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Correlative Multi-Modal Microscopy: A Novel Pipeline for Optimizing Fluorescence Microscopy Resolutions in Biological Applications.
Pelicci, Simone; Furia, Laura; Pelicci, Pier Giuseppe; Faretta, Mario.
Afiliação
  • Pelicci S; Department of Experimental Oncology, European Institute of Oncology IRCCS, 20139 Milan, Italy.
  • Furia L; Department of Experimental Oncology, European Institute of Oncology IRCCS, 20139 Milan, Italy.
  • Pelicci PG; Department of Experimental Oncology, European Institute of Oncology IRCCS, 20139 Milan, Italy.
  • Faretta M; Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy.
Cells ; 12(3)2023 01 17.
Article em En | MEDLINE | ID: mdl-36766696
ABSTRACT
The modern fluorescence microscope is the convergence point of technologies with different performances in terms of statistical sampling, number of simultaneously analyzed signals, and spatial resolution. However, the best results are usually obtained by maximizing only one of these parameters and finding a compromise for the others, a limitation that can become particularly significant when applied to cell biology and that can reduce the spreading of novel optical microscopy tools among research laboratories. Super resolution microscopy and, in particular, molecular localization-based approaches provide a spatial resolution and a molecular localization precision able to explore the scale of macromolecular complexes in situ. However, its use is limited to restricted regions, and consequently few cells, and frequently no more than one or two parameters. Correlative microscopy, obtained by the fusion of different optical technologies, can consequently surpass this barrier by merging results from different spatial scales. We discuss here the use of an acquisition and analysis correlative microscopy pipeline to obtain high statistical sampling, high content, and maximum spatial resolution by combining widefield, confocal, and molecular localization microscopy.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article