Profiling single cancer cell metabolism via high-content SRS imaging with chemical sparsity.


Journal

Science advances
ISSN: 2375-2548
Titre abrégé: Sci Adv
Pays: United States
ID NLM: 101653440

Informations de publication

Date de publication:
18 08 2023
Historique:
medline: 18 8 2023
pubmed: 16 8 2023
entrez: 16 8 2023
Statut: ppublish

Résumé

Metabolic reprogramming in a subpopulation of cancer cells is a hallmark of tumor chemoresistance. However, single-cell metabolic profiling is difficult because of the lack of a method that can simultaneously detect multiple metabolites at the single-cell level. In this study, through hyperspectral stimulated Raman scattering (hSRS) imaging in the carbon-hydrogen (C-H) window and sparsity-driven hyperspectral image decomposition, we demonstrate a high-content hSRS (h

Identifiants

pubmed: 37585522
doi: 10.1126/sciadv.adg6061
pmc: PMC10431717
doi:

Substances chimiques

Fatty Acids 0
Hydrogen 7YNJ3PO35Z
Proteins 0
Carbon 7440-44-0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

eadg6061

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Auteurs

Yuying Tan (Y)

Biomedical Engineering, Boston University, Boston, MA 02155, USA.

Haonan Lin (H)

Biomedical Engineering, Boston University, Boston, MA 02155, USA.

Ji-Xin Cheng (JX)

Biomedical Engineering, Boston University, Boston, MA 02155, USA.
Electrical and Computer Engineering, Boston University, Boston, MA 02155, USA.
Photonics Center, Boston University, Boston, MA 02155, USA.

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