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An Atlas of the Knee Joint Proteins and Their Role in Osteoarthritis Defined by Literature Mining

Osteoarthritis (OA) is the most prevalent rheumatic pathology. However, OA is not simply a process of wear and tear affecting articular cartilage but rather a disease of the entire joint. One of the most common locations of OA is the knee. Knee tissues have been studied using molecular strategies, g...

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Autores principales: Paz-González, Rocío, Lourido, Lucía, Calamia, Valentina, Fernández-Puente, Patricia, Quaranta, Patricia, Picchi, Florencia, Blanco, Francisco J., Ruiz-Romero, Cristina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Biochemistry and Molecular Biology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10393810/
https://www.ncbi.nlm.nih.gov/pubmed/37356495
http://dx.doi.org/10.1016/j.mcpro.2023.100606
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author Paz-González, Rocío
Lourido, Lucía
Calamia, Valentina
Fernández-Puente, Patricia
Quaranta, Patricia
Picchi, Florencia
Blanco, Francisco J.
Ruiz-Romero, Cristina
author_facet Paz-González, Rocío
Lourido, Lucía
Calamia, Valentina
Fernández-Puente, Patricia
Quaranta, Patricia
Picchi, Florencia
Blanco, Francisco J.
Ruiz-Romero, Cristina
author_sort Paz-González, Rocío
collection PubMed
description Osteoarthritis (OA) is the most prevalent rheumatic pathology. However, OA is not simply a process of wear and tear affecting articular cartilage but rather a disease of the entire joint. One of the most common locations of OA is the knee. Knee tissues have been studied using molecular strategies, generating a large amount of complex data. As one of the goals of the Rheumatic and Autoimmune Diseases initiative of the Human Proteome Project, we applied a text-mining strategy to publicly available literature to collect relevant information and generate a systematically organized overview of the proteins most closely related to the different knee components. To this end, the PubPular literature-mining software was employed to identify protein-topic relationships and extract the most frequently cited proteins associated with the different knee joint components and OA. The text-mining approach searched over eight million articles in PubMed up to November 2022. Proteins associated with the six most representative knee components (articular cartilage, subchondral bone, synovial membrane, synovial fluid, meniscus, and cruciate ligament) were retrieved and ranked by their relevance to the tissue and OA. Gene ontology analyses showed the biological functions of these proteins. This study provided a systematic and prioritized description of knee-component proteins most frequently cited as associated with OA. The study also explored the relationship of these proteins to OA and identified the processes most relevant to proper knee function and OA pathophysiology.
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spelling pubmed-103938102023-08-03 An Atlas of the Knee Joint Proteins and Their Role in Osteoarthritis Defined by Literature Mining Paz-González, Rocío Lourido, Lucía Calamia, Valentina Fernández-Puente, Patricia Quaranta, Patricia Picchi, Florencia Blanco, Francisco J. Ruiz-Romero, Cristina Mol Cell Proteomics Research Osteoarthritis (OA) is the most prevalent rheumatic pathology. However, OA is not simply a process of wear and tear affecting articular cartilage but rather a disease of the entire joint. One of the most common locations of OA is the knee. Knee tissues have been studied using molecular strategies, generating a large amount of complex data. As one of the goals of the Rheumatic and Autoimmune Diseases initiative of the Human Proteome Project, we applied a text-mining strategy to publicly available literature to collect relevant information and generate a systematically organized overview of the proteins most closely related to the different knee components. To this end, the PubPular literature-mining software was employed to identify protein-topic relationships and extract the most frequently cited proteins associated with the different knee joint components and OA. The text-mining approach searched over eight million articles in PubMed up to November 2022. Proteins associated with the six most representative knee components (articular cartilage, subchondral bone, synovial membrane, synovial fluid, meniscus, and cruciate ligament) were retrieved and ranked by their relevance to the tissue and OA. Gene ontology analyses showed the biological functions of these proteins. This study provided a systematic and prioritized description of knee-component proteins most frequently cited as associated with OA. The study also explored the relationship of these proteins to OA and identified the processes most relevant to proper knee function and OA pathophysiology. American Society for Biochemistry and Molecular Biology 2023-06-24 /pmc/articles/PMC10393810/ /pubmed/37356495 http://dx.doi.org/10.1016/j.mcpro.2023.100606 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research
Paz-González, Rocío
Lourido, Lucía
Calamia, Valentina
Fernández-Puente, Patricia
Quaranta, Patricia
Picchi, Florencia
Blanco, Francisco J.
Ruiz-Romero, Cristina
An Atlas of the Knee Joint Proteins and Their Role in Osteoarthritis Defined by Literature Mining
title An Atlas of the Knee Joint Proteins and Their Role in Osteoarthritis Defined by Literature Mining
title_full An Atlas of the Knee Joint Proteins and Their Role in Osteoarthritis Defined by Literature Mining
title_fullStr An Atlas of the Knee Joint Proteins and Their Role in Osteoarthritis Defined by Literature Mining
title_full_unstemmed An Atlas of the Knee Joint Proteins and Their Role in Osteoarthritis Defined by Literature Mining
title_short An Atlas of the Knee Joint Proteins and Their Role in Osteoarthritis Defined by Literature Mining
title_sort atlas of the knee joint proteins and their role in osteoarthritis defined by literature mining
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10393810/
https://www.ncbi.nlm.nih.gov/pubmed/37356495
http://dx.doi.org/10.1016/j.mcpro.2023.100606
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