A quantum thermometric sensing and analysis system using fluorescent nanodiamonds for the evaluation of living stem cell functions according to intracellular temperature.
Hiroshi YukawaMasazumi FujiwaraKaori KobayashiYuka KumonKazu MiyajiYushi NishimuraKeisuke OshimiYumi UmeharaYoshio TekiTakayuki IwasakiMutsuko HatanoHideki HashimotoYoshinobu BabaPublished in: Nanoscale advances (2020)
Intracellular thermometry techniques play an important role in elucidating the relationship between the intracellular temperature and stem cell functions. However, there have been few reports on thermometry techniques that can detect the intracellular temperature of cells during several days of incubation. In this study, we developed a novel quantum thermometric sensing and analysis system (QTAS) using fluorescent nanodiamonds (FNDs). FNDs could label adipose tissue-derived stem cells (ASCs) at high efficiency with 24 h of incubation, and no cytotoxicity was observed in ASCs labeled with less than 500 μg mL -1 of FNDs. The peak of FNDs was confirmed at approximately 2.87 GHz with the characteristic fluorescence spectra of NV centers that could be optically detected (optically detected magnetic resonance [ODMR]). The ODMR peak clearly shifted to the high-frequency side as the temperature decreased and gave a mean temperature dependence of -(77.6 ± 11.0) kHz °C -1 , thus the intracellular temperature of living ASCs during several days of culturing could be precisely measured using the QTAS. Moreover, the intracellular temperature was found to influence the production of growth factors and the degree of differentiation into adipocytes and osteocytes. These data suggest that the QTAS can be used to investigate the relationship between intracellular temperature and cellular functions.
Keyphrases
- stem cells
- high frequency
- adipose tissue
- magnetic resonance
- reactive oxygen species
- emergency department
- type diabetes
- magnetic resonance imaging
- molecular dynamics
- induced apoptosis
- signaling pathway
- cell death
- computed tomography
- bone marrow
- electronic health record
- skeletal muscle
- adverse drug
- deep learning
- positron emission tomography
- drug induced