ArticleMicromachines2025
Electrical Phenotyping of Aged Human Mesenchymal Stem Cells Using Dielectrophoresis.
Article in Micromachines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Electrophysiological analysis of mesenchymal stem cells post-cryopreservation highlights the need for a recovery period: implications for cell-based therapies.Stem cell research & therapy · 2025Article
- Label-Free Sorting of Human Mesenchymal Stem Cells Using Insulating Dielectrophoresis.Electrophoresis · 2025Article
- Immunophenotypic characterization and clinical relevance of passage number in umbilical cord mesenchymal stromal cells: A review.Cell transplantationReview
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Human mesenchymal stem cells (hMSCs) are widely used in regenerative medicine, but large-scale in vitro expansion alters their function, impacting proliferation and differentiation potential. Currently, a predictive marker to assess these changes is lacking. Here, we used dielectrophoresis (DEP) to characterize the electrical phenotype of hMSCs derived from bone marrow (BM), adipose tissue (AT), and umbilical cord (UC) as they aged in vitro from passage 4 (P4) to passage 9 (P9). The electrical phenotype was defined by the DEP spectra, membrane capacitance, and cytoplasm conductivity. Cell morphology and size, growth characteristics, adipogenic differentiation potential, and osteogenic differentiation potential were assessed alongside label-free biomarker membrane capacitance and cytoplasm conductivity. Differentiation was confirmed by histological staining and RT-qPCR. All hMSCs exhibited typical morphology, though cell size varied, with UC-hMSCs displaying the largest variability across all size metrics. Growth analysis revealed that UC-hMSCs proliferated the fastest. The electrical phenotype varied with cell source and in vitro age, with high passage hMSCs showing noticeable shifts in DEP spectra, membrane capacitance, and cytoplasm conductivity. Correlation analysis revealed that population doubling level (PDL) correlated with membrane capacitance and cytoplasm conductivity, indicating PDL as a more precise marker of in vitro aging than passage number. Additionally, we demonstrate that membrane capacitance correlates with the osteogenic marker COL1A1 and that cytoplasm conductivity correlates with the adipogenic markers ADIPOQ and FABP4, suggesting that DEP-derived electrical properties serve as label-free biomarkers of differentiation potential. While DEP has previously been applied to BM-hMSCs and AT-hMSCs, and more recently to UC-hMSCs, few studies have provided a direct comparison across all three sources or tracked changes across continuous expansion. These findings underscore the utility of DEP as a label-free approach for assessing hMSC aging and function, offering practical applications for optimizing stem cell expansion and stem cell banking in clinical settings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.