Abstract
The pre-clinical validation of cell therapies requires monitoring the biodistribution of transplanted cells in tissues of host organisms. Real-time detection of these cells in the circulatory system and identification of their aggregation state is a crucial piece of information, but necessitates deep penetration and fast imaging with high selectivity, subcellular resolution, and high throughput. In this study, multiphoton-based in-flow detection of human stem cells in whole, unfiltered blood is demonstrated in a microfluidic channel. The approach relies on a multiphoton microscope with diffractive scanning in the direction perpendicular to the flow via a rapidly wavelength-swept laser. Stem cells are labeled with metal oxide harmonic nanoparticles. Thanks to their strong and quasi-instantaneous second harmonic generation (SHG), an imaging rate in excess of 10 000 frames per second is achieved with pixel dwell times of 1 ns, a duration shorter than typical fluorescence lifetimes yet compatible with SHG. Through automated cell identification and segmentation, morphological features of each individual detected event are extracted and cell aggregates are distinguished from isolated cells. This combination of high-speed multiphoton microscopy and high-sensitivity SHG nanoparticle labeling in turbid media promises the detection of rare cells in the bloodstream for assessing novel cell-based therapies.
| Original language | English |
|---|---|
| Article number | 2401472 |
| Journal | Small |
| Volume | 20 |
| Issue number | 40 |
| Pages (from-to) | 2401472 |
| Number of pages | 12 |
| ISSN | 1613-6810 |
| DOIs | |
| Publication status | Published - 03.10.2024 |
Funding
All research groups gratefully acknowledge the funding from the European H2020\u2010ICT project FAIR CHARM (FAst InfraRed Coherent HARmonic Microscopy, http://www.faircharm.eu ). S.K. gratefully acknowledges his Juniorprofessorship with financial support by the state of Schleswig\u2013Holstein (Excellence chair program by the universities Kiel and Luebeck), and funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy \u2013 EXC 2167\u2010390884018. K.R. and L.D. were partially supported by a grant from the \u201CFonds Europ\u00E9en de D\u00E9veloppement R\u00E9gional\u201D (FEDER; N PL0003686). The authors acknowledge the support of the APEX platform of UMR703 PAnTher, Center of Excellence Nikon, member of IBiSA, NeurAtris infrastructure and Biogenouest, Nantes, France.
| Funders | Funder number |
|---|---|
| European H2020‐ICT project FAIR | |
| European H2020‐ICT project FAIR | |
| state of Schleswig–Holstein | |
| Deutsche Forschungsgemeinschaft | EXC 2167-390884018 |
| European Regional Development Fund | N PL0003686 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 9 Industry, Innovation, and Infrastructure
Research Areas and Centers
- Academic Focus: Biomedical Engineering
DFG Research Classification Scheme
- 2.22-32 Medical Physics, Biomedical Technology
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