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Yang L, Chen H, Yang C, Hu Z, Jiang Z, Meng S, Liu R, Huang L, Yang K. Research progress on the regulatory mechanism of integrin-mediated mechanical stress in cells involved in bone metabolism. J Cell Mol Med 2024; 28:e18183. [PMID: 38506078 PMCID: PMC10951882 DOI: 10.1111/jcmm.18183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 01/14/2024] [Accepted: 02/04/2024] [Indexed: 03/21/2024] Open
Abstract
Mechanical stress is an internal force between various parts of an object that resists external factors and effects that cause an object to deform, and mechanical stress is essential for various tissues that are constantly subjected to mechanical loads to function normally. Integrins are a class of transmembrane heterodimeric glycoprotein receptors that are important target proteins for the action of mechanical stress stimuli on cells and can convert extracellular physical and mechanical signals into intracellular bioelectrical signals, thereby regulating osteogenesis and osteolysis. Integrins play a bidirectional regulatory role in bone metabolism. In this paper, relevant literature published in recent years is reviewed and summarized. The characteristics of integrins and mechanical stress are introduced, as well as the mechanisms underlying responses of integrin to mechanical stress stimulation. The paper focuses on integrin-mediated mechanical stress in different cells involved in bone metabolism and its associated signalling mechanisms. The purpose of this review is to provide a theoretical basis for the application of integrin-mediated mechanical stress to the field of bone tissue repair and regeneration.
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Affiliation(s)
- Li Yang
- Department of Periodontology, Hospital of StomatologyZunyi Medical UniversityZunyiChina
| | - Hong Chen
- Department of Periodontology, Hospital of StomatologyZunyi Medical UniversityZunyiChina
| | - Chanchan Yang
- Department of Periodontology, Hospital of StomatologyZunyi Medical UniversityZunyiChina
| | - Zhengqi Hu
- Department of Periodontology, Hospital of StomatologyZunyi Medical UniversityZunyiChina
| | - Zhiliang Jiang
- Department of Periodontology, Hospital of StomatologyZunyi Medical UniversityZunyiChina
| | - Shengzi Meng
- Department of Periodontology, Hospital of StomatologyZunyi Medical UniversityZunyiChina
| | | | - Lan Huang
- Department of Periodontology, Hospital of StomatologyZunyi Medical UniversityZunyiChina
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Andrés-San Román JA, Gordillo-Vázquez C, Franco-Barranco D, Morato L, Fernández-Espartero CH, Baonza G, Tagua A, Vicente-Munuera P, Palacios AM, Gavilán MP, Martín-Belmonte F, Annese V, Gómez-Gálvez P, Arganda-Carreras I, Escudero LM. CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia. CELL REPORTS METHODS 2023; 3:100597. [PMID: 37751739 PMCID: PMC10626192 DOI: 10.1016/j.crmeth.2023.100597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 07/19/2023] [Accepted: 08/31/2023] [Indexed: 09/28/2023]
Abstract
Decades of research have not yet fully explained the mechanisms of epithelial self-organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for understanding the assembly and function of whole tissues. Combining 3D epithelial imaging with advanced deep-learning segmentation methods is essential for enabling this high-content analysis. We introduce CartoCell, a deep-learning-based pipeline that uses small datasets to generate accurate labels for hundreds of whole 3D epithelial cysts. Our method detects the realistic morphology of epithelial cells and their contacts in the 3D structure of the tissue. CartoCell enables the quantification of geometric and packing features at the cellular level. Our single-cell cartography approach then maps the distribution of these features on 2D plots and 3D surface maps, revealing cell morphology patterns in epithelial cysts. Additionally, we show that CartoCell can be adapted to other types of epithelial tissues.
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Affiliation(s)
- Jesús A Andrés-San Román
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | - Carmen Gordillo-Vázquez
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | - Daniel Franco-Barranco
- Department of Computer Science and Artificial Intelligence, University of the Basque Country (UPV/EHU), 20018 San Sebastian, Spain; Donostia International Physics Center (DIPC), 20018 San Sebastian, Spain
| | - Laura Morato
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | - Cecilia H Fernández-Espartero
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | - Gabriel Baonza
- Program of Tissue and Organ Homeostasis, Centro de Biología Molecular Severo Ochoa, CSIC-UAM and Ramón & Cajal Health Research Institute (IRYCIS), Hospital Universitario Ramón y Cajal, 28034 Madrid, Spain
| | - Antonio Tagua
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | | | - Ana M Palacios
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | - María P Gavilán
- Centro Andaluz de Biología Molecular y Medicina Regenerativa (CABIMER), JA/CSIC/Universidad de Sevilla/Universidad Pablo de Olavide and Departamento de Citología e Histología Normal y Patológica, Facultad de Medicina, Universidad de Sevilla, 41009 Seville, Spain
| | - Fernando Martín-Belmonte
- Program of Tissue and Organ Homeostasis, Centro de Biología Molecular Severo Ochoa, CSIC-UAM and Ramón & Cajal Health Research Institute (IRYCIS), Hospital Universitario Ramón y Cajal, 28034 Madrid, Spain
| | - Valentina Annese
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain
| | - Pedro Gómez-Gálvez
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain; MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Francis Crick Avenue, Trumpington, Cambridge CB2 0QH, UK; Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3EG, UK.
| | - Ignacio Arganda-Carreras
- Department of Computer Science and Artificial Intelligence, University of the Basque Country (UPV/EHU), 20018 San Sebastian, Spain; Donostia International Physics Center (DIPC), 20018 San Sebastian, Spain; Ikerbasque, Basque Foundation for Science, 48009 Bilbao, Spain; Biofisika Institute, 48940 Leioa, Spain.
| | - Luis M Escudero
- Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla and Departamento de Biología Celular, Facultad de Biología, Universidad de Sevilla, 41013 Seville, Spain; Biomedical Network Research Centre on Neurodegenerative Diseases (CIBERNED), 28029 Madrid, Spain.
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