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.

A basic macroeconomic agent-based model for analyzing monetary regime shifts

In macroeconomics, an emerging discussion of alternative monetary systems addresses the dimensions of systemic risk in advanced financial systems. Monetary regime changes with the aim of achieving a more sustainable financial system have already been discussed in several European parliaments and were the subject of a referendum in Switzerland. However, their effectiveness and efficacy concerning macro-financial stability are not well-known. This paper defines the economic requirements for modeling the current monetary system and introduces the corresponding macroeconomic agent-based model (MABM) in a continuous-time stochastic agent-based simulation environment with a provenance model. This MABM aims to present a starting point for exploring and analyzing monetary reforms. In this context, the monetary system affects the lending potential of banks and might impact the dynamics of financial crises. MABMs are predestined to replicate emergent financial crisis dynamics, analyze institutional changes within a financial system, and thus measure macro-financial stability. The used simulation environment makes the model more accessible and facilitates exploring the impact of different hypotheses and mechanisms in a less complex way. Moreover, the model replicates a wide range of stylized economic facts, which validates it as an analysis tool to implement and compare monetary regime shifts.

PROVenance Patterns in Numerical Modelling and Finite Element Simulation Processes of Bio-electric Systems

The reproducibility of scientific results gains increasing attention. In the context of biomedical engineering, this applies to experimental studies of three different kinds: in-vivo, in-vitro, and in-silico. Numerical modelling and finite element simulation of bio-electric systems are intricate processes involving manifold steps. A typical example of this process is the electrical stimulation at alloplastic reconstruction plates of the mandible. During the bio-electric modelling and simulation process, diverse methods realised in various software tools are exploited. To comprehensibly render how the final model has been developed requires a thorough documentation. We exploit the W3C provenance model PROV to structure this process and to make it accessible for modellers and for automatic analyses. Different entity types, such as data, model, software, literature, assumptions, and mathematical equations are distinguished; roles of entities within an activity are revealed as well as the involved researchers. In addition, we identify five process patterns: 1) information extraction from the literature; 2) generation of a geometrical model which uses data as input; 3) composition of several geometrical or mathematical models into a combined model; 4) parameterisation, which augments the input model by additional properties; and, finally, 5) refinement, which uses a model in addition to an assumption and generates an enhanced model. By modelling provenance information of a typical bio-electric modelling and simulation process as well as identifying provenance patterns, we provide a first step towards a better documentation of academic investigations in that scientific field.

Multi-Level Modeling in Systems Biology by Discrete Event Approaches (Mehrebenen-Modellierung in der Systembiologie innerhalb diskret-ereignisbasierter Ansätze)

The creation of models for heterogeneous and complex cellular networks is a central goal of Systems Biology. When modeling a biological network, one may wish to account for certain aspects in detail, while a bird's eye perspective would seem more appropriate for other parts. Multi-level models combine such overview and detail representations. We illustrate multi-level modeling with gene regulation of the Tryptophan operon in E. coli. We review three discrete event modeling formalisms and discuss model design therein: DEVS, STATECHARTS, and stochastic π-CALCULUS. This introductory presentation already reveals some of their respective virtues and shortcomings.

2-DE profiling of GDNF overexpression-related proteome changes in differentiating ST14A rat progenitor cells

Targeted differentiation of neural progenitor cells (NPCs) is a challenge for treatment of neurodegenerative diseases by cell replacement therapy and cell signalling manipulation. Here, we applied a proteome profiling approach to the rat striatal progenitor model cell line ST14A in order to elucidate cellular differentiation processes. Native cells and cells transfected with the glial cell line-derived neurotrophic factor (GDNF) gene were investigated at the proliferative state and at seven time points up to 72 h after induction of differentiation. 2-DE combined with MALDI-MS was used to create a reference 2-DE-map of 652 spots of which 164 were identified and assigned to 155 unique proteins. For identification of protein expression changes during cell differentiation, spot patterns of triplicate gels were matched to the 2-DE-map. Besides proteins that display expression changes in native cells, we also noted 43 protein-spots that were differentially regulated by GDNF overexpression in more than four time points of the experiment. The expression patterns of putative differentiation markers such as annexin 5 (ANXA5), glucosidase II beta subunit (GLU2B), phosphatidylethanolamine-binding protein 1 (PEBP1), myosin regulatory light chain 2-A (MLRA), NASCENT polypeptide-associated complex alpha (NACA), elongation factor 2 (EF2), peroxiredoxin-1 (PRDX1) and proliferating cell nuclear antigen (PCNA) were verified by Western blotting. The results reflect the large rearrangements of the proteome during the differentiation process of NPCs and their strong modification by neurotrophic factors like GDNF.

2-DE proteome analysis of a proliferating and differentiating human neuronal stem cell line (ReNcell VM)

The proteome of a proliferating human stem cell line was analyzed and then utilized to detect stem cell differentiation-associated changes in the protein profile. The analysis was conducted with a stable human fetal midbrain stem cell line (ReNcell VM) that displays the properties of a neural stem cell. Therefore, acquisition of proteomic data should be representative of cultured human neural stem cells (hNSCs) in general. Here we present a 2-DE protein-map of this cell line with annotations of 402 spots representing 318 unique proteins identified by MS. The subsequent proteome profiling of differentiating cells of this stem cell line at days 0, 4 and 7 of differentiation revealed changes in the expression of 49 identified spots that could be annotated to 45 distinct proteins. This differentiation-associated expression pattern was validated by Western blot analysis for transgelin-2, proliferating cell nuclear antigen, as well as peroxiredoxin 1 and 4. The group of regulated proteins also included NudC, ubiquilin-1, STRAP, stress-70 protein, creatine kinase B, glial fibrillary acidic protein and vimentin. Our results reflect the large rearrangement of the proteome during the differentiation process of the stem cells to terminally differentiated neurons and offer the possibility for further characterization of specific targets driving the stem cell differentiation.