Cell patterning in epithelia is critical for the establishment of tissue function during development. The organization of patterns in these tissues is mediated by the interpretation of signals operating across multiple length scales. How epithelial tissues coordinate changes in cell identity across these length scales to orchestrate cellular rearrangements and fate specification remains poorly understood. Here, we use human neural tube organoids as model systems to interrogate epithelial patterning principles that guide domain specification. In silico modeling of the patterning process by cellular automata, validated by in vitro experiments, reveal that the initial positions of floor plate cells, coupled with activator-inhibitor signaling interactions, deterministically dictate the patterning outcome according to a discretized Turing reaction-diffusion mechanism. This model predicts an enhancement of organoid patterning by modulating inhibitor levels. Receptor-ligand interaction analysis of scRNAseq data from multiple organoid domains reveals WNT-pathway ligands as the specific inhibitory agents, thereby allowing for the experimental validation of model predictions. These results demonstrate that neuroepithelia employ reaction-diffusion-based mechanisms during early embryonic human development to organize cellular identities and morphogen sources to achieve patterning. The wider implementation of such in vitro organoid models in combination with in-silico agent-based modeling coupled to receptor-ligand analysis of scRNAseq data opens avenues for a broader understanding of dynamic tissue patterning processes.

November 15, 1972 Negligence — Duty of care — Brick kiln — Workman exposed to dust — Dermatitis contracted — No washing facilities provided — Material increase in risk of contracting disease — Material contribution to contracting disease — Employers' liability.

Computer networks serve billions of users all over the world. Research in this field could be performed by building test beds in labs. However, this approach is very expensive, inflexible and hard to reconfigure. It is also difficult and sometimes impossible to replicate some scenarios with test beds. Network simulation on the other hand overcomes all these difficulties. Network simulation can be easily used to study and debug network protocols, understand their interaction and predict how network changes will affect performance. In this paper, we introduce the Event-Driven Network Architecture Simulator, EDNAS. EDNAS is a general-purpose, portable and scalable simulator. We discuss its architecture and implementation. We demonstrate and analyze the results EDNAS provides using various performance measures that are hard to obtain using analytical models. This makes EDNAS very appealing in the study of communication networks.