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Water dynamics in MCF-7 breast cancer cells: a neutron scattering descriptive study.

Murillo L MartinsAlexander B DinitzenEugene MamontovSvemir RudićJosé E M PereiraRasmus Hartmann-PetersenKenneth W HerwigHeloísa Nunes Bordallo
Published in: Scientific reports (2019)
Water mobility in cancer cells could be a powerful parameter to predict the progression or remission of tumors. In the present descriptive work, new insight into this concept was achieved by combining neutron scattering and thermal analyses. The results provide the first step to untangle the role played by water dynamics in breast cancer cells (MCF-7) after treatment with a chemotherapy drug. By thermal analyses, the cells were probed as micrometric reservoirs of bulk-like and confined water populations. Under this perspective we showed that the drug clearly alters the properties of the confined water. We have independently validated this idea by accessing the cellular water dynamics using inelastic neutron scattering. Finally, analysis of the quasi-elastic neutron scattering data allows us to hypothesize that, in this particular cell line, diffusion increases in the intracellular water in response to the action of the drug on the nanosecond timescale.
Keyphrases
  • breast cancer cells
  • machine learning
  • cross sectional
  • cell death
  • deep learning
  • artificial intelligence