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Effects of Varied Stimulation Parameters on Adipose-Derived Stem Cell Response to Low-Level Electrical Fields

Authors :
National Institutes of Health (US)
Hlavac, Nora
Bousalis, Deanna
Ahmad, Raffae N.
Pallack, Emily
Vela, Angelique
Li, Yuan
Mobini, Sahba
Patrick, Erin E.
Schmidt, Christine E.
National Institutes of Health (US)
Hlavac, Nora
Bousalis, Deanna
Ahmad, Raffae N.
Pallack, Emily
Vela, Angelique
Li, Yuan
Mobini, Sahba
Patrick, Erin E.
Schmidt, Christine E.
Publication Year :
2021

Abstract

Exogenous electrical fields have been explored in regenerative medicine to increase cellular expression of pro-regenerative growth factors. Adipose-derived stem cells (ASCs) are attractive for regenerative applications, specifically for neural repair. Little is known about the relationship between low-level electrical stimulation (ES) and ASC regenerative potentiation. In this work, patterns of ASC expression and secretion of growth factors (i.e., secretome) were explored across a range of ES parameters. ASCs were stimulated with low-level stimulation (20 mV/mm) at varied pulse frequencies, durations, and with alternating versus direct current. Frequency and duration had the most significant effects on growth factor expression. While a range of stimulation frequencies (1, 20, 1000 Hz) applied intermittently (1 h × 3 days) induced upregulation of general wound healing factors, neural-specific factors were only increased at 1 Hz. Moreover, the most optimal expression of neural growth factors was achieved when ASCs were exposed to 1 Hz pulses continuously for 24 h. In evaluation of secretome, apparent inconsistencies were observed across biological replications. Nonetheless, ASC secretome (from 1 Hz, 24 h ES) caused significant increase in neurite extension compared to non-stimulated control. Overall, ASCs are sensitive to ES parameters at low field strengths, notably pulse frequency and stimulation duration.

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1333180283
Document Type :
Electronic Resource