Chemogenetic Silencing of Differentiating Cortical Neurons Impairs Dendritic and Axonal Growth.

Electrical activity is considered a key driver for the neurochemical and morphological maturation of neurons and the formation of neuronal networks. Designer receptors exclusively activated by designer drugs (DREADDs) are tools for controlling neuronal activity at the single cell level by triggering specific G protein signaling. Our objective was to investigate if prolonged silencing of differentiating cortical neurons can influence dendritic and axonal maturation. The DREADD hM4Di couples to Gi/o signaling and evokes hyperpolarization via GIRK channels. HM4Di was biolistically transfected into neurons in organotypic slice cultures of rat visual cortex, and activated by clozapine-N-oxide (CNO) dissolved in H2O; controls expressed hM4Di, but were mock-stimulated with H2O. Neurons were analyzed after treatment for two postnatal time periods, DIV 5-10 and 10-20. We found that CNO treatment delays the maturation of apical dendrites of L2/3 pyramidal cells. Further, the number of collaterals arising from the main axon was significantly lower, as was the number of bouton terminaux along pyramidal cell and basket cell axons. The dendritic maturation of L5/6 pyramidal cells and of multipolar interneurons (basket cells and bitufted cells) was not altered by CNO treatment. Returning CNO-treated cultures to CNO-free medium for 7 days was sufficient to recover dendritic and axonal complexity. Our findings add to the view that activity is a key driver in particular of postnatal L2/3 pyramidal cell maturation. Our results further suggest that inhibitory G protein signaling may represent a factor balancing the strong driving force of neurotrophic factors, electrical activity and calcium signaling.

Structure-based knowledge acquisition from electronic lab notebooks for research data provenance documentation.

BACKGROUND: Electronic Laboratory Notebooks (ELNs) are used to document experiments and investigations in the wet-lab. Protocols in ELNs contain a detailed description of the conducted steps including the necessary information to understand the procedure and the raised research data as well as to reproduce the research investigation. The purpose of this study is to investigate whether such ELN protocols can be used to create semantic documentation of the provenance of research data by the use of ontologies and linked data methodologies. METHODS: Based on an ELN protocol of a biomedical wet-lab experiment, a retrospective provenance model of the raised research data describing the details of the experiment in a machine-interpretable way is manually engineered. Furthermore, an automated approach for knowledge acquisition from ELN protocols is derived from these results. This structure-based approach exploits the structure in the experiment's description such as headings, tables, and links, to translate the ELN protocol into a semantic knowledge representation. To satisfy the Findable, Accessible, Interoperable, and Reuseable (FAIR) guiding principles, a ready-to-publish bundle is created that contains the research data together with their semantic documentation. RESULTS: While the manual modelling efforts serve as proof of concept by employing one protocol, the automated structure-based approach demonstrates the potential generalisation with seven ELN protocols. For each of those protocols, a ready-to-publish bundle is created and, by employing the SPARQL query language, it is illustrated that questions about the processes and the obtained research data can be answered. CONCLUSIONS: The semantic documentation of research data obtained from the ELN protocols allows for the representation of the retrospective provenance of research data in a machine-interpretable way. Research Object Crate (RO-Crate) bundles including these models enable researchers to easily share the research data including the corresponding documentation, but also to search and relate the experiment to each other.

OSS-DBS: Open-source simulation platform for deep brain stimulation with a comprehensive automated modeling.

In this study, we propose a new open-source simulation platform that comprises computer-aided design and computer-aided engineering tools for highly automated evaluation of electric field distribution and neural activation during Deep Brain Stimulation (DBS). It will be shown how a Volume Conductor Model (VCM) is constructed and examined using Python-controlled algorithms for generation, discretization and adaptive mesh refinement of the computational domain, as well as for incorporation of heterogeneous and anisotropic properties of the tissue and allocation of neuron models. The utilization of the platform is facilitated by a collection of predefined input setups and quick visualization routines. The accuracy of a VCM, created and optimized by the platform, was estimated by comparison with a commercial software. The results demonstrate no significant deviation between the models in the electric potential distribution. A qualitative estimation of different physics for the VCM shows an agreement with previous computational studies. The proposed computational platform is suitable for an accurate estimation of electric fields during DBS in scientific modeling studies. In future, we intend to acquire SDA and EMA approval. Successful incorporation of open-source software, controlled by in-house developed algorithms, provides a highly automated solution. The platform allows for optimization and uncertainty quantification (UQ) studies, while employment of the open-source software facilitates accessibility and reproducibility of simulations.

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.

Requirements for Documenting Electrical Cell Stimulation Experiments for Replicability and Numerical Modeling∗.

Thorough documentation of biological experiments is necessary for their replicability. This becomes even more evident when individual steps of in vitro wet-lab experiments are to be incorporated into computer simulation models. In the highly interdisciplinary field of electrical stimulation of biological cells, not only biological but also physical aspects play a crucial role. Simulations may help to identify parameters that influence cells and thereby reveal new insights into mechanisms of the cell biological system. However, missing or misleading documentation of the electrical stimulation step within wet-lab experiments may lead to discrepancies between reported and simulated electrical quantities. In addition, this threatens the replicability of electrical stimulation experiments. Thus, we argue that a minimal set of information is needed to enable a translation of electrical stimulation experiments of biological cells into computer simulation experiments and to support replicability. This set includes detailed information about the electronic devices and components, their set-up as well as the applied stimulus and shall be integrated into an existing guideline for cell biological experiments. Ideally, the documentation should also contain measured properties of the cellular and experimental environment. Furthermore, a realization of our proposed documentation requirements within electronic lab notebooks may provide a crucial step toward a more seamless integration of wet-lab data into simulations. Based on two exemplary studies, we demonstrate the relevance of our claim.