Effect of laser photobiomodulation combined with hydroxyapatite nanoparticles on the osteogenic differentiation of mesenchymal stem cells using artificial intelligence: An in vitro study

Effect of laser photobiomodulation combined with hydroxyapatite nanoparticles on the osteogenic differentiation of mesenchymal stem cells using artificial intelligence: An in vitro study

To evaluate in vitro the effect of laser photobiomodulation (PBM) combined or not with 30-nm hydroxyapatite nanoparticles (HANp), on the osteogenic differentiation of human umbilical cord mesenchymal stem cells (hUC-MSCs) by morphometric analysis using artificial intelligence programs (TensorFlow an...

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Published in:PloS one Vol. 19; no. 11; p. e0313787
Main Authors: de Melo, Eloiza Leonardo, Miranda, Jéssica Meirinhos, Lima, Vanessa Bastos de Souza Rolim, Gaião, Wyndly Daniel Cardoso, Tostes, Braulio de Vilhena Amorim, Rodrigues, Claudio Gabriel, Bezerra da Silva, Márcia, Júnior, Severino Alves, Pontes Perger, Edson Luiz, Bispo, Mávio Eduardo Azevedo, de Martínez Gerbi, Marleny Elizabeth Márquez
Format: Journal Article
Language:English
Published: San Francisco Public Library of Science 14-11-2024
Public Library of Science (PLoS)
Subjects:
Alizarin
Analysis
Antibiotics
Antibodies
Artificial intelligence
Biological response modifiers
Biology and Life Sciences
Bone morphogenetic protein 2
Bone morphogenetic protein 7
Bones
Cell culture
Cell differentiation
Cell growth
Cell viability
Computer and Information Sciences
Confluence
Differentiation (biology)
Engineering and Technology
Ethylenediaminetetraacetic acid
Growth
Human error
Hydroxyapatite
Lasers
Machine learning
Medical research
Mesenchymal stem cells
Morphometry
Nanoparticles
Research and Analysis Methods
Stem cells
Tissue engineering
Umbilical cord
Brazil
United States > US
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Summary:To evaluate in vitro the effect of laser photobiomodulation (PBM) combined or not with 30-nm hydroxyapatite nanoparticles (HANp), on the osteogenic differentiation of human umbilical cord mesenchymal stem cells (hUC-MSCs) by morphometric analysis using artificial intelligence programs (TensorFlow and ArcGIS). UC-MSCs were isolated and cultured until 80% confluence was reached. The cells were then plated according to the following experimental groups: G1 -control (DMEM), G2 -BMP-2, G3 -BMP-7, G4 -PBM (660 nm, 10 mW, 2.5 J/cm.sup.2, spot size of 0.08 cm.sup.2 ), G5 -HANp, G6 -HANp + PBM, G7 -BMP-2 + PBM, and G8 -BMP-7 + PBM. The MTT assay was used to analyze cell viability at 24, 48 and 72 h. Osteogenic differentiation was assessed by Alizarin Red staining after 7, 14 and 21 days. For morphometric analysis, areas of osteogenic differentiation (pixel.sup.2) were delimited by machine learning using the TensorFlow and ArcGIS 10.8 programs. The results of the MTT assay showed high rates of cell viability and proliferation in all groups when compared to control. Morphometric analysis revealed a greater area of osteogenic differentiation in G5 (HANp = 142709,33±36573,39) and G6 (HANp + PBM = 125452,00±24226,95) at all time points evaluated. It is suggested that HANp, whether combined with PBM or not, may be a promising alternative to enhance the cellular viability and osteogenic differentiation of hUC-MSCs.
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Competing Interests: The authors have declared that no competing interests exist.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0313787