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This article was supported by the German Research Foundation (DFG) and the Open Access Publication Fund of Humboldt-Universität zu Berlin., Reaching population immunity against COVID-19 is proving difficult even in countries with high vaccination levels. Thus, it is critical to identify limits of control and effective measures against future outbreaks. The effects of nonpharmaceutical interventions (NPIs) and vaccination strategies are analyzed with a detailed community-specific agent-based model (ABM). The authors demonstrate that the threshold for population immunity is not a unique number, but depends on the vaccination strategy. Prioritizing highly interactive people diminishes the risk for an infection wave, while prioritizing the elderly minimizes fatalities when vaccinations are low. Control over COVID-19 outbreaks requires adaptive combination of NPIs and targeted vaccination, exemplified for Germany for January–September 2021. Bimodality emerges from the heterogeneity and stochasticity of community-specific human–human interactions and infection networks, which can render the effects of limited NPIs uncertain. The authors' simulation platform can process and analyze dynamic COVID-19 epidemiological situations in diverse communities worldwide to predict pathways to population immunity even with limited vaccination., Peer Reviewed

The study of plant-environment interactions is a multidisciplinary research field. With the emergence of quantitative large-scale and high-throughput techniques, amount and dimensionality of experimental data have strongly increased. Appropriate strategies for data storage, management, and evaluation are needed to make efficient use of experimental findings. Computational approaches of data mining are essential for deriving statistical trends and signatures contained in data matrices. Although, current biology is challenged by high data dimensionality in general, this is particularly true for plant biology. Plants as sessile organisms have to cope with environmental fluctuations. This typically results in strong dynamics of metabolite and protein concentrations which are often challenging to quantify. Summarizing experimental output results in complex data arrays, which need computational statistics and numerical methods for building quantitative models. Experimental findings need to be combined by computational models to gain a mechanistic understanding of plant metabolism. For this, bioinformatics and mathematics need to be combined with experimental setups in physiology, biochemistry, and molecular biology. This review presents and discusses concepts at the interface of experiment and computation, which are likely to shape current and future plant biology. Finally, this interface is discussed with regard to its capabilities and limitations to develop a quantitative model of plant-environment interactions., Peer Reviewed

Plants are constantly exposed to temperature fluctuations, which have direct effects on all cellular reactions because temperature influences reaction likelihood and speed. Chloroplasts are crucial to temperature acclimation responses of plants, due to their photosynthetic reactions whose products play a central role in plant metabolism. Consequently, chloroplasts serve as sensors of temperature changes and are simultaneously major targets of temperature acclimation. The core subunits of the complexes involved in the light reactions of photosynthesis are encoded in the chloroplast. As a result, it is assumed that temperature acclimation in plants requires regulatory responses in chloroplast gene expression and protein turnover. We conducted western blot experiments to assess changes in the accumulation of two photosynthetic complexes (PSII, and Cytb6f complex) and the ATP synthase in tobacco plants over two days of acclimation to low temperature. Surprisingly, the concentration of proteins within the chloroplast varied negligibly compared to controls. To explain this observation, we used a simplified Ordinary Differential Equation (ODE) model of transcription, translation, mRNA degradation and protein degradation to explain how the protein concentration can be kept constant. This model takes into account temperature effects on these processes. Through simulations of the ODE model, we show that mRNA and protein degradation are possible targets for control during temperature acclimation. Our model provides a basis for future directions in research and the analysis of future results., Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659, Humboldt-Universität zu Berlin (1034), Peer Reviewed

The phenomenon of adopting open source software development practices in a corporate environment is known by many names, one being inner source. The objective of this study is to investigate how an organization consisting of small development teams can benet from adopting inner source and assess the level of applicability. The research has been conducted as a case study at a software development company. Data collection was carried out through interviews and a series of focus group meetings, and then analyzed by mapping it to an available framework. The analysis shows that the organization possesses potential, and also identied a number of challenges and benets of special importance to the case company. To address these challenges, the case study synthesized the organizational and infrastructural needs of the organization in a requirements specication describing a technical infrastructure, also known as a software forge, with an adapted organizational context and work process.