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1,833 results on '"Azevedo, Ricardo A."'

1. Interactive Effects of Bacterial Consortia and Basal Nitrogen Fertilization on Initial Maize Growth: an Investigation Based on Physiological Parameters and 15N Isotopic Analysis

Author

Galindo, Fernando Shintate, Thiengo, Cassio Carlette, Pagliari, Paulo Humberto, Bernardes, João Victor Silva, dos Santos, Gustavo Duprat, Longato, Pedro Augusto Fedato, de Sousa Vilela, Lucila, Teixeira Filho, Marcelo Carvalho Minhoto, Azevedo, Ricardo Antunes, Gaziola, Salete Aparecida, and Lavres, José

Published
2024
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2. A horseshoe mixture model for Bayesian screening with an application to light sheet fluorescence microscopy in brain imaging

Author

Denti, Francesco, Azevedo, Ricardo, Lo, Chelsie, Wheeler, Damian G, Gandhi, Sunil P, Guindani, Michele, and Shahbaba, Babak

Subjects
Mathematical Sciences, Statistics, Econometrics, Statistics & Probability
Abstract

In this paper we focus on identifying differentially activated brain regions using a light sheet fluorescence microscopy—a recently developed technique for whole-brain imaging. Most existing statistical methods solve this problem by partitioning the brain regions into two classes: significantly and nonsignificantly activated. However, for the brain imaging problem at the center of our study, such binary grouping may provide overly simplistic discoveries by filtering out weak but important signals that are typically adulterated by the noise present in the data. To overcome this limitation, we introduce a new Bayesian approach that allows classifying the brain regions into several tiers with varying degrees of relevance. Our approach is based on a combination of shrinkage priors, widely used in regression and multiple hypothesis testing problems, and mixture models, commonly used in model-based clustering. In contrast to the existing regularizing prior distributions, which use either the spike-and-slab prior or continuous scale mixtures, our class of priors is based on a discrete mixture of continuous scale mixtures and devises a cluster shrinkage version of the horseshoe prior. As a result, our approach provides a more general setting for Bayesian sparse estimation, drastically reduces the number of shrinkage parameters needed, and creates a framework for sharing information across units of interest. We show that this approach leads to more biologically meaningful and interpretable results in our brain imaging problem, since it allows the discrimination between active and inactive regions, while at the same time ranking the discoveries into clusters representing tiers of similar importance.

Published
2023

6. Progress toward a universal biomedical data translator

Author

Fecho, Karamarie, Thessen, Anne E, Baranzini, Sergio E, Bizon, Chris, Hadlock, Jennifer J, Huang, Sui, Roper, Ryan T, Southall, Noel, Ta, Casey, Watkins, Paul B, Williams, Mark D, Xu, Hao, Byrd, William, Dančík, Vlado, Duby, Marc P, Dumontier, Michel, Glusman, Gustavo, Harris, Nomi L, Hinderer, Eugene W, Hyde, Greg, Johs, Adam, Su, Andrew I, Qin, Guangrong, Zhu, Qian, Dougherty, Jennifer, Huang, Conrad, Magis, Andrew, Smith, Brett, Celebi, Remzi, Chen, Zhehuan, Azevedo, Ricardo De Miranda, Emonet, Vincent, Lee, Jay, Weng, Chunhua, Yilmaz, Arif, Kim, Keum Joo, Santos, Eugene, Tonstad, Lucas, Veenhuis, Luke, Yakaboski, Chase, Acevedo, Liliana, Carrell, Steven, Deutsch, Eric, Glen, Amy, Hoffman, Andrew, Koslicki, David, Kvarfordt, Lindsey, Liu, Zheng, Liu, Shaopeng, Ma, Chunyu, Mendoza, Luis, Muluka, Arun Teja, Womack, Finn, Wood, Erica, Roach, Jared, Goel, Prateek, Weber, Rosina, Williams, Andrew, Gormley, Joseph, Zisk, Tom, Hanspers, Kristina, Hoatlin, Maureen, Pico, Alexander, Riutta, Anders, Callaghan, Jackson, Xu, Colleen, Ahalt, Stanley C, Balhoff, Jim, Edwards, Stephen, Haaland, Perry, Knowles, Michael, Krishnamurthy, Ashok, Mandal, Meisha, Peden, David B, Pfaff, Emily, Schurman, Shepherd, Shrivastava, Shalki, Yi, Hong, Reilly, Jason, Kanwar, Richa, Cox, Steven, Vaidya, Gaurav, Wang, Max, Alkanaq, Ahmed, Costanzo, Maria, Koesterer, Ryan, Flannick, Jason, Burtt, Noel, Kluge, Alexandria, Rubin, Irit, Strasser, Michael Michi, Chung, Lawrence, Kang, Jimin, Mantilla, Michelle, Muller, Sandrine, Persaud, Bria, Wei, Qi, Baumgartner, Andrew, Dai, Cheng, and Duvvuri, Venkata

Subjects
Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Biomedical Data Translator Consortium, Cardiorespiratory Medicine and Haematology, Oncology and Carcinogenesis, Other Medical and Health Sciences, General Clinical Medicine, Cardiovascular medicine and haematology, Pharmacology and pharmaceutical sciences
Abstract

Clinical, biomedical, and translational science has reached an inflection point in the breadth and diversity of available data and the potential impact of such data to improve human health and well-being. However, the data are often siloed, disorganized, and not broadly accessible due to discipline-specific differences in terminology and representation. To address these challenges, the Biomedical Data Translator Consortium has developed and tested a pilot knowledge graph-based "Translator" system capable of integrating existing biomedical data sets and "translating" those data into insights intended to augment human reasoning and accelerate translational science. Having demonstrated feasibility of the Translator system, the Translator program has since moved into development, and the Translator Consortium has made significant progress in the research, design, and implementation of an operational system. Herein, we describe the current system's architecture, performance, and quality of results. We apply Translator to several real-world use cases developed in collaboration with subject-matter experts. Finally, we discuss the scientific and technical features of Translator and compare those features to other state-of-the-art, biomedical graph-based question-answering systems.

Published
2022

7. Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science

Author

Unni, Deepak R, Moxon, Sierra AT, Bada, Michael, Brush, Matthew, Bruskiewich, Richard, Caufield, J Harry, Clemons, Paul A, Dancik, Vlado, Dumontier, Michel, Fecho, Karamarie, Glusman, Gustavo, Hadlock, Jennifer J, Harris, Nomi L, Joshi, Arpita, Putman, Tim, Qin, Guangrong, Ramsey, Stephen A, Shefchek, Kent A, Solbrig, Harold, Soman, Karthik, Thessen, Anne E, Haendel, Melissa A, Bizon, Chris, Mungall, Christopher J, Consortium, The Biomedical Data Translator, Acevedo, Liliana, Ahalt, Stanley C, Alden, John, Alkanaq, Ahmed, Amin, Nada, Avila, Ricardo, Balhoff, Jim, Baranzini, Sergio E, Baumgartner, Andrew, Baumgartner, William, Belhu, Basazin, Brandes, MacKenzie, Brandon, Namdi, Burtt, Noel, Byrd, William, Callaghan, Jackson, Cano, Marco Alvarado, Carrell, Steven, Celebi, Remzi, Champion, James, Chen, Zhehuan, Chen, Mei‐Jan, Chung, Lawrence, Cohen, Kevin, Conlin, Tom, Corkill, Dan, Costanzo, Maria, Cox, Steven, Crouse, Andrew, Crowder, Camerron, Crumbley, Mary E, Dai, Cheng, Dančík, Vlado, De Miranda Azevedo, Ricardo, Deutsch, Eric, Dougherty, Jennifer, Duby, Marc P, Duvvuri, Venkata, Edwards, Stephen, Emonet, Vincent, Fehrmann, Nathaniel, Flannick, Jason, Foksinska, Aleksandra M, Gardner, Vicki, Gatica, Edgar, Glen, Amy, Goel, Prateek, Gormley, Joseph, Greyber, Alon, Haaland, Perry, Hanspers, Kristina, He, Kaiwen, Henrickson, Jeff, Hinderer, Eugene W, Hoatlin, Maureen, Hoffman, Andrew, Huang, Sui, Huang, Conrad, Hubal, Robert, Huellas‐Bruskiewicz, Kenneth, Huls, Forest B, Hunter, Lawrence, Hyde, Greg, Issabekova, Tursynay, Jarrell, Matthew, Jenkins, Lindsay, Johs, Adam, Kang, Jimin, Kanwar, Richa, Kebede, Yaphet, Kim, Keum Joo, Kluge, Alexandria, Knowles, Michael, and Koesterer, Ryan

Subjects
Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Networking and Information Technology R&D (NITRD), Data Science, 2.6 Resources and infrastructure (aetiology), Aetiology, Generic health relevance, Knowledge, Pattern Recognition, Automated, Translational Science, Biomedical, Biomedical Data Translator Consortium, Cardiorespiratory Medicine and Haematology, Oncology and Carcinogenesis, Other Medical and Health Sciences, General Clinical Medicine, Cardiovascular medicine and haematology, Pharmacology and pharmaceutical sciences
Abstract

Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph-based data models elucidate the interconnectedness among core biomedical concepts, enable data structures to be easily updated, and support intuitive queries, visualizations, and inference algorithms. However, knowledge discovery across these "knowledge graphs" (KGs) has remained difficult. Data set heterogeneity and complexity; the proliferation of ad hoc data formats; poor compliance with guidelines on findability, accessibility, interoperability, and reusability; and, in particular, the lack of a universally accepted, open-access model for standardization across biomedical KGs has left the task of reconciling data sources to downstream consumers. Biolink Model is an open-source data model that can be used to formalize the relationships between data structures in translational science. It incorporates object-oriented classification and graph-oriented features. The core of the model is a set of hierarchical, interconnected classes (or categories) and relationships between them (or predicates) representing biomedical entities such as gene, disease, chemical, anatomic structure, and phenotype. The model provides class and edge attributes and associations that guide how entities should relate to one another. Here, we highlight the need for a standardized data model for KGs, describe Biolink Model, and compare it with other models. We demonstrate the utility of Biolink Model in various initiatives, including the Biomedical Data Translator Consortium and the Monarch Initiative, and show how it has supported easier integration and interoperability of biomedical KGs, bringing together knowledge from multiple sources and helping to realize the goals of translational science.

Published
2022

11. A Horseshoe mixture model for Bayesian screening with an application to light sheet fluorescence microscopy in brain imaging

Author

Denti, Francesco, Azevedo, Ricardo, Lo, Chelsie, Wheeler, Damian, Gandhi, Sunil P., Guindani, Michele, and Shahbaba, Babak

Subjects
Statistics - Methodology
Abstract

In this paper, we focus on identifying differentially activated brain regions using a light sheet fluorescence microscopy - a recently developed technique for whole-brain imaging. Most existing statistical methods solve this problem by partitioning the brain regions into two classes: significantly and non-significantly activated. However, for the brain imaging problem at the center of our study, such binary grouping may provide overly simplistic discoveries by filtering out weak but important signals, that are typically adulterated by the noise present in the data. To overcome this limitation, we introduce a new Bayesian approach that allows classifying the brain regions into several tiers with varying degrees of relevance. Our approach is based on a combination of shrinkage priors - widely used in regression and multiple hypothesis testing problems - and mixture models - commonly used in model-based clustering. In contrast to the existing regularizing prior distributions, which use either the spike-and-slab prior or continuous scale mixtures, our class of priors is based on a discrete mixture of continuous scale mixtures and devises a cluster-shrinkage version of the Horseshoe prior. As a result, our approach provides a more general setting for Bayesian sparse estimation, drastically reduces the number of shrinkage parameters needed, and creates a framework for sharing information across units of interest. We show that this approach leads to more biologically meaningful and interpretable results in our brain imaging problem, since it allows the discrimination between active and inactive regions, while at the same time ranking the discoveries into clusters representing tiers of similar importance.

Published
2021

15. Rostro-Caudal Specificity of Corticospinal Tract Projections in Mice.

Author

Steward, Oswald, Yee, Kelly M, Metcalfe, Mariajose, Willenberg, Rafer, Luo, Juan, Azevedo, Ricardo, Martin-Thompson, Jacob H, and Gandhi, Sunil P

Subjects
Neurosciences, Neurological, Animals, Axons, Hindlimb, Male, Mice, Inbred BALB C, Motor Cortex, Neurons, Pyramidal Tracts, Spinal Cord, biotinylated dextran amine, mouse, retro-AAV, sensorimotor cortex, spinal cord, Psychology, Cognitive Sciences, Experimental Psychology
Abstract

Rostro-caudal specificity of corticospinal tract (CST) projections from different areas of the cortex was assessed by retrograde labeling with fluorogold and retrograde transfection following retro-AAV/Cre injection into the spinal cord of tdT reporter mice. Injections at C5 led to retrograde labeling of neurons throughout forelimb area of the sensorimotor cortex and a region in the dorsolateral cortex near the barrel field (S2). Injections at L2 led to retrograde labeling of neurons in the posterior sensorimotor cortex (hindlimb area) but not the dorsolateral cortex. With injections of biotinylated dextran amine (BDA) into the main sensorimotor cortex (forelimb region), labeled axons terminated selectively at cervical levels. With BDA injections into caudal sensorimotor cortex (hindlimb region), labeled axons passed through cervical levels without sending collaterals into the gray matter and then elaborated terminal arbors at thoracic sacral levels. With BDA injections into the dorsolateral cortex near the barrel field, labeled axons terminated at high cervical levels. Axons from medial sensorimotor cortex terminated primarily in intermediate laminae and axons from lateral sensorimotor cortex terminated primarily in laminae III-V of the dorsal horn. One of the descending pathways seen in rats (the ventral CST) was not observed in most mice.

Published
2021

21. Proline Exogenously Supplied or Endogenously Overproduced Induces Different Nutritional, Metabolic, and Antioxidative Responses in Transgenic Tobacco Exposed to Cadmium

Author

Borgo, Lucélia, Rabêlo, Flávio Henrique Silveira, Budzinski, Ilara Gabriela Frasson, Cataldi, Thaís Regiani, Ramires, Thiago Gentil, Schaker, Patricia Dayane Carvalho, Ribas, Alessandra Ferreira, Labate, Carlos Alberto, Lavres, José, Cuypers, Ann, and Azevedo, Ricardo Antunes

Published
2022
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23. Imaging the dynamic recruitment of monocytes to the blood–brain barrier and specific brain regions during Toxoplasma gondii infection

Author

Schneider, Christine A, Velez, Dario X Figueroa, Azevedo, Ricardo, Hoover, Evelyn M, Tran, Cuong J, Lo, Chelsie, Vadpey, Omid, Gandhi, Sunil P, and Lodoen, Melissa B

Subjects
Veterinary Sciences, Agricultural, Veterinary and Food Sciences, Physical Sciences, Vaccine Related, Neurosciences, Emerging Infectious Diseases, Foodborne Illness, Infectious Diseases, Prevention, Infection, Animals, Antigens, Ly, Blood-Brain Barrier, Brain, CX3C Chemokine Receptor 1, Disease Models, Animal, Female, Male, Mice, Mice, Inbred C57BL, Monocytes, Receptors, CCR2, Toxoplasmosis, monocyte, Toxoplasma gondii, CNS infection, LPS, blood-brain barrier, blood–brain barrier
Abstract

Brain infection by the parasite Toxoplasma gondii in mice is thought to generate vulnerability to predation by mechanisms that remain elusive. Monocytes play a key role in host defense and inflammation and are critical for controlling T. gondii However, the dynamic and regional relationship between brain-infiltrating monocytes and parasites is unknown. We report the mobilization of inflammatory (CCR2+Ly6Chi) and patrolling (CX3CR1+Ly6Clo) monocytes into the blood and brain during T. gondii infection of C57BL/6J and CCR2RFP/+CX3CR1GFP/+ mice. Longitudinal analysis of mice using 2-photon intravital imaging of the brain through cranial windows revealed that CCR2-RFP monocytes were recruited to the blood-brain barrier (BBB) within 2 wk of T. gondii infection, exhibited distinct rolling and crawling behavior, and accumulated within the vessel lumen before entering the parenchyma. Optical clearing of intact T. gondii-infected brains using iDISCO+ and light-sheet microscopy enabled global 3D detection of monocytes. Clusters of T. gondii and individual monocytes across the brain were identified using an automated cell segmentation pipeline, and monocytes were found to be significantly correlated with sites of T. gondii clusters. Computational alignment of brains to the Allen annotated reference atlas [E. S. Lein et al., Nature 445:168-176 (2007)] indicated a consistent pattern of monocyte infiltration during T. gondii infection to the olfactory tubercle, in contrast to LPS treatment of mice, which resulted in a diffuse distribution of monocytes across multiple brain regions. These data provide insights into the dynamics of monocyte recruitment to the BBB and the highly regionalized localization of monocytes in the brain during T. gondii CNS infection.

Published
2019

24. FAIRshake: Toolkit to Evaluate the FAIRness of Research Digital Resources

Author

Clarke, Daniel JB, Wang, Lily, Jones, Alex, Wojciechowicz, Megan L, Torre, Denis, Jagodnik, Kathleen M, Jenkins, Sherry L, McQuilton, Peter, Flamholz, Zachary, Silverstein, Moshe C, Schilder, Brian M, Robasky, Kimberly, Castillo, Claris, Idaszak, Ray, Ahalt, Stanley C, Williams, Jason, Schurer, Stephan, Cooper, Daniel J, de Miranda Azevedo, Ricardo, Klenk, Juergen A, Haendel, Melissa A, Nedzel, Jared, Avillach, Paul, Shimoyama, Mary E, Harris, Rayna M, Gamble, Meredith, Poten, Rudy, Charbonneau, Amanda L, Larkin, Jennie, Brown, C Titus, Bonazzi, Vivien R, Dumontier, Michel J, Sansone, Susanna-Assunta, and Ma'ayan, Avi

Subjects
Generic health relevance, Health Resources, Humans, Information Dissemination, Internet, Online Systems, Biochemistry and Cell Biology
Abstract

As more digital resources are produced by the research community, it is becoming increasingly important to harmonize and organize them for synergistic utilization. The findable, accessible, interoperable, and reusable (FAIR) guiding principles have prompted many stakeholders to consider strategies for tackling this challenge. The FAIRshake toolkit was developed to enable the establishment of community-driven FAIR metrics and rubrics paired with manual and automated FAIR assessments. FAIR assessments are visualized as an insignia that can be embedded within digital-resources-hosting websites. Using FAIRshake, a variety of biomedical digital resources were manually and automatically evaluated for their level of FAIRness.

Published
2019

28. Synthesis and Characterization of Novel Silylated Sm3+ and Eu3+ Complexes Incorporated into Mesoporous and Dense Silica Nanoparticles

Author

Jorge, Juliana, primary, Silva, Jaqueline Rodrigues da, additional, Boldo, Diego, additional, Santos, Kristiane Fanti Del Pino, additional, Duarte, Adriana Pereira, additional, Castro, Gustavo Rocha de, additional, Azevedo, Ricardo Bentes de, additional, Prada, Ariadna Lafourcade, additional, Amado, Jesús Rafael Rodríguez, additional, Verelst, Marc, additional, and Martines, Marco Antonio Utrera, additional

Published
2024
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31. Development of a Chimeric Model to Study and Manipulate Human Microglia In Vivo

Author

Hasselmann, Jonathan, Coburn, Morgan A, England, Whitney, Figueroa Velez, Dario X, Kiani Shabestari, Sepideh, Tu, Christina H, McQuade, Amanda, Kolahdouzan, Mahshad, Echeverria, Karla, Claes, Christel, Nakayama, Taylor, Azevedo, Ricardo, Coufal, Nicole G, Han, Claudia Z, Cummings, Brian J, Davtyan, Hayk, Glass, Christopher K, Healy, Luke M, Gandhi, Sunil P, Spitale, Robert C, and Blurton-Jones, Mathew

Subjects
Genetics, Stem Cell Research, Neurosciences, 2.1 Biological and endogenous factors, Aetiology, Neurological, Alzheimer Disease, Amyloid beta-Peptides, Animals, Brain, Cell Differentiation, Disease Models, Animal, Gene Expression, Granulocyte-Macrophage Colony-Stimulating Factor, Hematopoietic Stem Cell Transplantation, Humans, Induced Pluripotent Stem Cells, Macrophage Colony-Stimulating Factor, Mice, Mice, Transgenic, Microglia, Plaque, Amyloid, Thrombopoietin, Transplantation Chimera, Alzheimer’s disease, TREM-2, beta-amyloid, chimera, hematopoietic, humanized, microglia, neurodegeneration, pluripotent, stem cells, Psychology, Cognitive Sciences, Neurology & Neurosurgery
Abstract

iPSC-derived microglia offer a powerful tool to study microglial homeostasis and disease-associated inflammatory responses. Yet, microglia are highly sensitive to their environment, exhibiting transcriptomic deficiencies when kept in isolation from the brain. Furthermore, species-specific genetic variations demonstrate that rodent microglia fail to fully recapitulate the human condition. To address this, we developed an approach to study human microglia within a surrogate brain environment. Transplantation of iPSC-derived hematopoietic-progenitors into the postnatal brain of humanized, immune-deficient mice results in context-dependent differentiation into microglia and other CNS macrophages, acquisition of an ex vivo human microglial gene signature, and responsiveness to both acute and chronic insults. Most notably, transplanted microglia exhibit robust transcriptional responses to Aβ-plaques that only partially overlap with that of murine microglia, revealing new, human-specific Aβ-responsive genes. We therefore have demonstrated that this chimeric model provides a powerful new system to examine the in vivo function of patient-derived and genetically modified microglia.

Published
2019

36. Detection of SARS-CoV-2 virus via dynamic light scattering using antibody-gold nanoparticle bioconjugates against viral spike protein

Author

Silva, Patricia Bento da, Silva, Jaqueline Rodrigues da, Rodrigues, Mosar Corrêa, Vieira, Julia Augusto, Andrade, Ikaro Alves de, Nagata, Tatsuya, Santos, Alexandre Silva, Silva, Sebastião William da, Rocha, Marcia Cristina Oliveira da, Báo, Sônia Nair, Moraes-Vieira, Pedro M., Proença-Modena, José, Angelim, Monara K.C., de Souza, Gabriela Fabiano, Muraro, Stefanie Primon, de Barros, André Luis Branco, de Souza Martins, Glêndara Aparecida, Ribeiro-Dias, Fátima, Machado, Giovanna, Fessel, Melissa Regina, Chudzinski-Tavassi, Ana Marisa, Ronconi, Célia Machado, Gonçalves, Debora, Curi, Rui, Oliveira, Osvaldo N., and Azevedo, Ricardo Bentes

Published
2022
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44. Don't forget the blogosphere.

Author

Heinen, Robin, Duffy, Meghan, Fox, Jeremy W., Heard, Stephen B., McGlynn, Terry, Ollerton, Jeff, Rillig, Matthias C., Saunders, Manu E., Millman, Carol A., and de Azevedo, Ricardo Antunes

Abstract

Communicating results and ideas to a wider audience has been an important, but challenging component of scientists working in an academic environment. Particularly in recent decades, various social media platforms have become increasingly important to facilitate this. In addition, many scientists have used blogging platforms to communicate and discuss their work. Although the online dynamics of science communication are continuously changing, blogging has been used in a remarkably stable form for several decades. For this work, we brought several ecology bloggers to reflect on blogging as a science communication medium. We argue that blogging can be a powerful way to present new ideas and discuss them with a wide audience. Although blogs are not the same as scientific articles, they often serve as the initial brainstorm session. Importantly, we argue that blogs are most effective when bloggers and readers actively engage in conversations. We believe that blogging will be here to stay in science communication because of its unique and independent form of outreach. [ABSTRACT FROM AUTHOR]

Published
2024
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48. Introdução

Author

Joanitti, Graziella Anselmo, primary, Morais, Paulo César de, additional, and Azevedo, Ricardo Bentes de, additional

Published
2022
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49. Desafios e perspectivas da editoria científica

Author

Rode, Sigmar de Mello, primary, Galleti, Silvia Regina, additional, Azevedo, Ricardo Antunes, additional, Trzesniak, Piotr, additional, Biojone, Mariana, additional, Fontes, Ilda, additional, Barata, Germana, additional, Junior, Rui Seabra Ferreira, additional, Gonçalves, Andréa Ferreira, additional, Shintaku, Milton, additional, Fleury, Heloisa Junqueira, additional, Fialho, Lia Machado Fiuza, additional, Montero, Edna Frasson de Souza, additional, Príncipe, Eloísa, additional, Pinto, Juliana Maria de Sousa, additional, Gonçalves, Andréa, additional, and Werlang, Elisabete, additional

Published
2022
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