Discrimination between the effects of pulsed electrical stimulation and electrochemically conditioned medium on human osteoblasts.

BACKGROUND: Electrical stimulation is used for enhanced bone fracture healing. Electrochemical processes occur during the electrical stimulation at the electrodes and influence cellular reactions. Our approach aimed to distinguish between electrochemical and electric field effects on osteoblast-like MG-63 cells. We applied 20 Hz biphasic pulses via platinum electrodes for 2 h. The electrical stimulation of the cell culture medium and subsequent application to cells was compared to directly stimulated cells. The electric field distribution was predicted using a digital twin. RESULTS: Cyclic voltammetry and electrochemical impedance spectroscopy revealed partial electrolysis at the electrodes, which was confirmed by increased concentrations of hydrogen peroxide in the medium. While both direct stimulation and AC-conditioned medium decreased cell adhesion and spreading, only the direct stimulation enhanced the intracellular calcium ions and reactive oxygen species. CONCLUSION: The electrochemical by-product hydrogen peroxide is not the main contributor to the cellular effects of electrical stimulation. However, undesired effects like decreased adhesion are mediated through electrochemical products in stimulated medium. Detailed characterisation and monitoring of the stimulation set up and electrochemical reactions are necessary to find safe electrical stimulation protocols.

Experimental and numerical methods to ensure comprehensible and replicable alternating current electrical stimulation experiments.

Electrical stimulation has received increasing attention for decades for its application in regenerative medicine. Applications range from bone growth stimulation over cartilage regeneration to deep brain stimulation. Despite all research efforts, translation into clinical use has not yet been achieved in all fields. Recent critical assessments have identified limited documentation and monitoring of preclinical in vitro and in vivo experiments as possible reasons hampering clinical translation. In this work, we present experimental and numerical methods to determine the crucial quantities of electrical stimulation such as the electric field or current density. Knowing the stimulation quantities contributes to comprehending the biological response to electrical stimulation and to finally developing a reliable dose-response curve. To demonstrate the methods, we consider a direct contact electrical stimulation experiment that stands representative for a broad class of stimulation experiments. Electrochemical effects are addressed and methods to integrate them into numerical simulations are evaluated. A focus is laid on affordable lab equipment and reproducible open-source software solutions. Finally, clear guidelines to ensure replicability of electrical stimulation experiments are formulated.

Correction: Lange et al. Performance of a Piezoelectric Energy Harvesting System for an Energy-Autonomous Instrumented Total Hip Replacement: Experimental and Numerical Evaluation. Materials 2021, 14, 5151.

The authors wish to make the following corrections to their paper [...].

Using a Digital Twin of an Electrical Stimulation Device to Monitor and Control the Electrical Stimulation of Cells in vitro.

Electrical stimulation for application in tissue engineering and regenerative medicine has received increasing attention in recent years. A variety of stimulation methods, waveforms and amplitudes have been studied. However, a clear choice of optimal stimulation parameters is still not available and is complicated by ambiguous reporting standards. In order to understand underlying cellular mechanisms affected by the electrical stimulation, the knowledge of the actual prevailing field strength or current density is required. Here, we present a comprehensive digital representation, a digital twin, of a basic electrical stimulation device for the electrical stimulation of cells in vitro. The effect of electrochemical processes at the electrode surface was experimentally characterised and integrated into a numerical model of the electrical stimulation. Uncertainty quantification techniques were used to identify the influence of model uncertainties on relevant observables. Different stimulation protocols were compared and it was assessed if the information contained in the monitored stimulation pulses could be related to the stimulation model. We found that our approach permits to model and simulate the recorded rectangular waveforms such that local electric field strengths become accessible. Moreover, we could predict stimulation voltages and currents reliably. This enabled us to define a controlled stimulation setting and to identify significant temperature changes of the cell culture in the monitored voltage data. Eventually, we give an outlook on how the presented methods can be applied in more complex situations such as the stimulation of hydrogels or tissue in vivo.

Performance of a Piezoelectric Energy Harvesting System for an Energy-Autonomous Instrumented Total Hip Replacement: Experimental and Numerical Evaluation.

Instrumented implants can improve the clinical outcome of total hip replacements (THRs). To overcome the drawbacks of external energy supply and batteries, energy harvesting is a promising approach to power energy-autonomous implants. Therefore, we recently presented a new piezoelectric-based energy harvesting concept for THRs. In this study, the performance of the proposed energy harvesting system was numerically and experimentally investigated. First, we numerically reproduced our previous results for the physiologically based loading situation in a simplified setup. Thereafter, this configuration was experimentally realised by the implantation of a functional model of the energy harvesting concept into an artificial bone segment. Additionally, the piezoelectric element alone was investigated to analyse the predictive power of the numerical model. We measured the generated voltage for a load profile for walking and calculated the power output. The maximum power for the directly loaded piezoelectric element and the functional model were 28.6 and 10.2 µW, respectively. Numerically, 72.7 µW was calculated. The curve progressions were qualitatively in good accordance with the numerical data. The deviations were explained by sensitivity analysis and model simplifications, e.g., material data or lower acting force levels by malalignment and differences between virtual and experimental implantation. The findings verify the feasibility of the proposed energy harvesting concept and form the basis for design optimisations with increased power output.