TY - JOUR AB - The reaction-diffusion model constitutes one of the most influential mathematical models to study distribution of morphogens in tissues. Despite its widespread use, the effect of finite tissue size on model-predicted spatio-temporal morphogen distributions has not been completely elucidated. In this study, we analytically investigated the spatio-temporal distributions of morphogens predicted by a reaction-diffusion model in a finite one-dimensional domain, as a proxy for a biological tissue, and compared it with the solution of the infinite-domain model. We explored the reduced parameter, the tissue length in units of a characteristic reaction-diffusion length, and identified two reaction-diffusion regimes separated by a crossover tissue size estimated in approximately three characteristic reaction-diffusion lengths. While above this crossover the infinite-domain model constitutes a good approximation, it breaks below this crossover, whereas the finite-domain model faithfully describes the entire parameter space. We evaluated whether the infinite-domain model renders accurate estimations of diffusion coefficients when fitted to finite spatial profiles, a procedure typically followed in fluorescence recovery after photobleaching (FRAP) experiments. We found that the infinite-domain model overestimates diffusion coefficients when the domain is smaller than the crossover tissue size. Thus, the crossover tissue size may be instrumental in selecting the suitable reaction-diffusion model to study tissue morphogenesis. AU - Ceccarelli, A.S.* AU - Borges, A. AU - Chara, O.* C1 - 64208 C2 - 52109 CY - 6-9 Carlton House Terrace, London Sw1y 5ag, England TI - Size matters: Tissue size as a marker for a transition between reaction-diffusion regimes in spatio-temporal distribution of morphogens. JO - R. Soc. Open Sci. VL - 9 IS - 1 PB - Royal Soc PY - 2022 SN - 2054-5703 ER - TY - JOUR AB - Vaccination hesitancy is a major obstacle to achieving and maintaining herd immunity. Therefore, public health authorities need to understand the dynamics of an anti-vaccine opinion in the population. We introduce a spatially structured mathematical model of opinion dynamics with reinforcement. The model allows as an emergent property for the occurrence of echo chambers, i.e. opinion bubbles in which information that is incompatible with one's entrenched worldview, is probably disregarded. We scale the model both to a deterministic limit and to a weak-effects limit, and obtain bifurcations, phase transitions and the invariant measure. Fitting the model to measles and meningococci vaccination coverage across Germany, reveals that the emergence of echo chambers dynamics explains the occurrence and persistence of the anti-vaccination opinion in allowing anti-vaxxers to isolate and to ignore pro-vaccination facts. We predict and compare the effectiveness of different policies aimed at influencing opinion dynamics in order to increase vaccination uptake. According to our model, measures aiming at reducing the salience of partisan anti-vaccine information sources would have the largest effect on enhancing vaccination uptake. By contrast, measures aiming at reducing the reinforcement of vaccination deniers are predicted to have the smallest impact. AU - Müller, J. AU - Tellier, A.* AU - Kurschilgen, M.* C1 - 66524 C2 - 53201 CY - 6-9 Carlton House Terrace, London Sw1y 5ag, England TI - Echo chambers and opinion dynamics explain the occurrence of vaccination hesitancy. JO - R. Soc. Open Sci. VL - 9 IS - 10 PB - Royal Soc PY - 2022 SN - 2054-5703 ER - TY - JOUR AB - For a given research question, there are usually a large variety of possible analysis strategies acceptable according to the scientific standards of the field, and there are concerns that this multiplicity of analysis strategies plays an important role in the non-replicability of research findings. Here, we define a general framework on common sources of uncertainty arising in computational analyses that lead to this multiplicity, and apply this framework within an overview of approaches proposed across disciplines to address the issue. Armed with this framework, and a set of recommendations derived therefrom, researchers will be able to recognize strategies applicable to their field and use them to generate findings more likely to be replicated in future studies, ultimately improving the credibility of the scientific process. AU - Hoffmann, S.* AU - Schoenbrodt, F.* AU - Elsas, R.* AU - Wilson, R. AU - Strasser, U.* AU - Boulesteix, A.-L.* C1 - 61916 C2 - 50425 CY - 6-9 Carlton House Terrace, London Sw1y 5ag, England TI - The multiplicity of analysis strategies jeopardizes replicability: Lessons learned across disciplines. JO - R. Soc. Open Sci. VL - 8 IS - 4 PB - Royal Soc PY - 2021 SN - 2054-5703 ER - TY - JOUR AB - Astrocytes provide neurons with structural support and energy in form of lactate, modulate synaptic transmission, are insulin sensitive and act as gatekeeper for water, ions, glutamate and second messengers. Furthermore, astrocytes are important for glucose sensing, possess neuroendocrine functions and also play an important role in cerebral lipid metabolism. To answer the question, if there is a connection between lipid metabolism and insulin action in human astrocytes, we investigated if storage of ectopic lipids in human astrocytes has an impact on insulin signalling in those cells. Human astrocytes were cultured in the presence of a lipid emulsion, consisting of fatty acids and triglycerides, to induce ectopic lipid storage. After several days, cells were stimulated with insulin and gene expression profiling was performed. In addition, phosphorylation of Akt as well as glycogen synthesis and cell proliferation was assessed. Ectopic lipid storage was detected in human astrocytes after lipid exposure and lipid storage was persistent even when the fat emulsion was removed from the cell culture medium. Chronic exposure to lipids induced profound changes in the gene expression profile, whereby some genes showed a reversible gene expression profile upon removal of fat, and some did not. This included FOXO-dependent expression patterns. Furthermore, insulin-induced phosphorylation of Akt was diminished and also insulin-induced glycogen synthesis and proliferation was impaired in lipid-laden astrocytes. Chronic lipid exposure induces lipid storage in human astrocytes accompanied by insulin resistance. Analyses of the gene expression pattern indicated the potential of a partially reversible gene expression profile. Targeting astrocytic insulin resistance by reducing ectopic lipid load might represent a promising treatment target for insulin resistance of the brain in obesity, diabetes and neurodegeneration. AU - Heni, M. AU - Eckstein, S.S. AU - Schittenhelm, J.* AU - Böhm, A. AU - Hogrefe, N.* AU - Irmler, M. AU - Beckers, J. AU - Hrabě de Angelis, M. AU - Häring, H.-U. AU - Fritsche, A. AU - Staiger, H. C1 - 60057 C2 - 49093 CY - 6-9 Carlton House Terrace, London Sw1y 5ag, England TI - Ectopic fat accumulation in human astrocytes impairs insulin action. JO - R. Soc. Open Sci. VL - 7 IS - 9 PB - Royal Soc PY - 2020 SN - 2054-5703 ER - TY - JOUR AB - Modelling random dynamical systems in continuous time, diffusion processes are a powerful tool in many areas of science. Model parameters can be estimated from time-discretely observed processes using Markov chain Monte Carlo (MCMC) methods that introduce auxiliary data. These methods typically approximate the transition densities of the process numerically, both for calculating the posterior densities and proposing auxiliary data. Here, the Euler-Maruyama scheme is the standard approximation technique. However, the MCMC method is computationally expensive. Using higher-order approximations may accelerate it, but the specific implementation and benefit remain unclear. Hence, we investigate the utilization and usefulness of higher-order approximations in the example of the Milstein scheme. Our study demonstrates that the MCMC methods based on the Milstein approximation yield good estimation results. However, they are computationally more expensive and can be applied to multidimensional processes only with impractical restrictions. Moreover, the combination of the Milstein approximation and the well-known modified bridge proposal introduces additional numerical challenges. AU - Pieschner, S. AU - Fuchs, C. C1 - 60587 C2 - 49396 TI - Bayesian inference for diffusion processes: Using higher-order approximations for transition densities. JO - R. Soc. Open Sci. VL - 7 IS - 10 PY - 2020 SN - 2054-5703 ER -