbajal-López, Jonathan Rodolfo Guereca-Ibarra, and Guadalupe Murillo-Aleman

Subjects
plantar pressure, foot soft tissue, finite element analysis, medical imaging, 3D foot orthosis, orthotic devices, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

Plantar pressure distribution is a thoroughly recognized parameter for evaluating foot structure and biomechanical behavior, as it is utilized to determine musculoskeletal conditions and diagnose foot abnormalities. Experimental testing is currently being utilized to investigate static foot conditions using invasive and noninvasive techniques. These methods are usually expensive and laborious, and they lack valuable data since they only evaluate compressive forces, missing the complex stress combinations the foot undergoes while standing. The present investigation applied medical and engineering methods to predict pressure points in a healthy foot soft tissue during normal standing conditions. Thus, a well-defined three-dimensional foot biomodel was constructed to be numerically analyzed through medical imaging. Two study cases were developed through a structural finite element analysis. The first study was developed to evaluate barefoot behavior deformation and stresses occurring in the plantar region. The results from this analysis were validated through baropodometric testing. Subsequently, a customized 3D model total-contact foot orthosis was designed to redistribute peak pressures appropriately, relieving the plantar region from excessive stress. The results in the first study case successfully demonstrated the prediction of the foot sole regions more prone to suffer a pressure concentration since the values are in good agreement with experimental testing. Employing a customized insole proved to be highly advantageous in fulfilling its primary function, reducing peak pressure points substantially. The main aim of this paper was to provide more precise insights into the biomechanical behavior of foot pressure points through engineering methods oriented towards innovative assessment for absolute customization for orthotic devices.

Published
2024
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31. Integrative description of changes occurring on zebrafish embryos exposed to water-soluble crude oil components and its mixture with a chemical surfactant

Author

González-Penagos, Carlos Eduardo, Zamora-Briseño, Jesús Alejandro, Améndola-Pimenta, Monica, Elizalde-Contreras, José Miguel, Árcega-Cabrera, Flor, Cruz-Quintana, Yanis, Santana-Piñeros, Ana María, Cañizárez-Martínez, Mayra Alejandra, Pérez-Vega, Juan Antonio, Ruiz-May, Eliel, and Rodríguez-Canul, Rossanna

Published
2022
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33. A first glimpse into the transcriptomic changes induced by the PaV1 infection in the gut of Caribbean spiny lobsters, Panulirus argus (Latreille, 1804) (Decapoda: Achelata: Palinuridae)

Author

Hernández-Velázquez, Ioreni Margarita, Zamora-Briseño, Jesús Alejandro, Pereira-Santana, Alejandro, Huchin-Mian, Juan Pablo, González-Penagos, Carlos Eduardo, Pérez-Vega, Juan Antonio, Lozano-Álvarez, Enrique, Briones-Fourzán, Patricia, and Rodríguez-Canul, Rossanna

Published
2022
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37. Coffee Maturity Classification Using Convolutional Neural Networks and Transfer Learning

Author

Manuel Alejandro Tamayo-Monsalve, Esteban Mercado-Ruiz, Juan Pablo Villa-Pulgarin, Mario Alejandro Bravo-Ortiz, Harold Brayan Arteaga-Arteaga, Alejandro Mora-Rubio, Jesus Alejandro Alzate-Grisales, Daniel Arias-Garzon, Victor Romero-Cano, Simon Orozco-Arias, Gustavo Gustavo-Osorio, and Reinel Tabares-Soto

Subjects
Coffee maturity classification, convolutional neural network, data augmentation, deep learning, multispectral images, transfer learning, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

This work presents a framework for coffee maturity classification from multispectral image data based on Convolutional Neural Networks (CNNs). The system leverages the use of multispectral image acquisition systems that generate large amounts of data, by taking advantage of the ability of CNNs to extract meaningful patterns from very high-dimensional data. We validated the use of five different popular CNN architectures on the classification of cherry coffee fruits according to their ripening stage. The different models were trained on a training dataset balanced in different ways, which resulted in a top accuracy higher than 98% when applied to the classification of 600 coffee fruits in 5 different stages of ripening. This work has the potential of providing the farmer with a high-quality, optimized, accurate and viable method for classifying coffee fruits. In order to foster future research in this area, the data used in this work, which was acquired with a custom-developed multispectral image acquisition system, have been released.

Published
2022
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40. Deep Learning Applied to COVID-19 Detection in X-Ray Images

Author

Arteaga-Arteaga, Harold Brayan, primary, delaPava, Melissa, additional, Mora-Rubio, Alejandro, additional, Bravo-Ortíz, Mario Alejandro, additional, Alzate-Grisales, Jesus Alejandro, additional, Arias-Garzón, Daniel, additional, López-Murillo, Luis Humberto, additional, Buitrago-Carmona, Felipe, additional, Villa-Pulgarín, Juan Pablo, additional, Mercado-Ruiz, Esteban, additional, Martínez Rodríguez, Fernanda, additional, Palancares Sosa, Maria Jose, additional, Contreras-Ortiz, Sonia H., additional, Orozco-Arias, Simon, additional, Hassaballah, Mahmoud, additional, de la Iglesia Vayá, María, additional, Cardona-Morales, Oscar, additional, and Tabares-Soto, Reinel, additional

Published
2022
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43. Isolated High-Gain DC-DC Converter with Nanocrystalline-Core Transformer: Achieving 1:16 Voltage Boost for Renewable Energy Applications.

Author

Sandoval-Valencia, Tania, Ruiz-Robles, Dante, Ortíz-Marín, Jorge, Franco, Jesus Alejandro, Hernandez-Escobedo, Quetzalcoatl, and Moreno-Goytia, Edgar

Subjects
DC-to-DC converters, HIGH voltages, RENEWABLE energy sources, PHOTOVOLTAIC power systems, ENERGY consumption
Abstract

This paper presents an isolated DC-DC converter with high voltage gain that features an advanced inter-built nanocrystalline-core medium-frequency transformer (NC-MFT). The isolated DC-DC converter with an NC-MFT is specifically designed for applications such as interconnect photovoltaic (PV) systems, DC microgrids, DC loads, and DC buses, where voltage gain is one of the essential issues to consider. The NC-MFT inside the DC-DC converter is designed with a new approach that not only provides isolation but also contributes to achieving high efficiency and a higher step-up ratio. The high efficiency of the converters contributes to the integration of PV systems into DC microgrids. The converter yields a high voltage conversion ratio of 16.17. The experimental results obtained at 41.8 V/676 V and 275 W for the prototype revealed high efficiency (95.63% at full load). The experimental results validate the theoretical analysis and simulation, confirming that the converter achieves the main objective of high voltage conversion and high efficiency. These results will contribute to the interest in the use of this type of energy and its impact on the reduction in CO2 emissions. [ABSTRACT FROM AUTHOR]

Published
2024
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44. Maternal Supplementation with Lacticaseibacillus rhamnosus GG Improves Glucose Tolerance and Modulates the Intestinal Microbiota of Offspring.

Author

Correia Gomes, Dayane, Meza Alvarado, José Enrique, Zamora Briseño, Jesus Alejandro, Cano Sarmiento, Cynthia, Camacho Morales, Alberto, and Viveros Contreras, Rubi

Subjects
ORAL drug administration, GLUCOSE tolerance tests, HIGH-fat diet, GUT microbiome, FOOD consumption
Abstract

Introduction: Consuming hypercaloric diets during pregnancy induces metabolic, immune, and maternal intestinal dysbiosis disorders. These conditions are transferred to the offspring through the placenta and breastfeeding, increasing susceptibility to metabolic diseases. We investigated the effect of L. rhamnosus GG supplementation on offspring maternally programmed with a hypercaloric diet. Methods: Our study involved sixteen female Wistar rats aged ten weeks, which were divided into four groups based on their diets: control (Ctrl), cafeteria (CAF), control + probiotic (PRO), and cafeteria + probiotic (CPRO). The control + probiotic and cafeteria + probiotic groups received a daily oral administration of 250 μL of L. rhamnosus GG cell suspension (equivalent to 109 UFC) for nine weeks. The body weight of the animals was recorded weekly, and their food intake was monitored every 24 h. An oral glucose tolerance test was conducted on the offspring at seven weeks of age. At the ninth week of age, animals were euthanized, and blood, tissues, and organs were collected. Results: Maternal supplementation with L. rhamnosus GG decreased food intake and the average birth weight, improved glucose sensitivity, and lowered the levels of LDL, cholesterol, triglycerides, and mesenteric adipose tissue in offspring compared with the control and cafeteria groups. Conclusions: Our findings indicate that supplementing with LGG during maternal programming could protect offspring from metabolic disruptions caused by a hypercaloric maternal diet. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Protection of rotor side converter of doubly fed induction generator based wind energy conversion system under symmetrical grid voltage fluctuations.

Author

Sreenivasulu, Panisetty, Hussain, Jakeer, Piña, Jesus Alejandro Franco, Padala, Santosh Kumar Reddy, Ganjikunta, Siva Kumar, and P., Umapathi Reddy

Subjects
WIND energy conversion systems, INDUCTION generators, POWER resources, WIND turbines, VOLTAGE
Abstract

This paper presents the protection of the rotor side converter in a grid-connected doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) during a symmetrical voltage dip. In order to manage rotor current and regulate DC link voltage, an efficient active crowbar protection circuit is implemented in the rotor side converter (RSC). To improve the low-voltage ride-through capability for grid-connected wind turbine systems, an integrated DFIG-based WECS role is crucial because wind turbines must remain connected to the utility grid during faults to ensure continuity and reliability of power supply. This paper aims to design and implement an efficient active crowbar protection technique to protect the RSC and avoid excessive rotor current during a symmetrical voltage dip. Therefore, the efficient active crowbar protection circuit is designed using MATLAB-Simulink software, and its performance is validated using a real-time (RT) simulator. Finally, the existing methods are compared with the proposed work outcomes, and a conclusion is made. [ABSTRACT FROM AUTHOR]

Published
2024
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46. Comparative Proteomic Analysis of Wild and Cultivated Amaranth Species Seeds by 2-DE and ESI-MS/MS.

Author

Bojórquez-Velázquez, Esaú, Zamora-Briseño, Jesus Alejandro, Barrera-Pacheco, Alberto, Espitia-Rangel, Eduardo, Herrera-Estrella, Alfredo, and Barba de la Rosa, Ana Paulina

Subjects
SEED proteins, TWO-dimensional electrophoresis, POST-translational modification, CROP improvement, GEL electrophoresis
Abstract

Amaranth is a promising staple food that produces seeds with excellent nutritional quality. Although cultivated species intended for grain production have interesting agronomic traits, relatively little is known about wild species, which can prosper in diverse environments and could be a rich genetic source for crop improvement. This work focuses on the proteomic comparison between the seeds of wild and cultivated amaranth species using polarity-based protein extraction and two-dimensional gel electrophoresis. Differentially accumulated proteins (DAPs) showed changes in granule-bound starch synthases and a wide range of 11S globulin isoforms. The electrophoretic profile of these proteins suggests that they may contain significant phosphorylation as post-translational modifications (PTMs), which were confirmed via immunodetection. These PTMs may impact the physicochemical functionality of storage proteins, with potential implications for seed agronomic traits and food system applications. Low-abundant DAPs with highly variable accumulation patterns are also discussed; these were involved in diverse molecular processes, such as genic regulation, lipid storage, and stress response. [ABSTRACT FROM AUTHOR]

Published
2024
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47. Estructura genética y aptitud ambiental de poblaciones de pasto banderita [Bouteloua curtipendula (Michx.) Torr.] en Chihuahua, México

Author

Alan Álvarez-Holguín, Carlos Raúl Morales-Nieto, Raúl Corrales-Lerma, Jesus Alejandro Prieto-Amparán, Ireyli Zuluami Iracheta-Lara, and Nathalie Socorro Hernández-Quiroz

Subjects
AFLP, Nicho climático, MaxEnt, STRUCTURE, Animal culture, SF1-1100, Veterinary medicine, SF600-1100
Abstract

En los últimos años se han realizado diversos trabajos para seleccionar genotipos sobresalientes de pastos para restauración de pastizales. Estos trabajos se han enfocado principalmente en características agronómicas y poca importancia se ha dado a la estructura genética y adaptación ambiental de los genotipos. El objetivo fue evaluar la estructura genética y aptitud ambiental de poblaciones de pasto banderita en Chihuahua, México. Se evaluaron 51 poblaciones de pasto banderita (Bouteloua curtipendula) a través de marcadores AFLP y análisis de su estructura genética. La aptitud ambiental de los grupos genéticos que se conformaron se determinó mediante el diseño de modelos que utilizan el algoritmo de MaxEnt. Lo anterior, representa una manera novedosa de usar el algoritmo, ya que comúnmente solo se utilizada a nivel especie. El análisis STRUCTURE dividió las poblaciones de pasto banderita en dos grupos genéticos diferentes (AMOVA; P

Published
2022
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