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Article ; Online: Biocomposite’s ecodevelopment from water hyacinth

Ricardo Gonzalez

Discern, Vol 3, Iss

2022 Volume 1

Abstract: This work starts from the context of an environmental crisis that frames a growing trend of a search for alternatives of a sustainable nature as a proposal solution from the transdisciplinary approach of design. The objective of this work consists of ... ...

Abstract	This work starts from the context of an environmental crisis that frames a growing trend of a search for alternatives of a sustainable nature as a proposal solution from the transdisciplinary approach of design. The objective of this work consists of planning an eco-development strategy to create biocomposite materials using water hyacinth (eicchornia crassipes) as raw material. The approach will be part of a collective research programme for future doctoral studies whose further objective is the sustainable integral community development of San Gregorio Atlapulco in Xochimilco, Mexico City. Theoretically, an approach is made from complex thinking and the sustainability paradigm, resulting in a vision of design as an integral sustainable activity, from the perspective of the formulation of new materials, appealing to movements like Material Activism, Ecodesign and Material Designers, in conjunction with a circular economy. Exploratory experimentation for bio bases and sustainable treatments for the water hyacinth fibre was conducted to establish the optimal formulations for the elaboration of biocomposites. From this, seven biocomposites with different properties were obtained that can be used with various low-impact processes for manufacturing sustainable design objects. By doing so, this stage ended with a prospective scenario that was proposed for further work with the community as the beginning of a social entrepreneurship initiative.
Keywords	biocomposites ; sustainability ; water hyacinth ; ecodevelopment ; Social sciences (General) ; H1-99 ; Drawing. Design. Illustration ; NC1-1940
Subject code	710
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	Art + Design: elearning lab - design for social change, Cyprus University of Technology
Document type	Article ; Online
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Article ; Online: ILC2s - development, divergence, dispersal.

Ricardo-Gonzalez, Roberto R / Molofsky, Ari B / Locksley, Richard M

Current opinion in immunology

2022 Volume 75, Page(s) 102168

Abstract: Over the last decade, we have come to appreciate group 2 innate lymphoid cells (ILC2s) as important players in host and tissue immunity. New studies of ILC2s and their precursors using novel reporter mice, advanced microscopy, and multi-omics approaches ... ...

Abstract	Over the last decade, we have come to appreciate group 2 innate lymphoid cells (ILC2s) as important players in host and tissue immunity. New studies of ILC2s and their precursors using novel reporter mice, advanced microscopy, and multi-omics approaches have expanded our knowledge on how these cells contribute to tissue physiology and function. This review highlights recent literature on this enigmatic cell, and we organize our discussion across three important paradigms in ILC2 biology: development, divergence, and dispersal. In addition, we frame our discussion in the context of other innate and adaptive immune cells to emphasize the relevance of expanding knowledge of ILC2s and tissue immunity.
MeSH term(s)	Animals ; Humans ; Immunity, Innate ; Lymphocytes ; Mice
Language	English
Publishing date	2022-02-14
Publishing country	England
Document type	Journal Article ; Review ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1035767-1
ISSN	1879-0372 ; 0952-7915
ISSN (online)	1879-0372
ISSN	0952-7915
DOI	10.1016/j.coi.2022.102168
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Article ; Online: Construcción de la Ciudadanía Ambiental

Diego Ricardo González Zevallos / María Isabel Márquez

Sociedad y Ambiente, Iss

El caso de la Asociación Vecinal Quintas El Mirador, Puerto Madryn, Argentina

2022 Volume 25

Abstract: Reconocer al ambiente como una responsabilidad en común y compartida implica transformarlo en un espacio de comunicación y ejercicio democrático, para lo cual se requiere de compromiso ciudadano. Las Asociaciones Vecinales son organizaciones que ... ...

Abstract	Reconocer al ambiente como una responsabilidad en común y compartida implica transformarlo en un espacio de comunicación y ejercicio democrático, para lo cual se requiere de compromiso ciudadano. Las Asociaciones Vecinales son organizaciones que representan un espacio de encuentro vecinal. El presente trabajo analiza una experiencia llevada a cabo por la Asociación Vecinal del Barrio Quintas El Mirador, en la ciudad de Puerto Madryn, durante los años 2016 a 2018. El propósito del estudio fue plantear un abordaje barrial a través de la construcción de la ciudadanía ambiental como una forma de experimentar la Educación Ambiental (EA). La metodología de trabajo fue de tipo mixta y se organizó en cuatro fases: diseño, implementación, evaluación y comunicación. Como resultado de la experiencia, se logró abordar el 74 % de las problemáticas mencionadas en una encuesta inicial, evidenciando la potencialidad de un barrio como escenario de construcción de la ciudadanía ambiental en un contexto de la EA. La originalidad de la propuesta fue el abordaje socioambiental a escala barrial, emprendido por una veintena de vecinas y vecinos en formato de proyecto ambiental. Los resultados obtenidos invitan a repetir la experiencia en otros barrios y contextos.
Keywords	Environmental sciences ; GE1-350
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	El Colegio de la Frontera Sur
Document type	Article ; Online
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Article ; Online: Sea anemones (Cnidaria, Anthozoa, Actiniaria) in high sedimentation environments influenced by the Magdalena River (Colombian Caribbean)

JEFERSON DURÁN-FUENTES / ADRIANA GRACIA / RICARDO GONZÁLEZ-MUÑOZ

Anais da Academia Brasileira de Ciências, Vol 94, Iss

2022 Volume 1

Abstract: Abstract Fifteen species of sea anemones (Cnidaria, Actiniaria) have been recorded so far in the Colombian Caribbean, comprising approximately 28% of the total number of known species in the Caribbean Sea. Most species recorded are associated with coral ... ...

Abstract	Abstract Fifteen species of sea anemones (Cnidaria, Actiniaria) have been recorded so far in the Colombian Caribbean, comprising approximately 28% of the total number of known species in the Caribbean Sea. Most species recorded are associated with coral reef communities. However, in the region, no records of sea anemones are known from areas with high sedimentation conditions as is characteristic along the coastline of the Atlántico Department, in Colombia. In this area, organisms are exposed to a high degree of turbidity and sedimentation (~143.9x106 t year-1) as a result of their proximity to the Magdalena River mouth and the 26 micro-basins that flow along its coastline. Several observations and collections were made on soft bottoms, rocky, and artificial substrates in the sectors of Puerto Velero and Caño Dulce to determine the fauna that exist under these conditions. Four species of sea anemones were found belonging to the families Actiniidae and Aiptasiidae, and images from living specimens and cnidae are provided. Bunodosoma cavernatum and Exaiptasia diaphana are here recorded for the first time from the Colombian Caribbean. An updated list of sea anemones in the Colombian Caribbean, now comprising 34 taxa (i.e., 21 species and 13 identified at supra-specific levels), is provided.
Keywords	Actiniidae ; Aiptasiidae ; benthic invertebrates ; colonization marginal ; environments ; turbidity ; Science ; Q
Subject code	590
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Academia Brasileira de Ciências
Document type	Article ; Online
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Article ; Online: Skin-Resident Innate Lymphoid Cells - Cutaneous Innate Guardians and Regulators.

Kobayashi, Tetsuro / Ricardo-Gonzalez, Roberto R / Moro, Kazuyo

Trends in immunology

2020 Volume 41, Issue 2, Page(s) 100–112

Abstract: Skin is the largest barrier organ and an important interface between the body and the outside environment. Immune surveillance and homeostatic regulation of skin function are governed by complex interactions between resident lymphoid and myeloid cells ... ...

Abstract	Skin is the largest barrier organ and an important interface between the body and the outside environment. Immune surveillance and homeostatic regulation of skin function are governed by complex interactions between resident lymphoid and myeloid cells and their communications with the surrounding parenchyma. Recent studies have provided exciting insights about the unique characteristics of skin-resident innate lymphoid cells (ILCs). Here, we discuss advances demonstrating how skin ILCs contribute to tissue homeostasis by regulating microbiome balance in steady-state and how their dysregulation can trigger and promote inflammatory skin diseases such as atopic dermatitis and psoriasis. We review the phenotypic and functional similarities and differences of ILCs between the skin and other organs and highlight future areas of investigation for this field.
MeSH term(s)	Dermatitis, Atopic/immunology ; Humans ; Immunity, Innate/immunology ; Lymphocytes/immunology ; Psoriasis/immunology ; Skin/cytology ; Skin/immunology
Language	English
Publishing date	2020-01-14
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	2036831-8
ISSN	1471-4981 ; 1471-4906
ISSN (online)	1471-4981
ISSN	1471-4906
DOI	10.1016/j.it.2019.12.004
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Article ; Online: Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models

Ricardo Gonzalez / Ashirbani Saha / Clinton J.V. Campbell / Peyman Nejat / Cynthia Lokker / Andrew P. Norgan

Journal of Pathology Informatics, Vol 15, Iss , Pp 100347- (2024)

Challenges and opportunities

1481

Abstract: This paper discusses some overlooked challenges faced when working with machine learning models for histopathology and presents a novel opportunity to support “Learning Health Systems” with them. Initially, the authors elaborate on these challenges after ...

Abstract	This paper discusses some overlooked challenges faced when working with machine learning models for histopathology and presents a novel opportunity to support “Learning Health Systems” with them. Initially, the authors elaborate on these challenges after separating them according to their mitigation strategies: those that need innovative approaches, time, or future technological capabilities and those that require a conceptual reappraisal from a critical perspective. Then, a novel opportunity to support ''Learning Health Systems'' by integrating hidden information extracted by ML models from digitalized histopathology slides with other healthcare big data is presented.
Keywords	Pathology ; Artificial intelligence ; Machine learning ; Learning health system ; Image processing ; Computer-assisted ; Computer applications to medicine. Medical informatics ; R858-859.7 ; RB1-214
Subject code	006
Language	English
Publishing date	2024-12-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
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Article ; Online: Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer

Ricardo Gonzalez / Peyman Nejat / Ashirbani Saha / Clinton J.V. Campbell / Andrew P. Norgan / Cynthia Lokker

Journal of Pathology Informatics, Vol 15, Iss , Pp 100348- (2024)

A systematic review

1481

Abstract: Numerous machine learning (ML) models have been developed for breast cancer using various types of data. Successful external validation (EV) of ML models is important evidence of their generalizability. The aim of this systematic review was to assess the ...

Abstract	Numerous machine learning (ML) models have been developed for breast cancer using various types of data. Successful external validation (EV) of ML models is important evidence of their generalizability. The aim of this systematic review was to assess the performance of externally validated ML models based on histopathology images for diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer. A systematic search of MEDLINE, EMBASE, CINAHL, IEEE, MICCAI, and SPIE conferences was performed for studies published between January 2010 and February 2022. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was employed, and the results were narratively described. Of the 2011 non-duplicated citations, 8 journal articles and 2 conference proceedings met inclusion criteria. Three studies externally validated ML models for diagnosis, 4 for classification, 2 for prognosis, and 1 for both classification and prognosis. Most studies used Convolutional Neural Networks and one used logistic regression algorithms. For diagnostic/classification models, the most common performance metrics reported in the EV were accuracy and area under the curve, which were greater than 87% and 90%, respectively, using pathologists' annotations/diagnoses as ground truth. The hazard ratios in the EV of prognostic ML models were between 1.7 (95% CI, 1.2–2.6) and 1.8 (95% CI, 1.3–2.7) to predict distant disease-free survival; 1.91 (95% CI, 1.11–3.29) for recurrence, and between 0.09 (95% CI, 0.01–0.70) and 0.65 (95% CI, 0.43–0.98) for overall survival, using clinical data as ground truth. Despite EV being an important step before the clinical application of a ML model, it hasn't been performed routinely. The large variability in the training/validation datasets, methods, performance metrics, and reported information limited the comparison of the models and the analysis of their results. Increasing the availability of validation datasets and implementing standardized methods and reporting protocols may ...
Keywords	Breast neoplasms ; Pathology ; Validation studies ; Machine learning ; Systematic review ; Computer applications to medicine. Medical informatics ; R858-859.7 ; RB1-214
Subject code	006
Language	English
Publishing date	2024-12-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
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Article ; Online: Generalization of vision pre-trained models for histopathology

Milad Sikaroudi / Maryam Hosseini / Ricardo Gonzalez / Shahryar Rahnamayan / H. R. Tizhoosh

Scientific Reports, Vol 13, Iss 1, Pp 1-

2023 Volume 14

Abstract: Abstract Out-of-distribution (OOD) generalization, especially for medical setups, is a key challenge in modern machine learning which has only recently received much attention. We investigate how different convolutional pre-trained models perform on OOD ... ...

Abstract	Abstract Out-of-distribution (OOD) generalization, especially for medical setups, is a key challenge in modern machine learning which has only recently received much attention. We investigate how different convolutional pre-trained models perform on OOD test data—that is data from domains that have not been seen during training—on histopathology repositories attributed to different trial sites. Different trial site repositories, pre-trained models, and image transformations are examined as specific aspects of pre-trained models. A comparison is also performed among models trained entirely from scratch (i.e., without pre-training) and models already pre-trained. The OOD performance of pre-trained models on natural images, i.e., (1) vanilla pre-trained ImageNet, (2) semi-supervised learning (SSL), and (3) semi-weakly-supervised learning (SWSL) models pre-trained on IG-1B-Targeted are examined in this study. In addition, the performance of a histopathology model (i.e., KimiaNet) trained on the most comprehensive histopathology dataset, i.e., TCGA, has also been studied. Although the performance of SSL and SWSL pre-trained models are conducive to better OOD performance in comparison to the vanilla ImageNet pre-trained model, the histopathology pre-trained model is still the best in overall. In terms of top-1 accuracy, we demonstrate that diversifying the images in the training using reasonable image transformations is effective to avoid learning shortcuts when the distribution shift is significant. In addition, XAI techniques—which aim to achieve high-quality human-understandable explanations of AI decisions—are leveraged for further investigations.
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: ILC2s chew the fat.

Ricardo-Gonzalez, Roberto R / Locksley, Richard M

The Journal of experimental medicine

2019 Volume 216, Issue 9, Page(s) 1972–1973

Abstract: In this issue ... ...

Abstract	In this issue of
MeSH term(s)	Adipose Tissue ; Diabetes Mellitus, Type 2 ; Humans ; Immunity, Innate ; Lymphocytes ; Stromal Cells
Language	English
Publishing date	2019-08-12
Publishing country	United States
Document type	Journal Article ; Comment
ZDB-ID	218343-2
ISSN	1540-9538 ; 0022-1007
ISSN (online)	1540-9538
ISSN	0022-1007
DOI	10.1084/jem.20191098
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Article ; Online: Regulatory T cells in skin mediate immune privilege of the hair follicle stem cell niche.

Cohen, Jarish N / Gouirand, Victoire / Macon, Courtney E / Lowe, Margaret M / Boothby, Ian C / Moreau, Joshua M / Gratz, Iris K / Stoecklinger, Angelika / Weaver, Casey T / Sharpe, Arlene H / Ricardo-Gonzalez, Roberto R / Rosenblum, Michael D

Science immunology

2024 Volume 9, Issue 91, Page(s) eadh0152

Abstract: Immune tolerance is maintained in lymphoid organs (LOs). Despite the presence of complex immune cell networks in non-LOs, it is unknown whether self-tolerance is maintained in these tissues. We developed a technique to restrict genetic recombination to ... ...

Abstract	Immune tolerance is maintained in lymphoid organs (LOs). Despite the presence of complex immune cell networks in non-LOs, it is unknown whether self-tolerance is maintained in these tissues. We developed a technique to restrict genetic recombination to regulatory T cells (T
MeSH term(s)	Humans ; Immune Privilege ; T-Lymphocytes, Regulatory ; Hair Follicle ; Interleukin-2 ; Stem Cell Niche
Chemical Substances	Interleukin-2
Language	English
Publishing date	2024-01-05
Publishing country	United States
Document type	Journal Article
ISSN	2470-9468
ISSN (online)	2470-9468
DOI	10.1126/sciimmunol.adh0152
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