Non-invasive classification of macrophage polarisation by 2P-FLIM and machine learning.

Neto, Nuno G B; O'Rourke, Sinead A; Zhang, Mimi; Fitzgerald, Hannah K; Dunne, Aisling; Monaghan, Michael G

Neto, Nuno G B; O'Rourke, Sinead A; Zhang, Mimi; Fitzgerald, Hannah K; Dunne, Aisling; Monaghan, Michael G.

Afiliação

Neto NGB; Department of Mechanical, Manufacturing and Biomedical Engineering, Trinity College Dublin, Dublin, Ireland.
O'Rourke SA; Trinity Centre for Biomedical Engineering, Trinity Biomedical Science Institute, Trinity College Dublin, Dublin, Ireland.
Zhang M; Department of Mechanical, Manufacturing and Biomedical Engineering, Trinity College Dublin, Dublin, Ireland.
Fitzgerald HK; Trinity Centre for Biomedical Engineering, Trinity Biomedical Science Institute, Trinity College Dublin, Dublin, Ireland.
Dunne A; School of Biochemistry & Immunology and School of Medicine, Trinity Biomedical Science Institute, Trinity College Dublin, Dublin, Ireland.
Monaghan MG; School of Computer Science and Statistics, Trinity College Dublin, Dublin, Ireland.

Elife ; 112022 10 18.

Article em En | MEDLINE | ID: mdl-36254592

Assuntos

Macrófagos; NAD; Carbonil Cianeto p-Trifluormetoxifenil Hidrazona; Humanos; Aprendizado de Máquina; Macrófagos/metabolismo; Microscopia de Fluorescência/métodos; NAD/metabolismo

Palavras-chave

FLIM; cell biology; cellular metabolism; human; immunology; inflammation; machine learning; macrophages; multiphoton

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Macrófagos / NAD Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Elife Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Irlanda

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