• Restorative Dentistry and Endodontics
• /
• 제47권2호
• /
• pp.18.1-18.9
• /
• 2022

Objectives: This study evaluated alterations in neuronal conductivity related to calcium silicate cements (CSCs) by investigating compound action potentials (cAPs) in rat sciatic nerves. Materials and Methods: Sciatic nerves were placed in a Tyrode bath and cAPs were recorded before, during, and after the application of test materials for 60-minute control, application, and recovery measurements, respectively. Freshly prepared ProRoot MTA, MTA Angelus, Biodentine, Endosequence RRM-Putty, BioAggregate, and RetroMTA were directly applied onto the nerves. Biopac LabPro version 3.7 was used to record and analyze cAPs. The data were statistically analyzed. Results: None of the CSCs totally blocked cAPs. RetroMTA, Biodentine, and MTA Angelus caused no significant alteration in cAPs (p > 0.05). Significantly lower cAPs were observed in recovery measurements for BioAggregate than in the control condition (p < 0.05). ProRoot MTA significantly but transiently reduced cAPs in the application period compared to the control period (p < 0.05). Endosequence RRM-Putty significantly reduced cAPs. Conclusions: Various CSCs may alter cAPs to some extent, but none of the CSCs irreversibly blocked them. The usage of fast-setting CSCs during apexification or regeneration of immature teeth seems safer than slow-setting CSCs due to their more favorable neuronal effects.

• 한국진공학회:학술대회논문집
• /
• 한국진공학회 2013년도 제45회 하계 정기학술대회 초록집
• /
• pp.278.1-278.1
• /
• 2013

Among the prerequisites for stable neural interfacing are the long-term stability of electrical performance of and the excellent biocompatibility of conducting materials in implantable neural electrodes. Reduced graphene oxide offers a great potential for a variety of biomedical applications including biosensors and, particularly, neural interfaces due to its superb material properties such as high electrical conductivity, decent optical transparency, facile processibility, and etc. Nonetheless, there have been few systematic studies on the graphene-based neural interfaces in terms of biocompatibility of electrode materials and long term stability in electrical characteristics. In this research, we prepared the primary culture of rat hippocampal neurons directly on reduced graphene oxide films which is chosen as a model electrode material for the neural electrode. We observed that the viability of primary neuronal culture on the present structure is minimally affected by nanoscale graphene flakes below. These results implicate that the multilayer films of reduced graphene oxides can be utilized for the next-generation neural interfaces with decent biocompatibility and outstanding electrical performance.

• 대한의용생체공학회:의공학회지
• /
• 제30권1호
• /
• pp.10-17
• /
• 2009

Accurate electroencephalography (EEG) forward calculation is of importance for the accurate estimation of neuronal electrical sources. Conventional studies concerning the EEG forward problems have investigated various factors influencing the forward solution accuracy, e.g. tissue conductivity values in head compartments, anisotropic conductivity distribution of a head model, tessellation patterns of boundary element models, the number of elements used for boundary/finite element method (BEM/FEM), and so on. In the present paper, we investigated the influence of modeling errors in the boundary element volume conductor models upon the accuracy of the EEG forward solutions. From our simulation results, we could confirm that accurate construction of boundary element models is one of the key factors in obtaining accurate EEG forward solutions from BEM. Among three boundaries (scalp, outer skull, and inner skull boundary), the solution errors originated from the modeling error in the scalp boundary were most significant. We found that the nonuniform error distribution on the scalp surface is closely related to the electrode configuration and the error distributions on the outer and inner skull boundaries have statistically meaningful similarity to the curvature distributions of the boundary surfaces. Our simulation results also demonstrated that the accumulation of small modeling errors could lead to considerable errors in the EEG source localization. It is expected that our finding can be a useful reference in generating boundary element head models.