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- ItemPhotobiomodulation of lymphatic drainage and clearance: Perspective strategy for augmentation of meningeal lymphatic functions(Washington, DC : Optica, 2020) Semyachkina-Glushkovskaya, Oxana; Abdurashitov, Arkady; Dubrovsky, Alexander; Klimova, Maria; Agranovich, Ilana; Terskov, Andrey; Shirokov, Alexander; Vinnik, Valeria; Kuzmina, Anna; Lezhnev, Nikita; Blokhina, Inna; Shnitenkova, Anastassia; Tuchin, Valery; Rafailov, Edik; Kurths, JurgenThere is a hypothesis that augmentation of the drainage and clearing function of the meningeal lymphatic vessels (MLVs) might be a promising therapeutic target for preventing neurological diseases. Here we investigate mechanisms of photobiomodulation (PBM, 1267 nm) of lymphatic drainage and clearance. Our results obtained at optical coherence tomography (OCT) give strong evidence that low PBM doses (5 and 10 J/cm2) stimulate drainage function of the lymphatic vessels via vasodilation (OCT data on the mesenteric lymphatics) and stimulation of lymphatic clearance (OCT data on clearance of gold nanorods from the brain) that was supported by confocal imaging of clearance of FITC-dextran from the cortex via MLVs. We assume that PBM-mediated relaxation of the lymphatic vessels can be possible mechanisms underlying increasing the permeability of the lymphatic endothelium that allows molecules transported by the lymphatic vessels and explain PBM stimulation of lymphatic drainage and clearance. These findings open new strategies for the stimulation of MLVs functions and non-pharmacological therapy of brain diseases.
- ItemPhotostimulation of extravasation of beta-amyloid through the model of blood-brain barrier(Basel : MDPI AG, 2020) Zinchenko, Ekaterina; Klimova, Maria; Mamedova, Aysel; Agranovich, Ilana; Blokhina, Inna; Antonova, Tatiana; Terskov, Andrey; Shirokov, Alexander; Navolokin, Nikita; Morgun, Andrey; Osipova, Elena; Boytsova, Elizaveta; Yu, Tingting; Zhu, Dan; Kurths, Juergen; Semyachkina-Glushkovskaya, OxanaAlzheimer’s disease (AD) is an incurable pathology associated with progressive decline in memory and cognition. Phototherapy might be a new promising and alternative strategy for the effective treatment of AD, and has been actively discussed over two decades. However, the mechanisms of therapeutic photostimulation (PS) effects on subjects with AD remain poorly understood. The goal of this study was to determine the mechanisms of therapeutic PS effects in beta-amyloid (Aβ)-injected mice. The neurological severity score and the new object recognition tests demonstrate that PS 9 J/cm2 attenuates the memory and neurological deficit in mice with AD. The immunohistochemical assay revealed a decrease in the level of Aβ in the brain and an increase of Aβ in the deep cervical lymph nodes obtained from mice with AD after PS. Using the in vitro model of the blood-brain barrier (BBB), we show a PS-mediated decrease in transendothelial resistance and in the expression of tight junction proteins as well an increase in the BBB permeability to Aβ. These findings suggest that a PS-mediated BBB opening and the activation of the lymphatic clearance of Aβ from the brain might be a crucial mechanism underlying therapeutic effects of PS in mice with AD. These pioneering data open new strategies in the development of non-pharmacological methods for therapy of AD and contribute to a better understanding of the PS effects on the central nervous system. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
- ItemExtending Transition Path Theory: Periodically Driven and Finite-Time Dynamics(New York, NY : Springer, 2020) Helfmann, Luzie; Ribera Borrell, Enric; Schütte, Christof; Koltai, PéterGiven two distinct subsets A, B in the state space of some dynamical system, transition path theory (TPT) was successfully used to describe the statistical behavior of transitions from A to B in the ergodic limit of the stationary system. We derive generalizations of TPT that remove the requirements of stationarity and of the ergodic limit and provide this powerful tool for the analysis of other dynamical scenarios: periodically forced dynamics and time-dependent finite-time systems. This is partially motivated by studying applications such as climate, ocean, and social dynamics. On simple model examples, we show how the new tools are able to deliver quantitative understanding about the statistical behavior of such systems. We also point out explicit cases where the more general dynamical regimes show different behaviors to their stationary counterparts, linking these tools directly to bifurcations in non-deterministic systems. © 2020, The Author(s).
- ItemHow to Optimize the Supply and Allocation of Medical Emergency Resources During Public Health Emergencies(Lausanne : Frontiers Media, 2020) Wang, Chunyu; Deng, Yue; Yuan, Ziheng; Zhang, Chijun; Zhang, Fan; Cai, Qing; Gao, Chao; Kurths, JürgenThe solutions to the supply and allocation of medical emergency resources during public health emergencies greatly affect the efficiency of epidemic prevention and control. Currently, the main problem in computational epidemiology is how the allocation scheme should be adjusted in accordance with epidemic trends to satisfy the needs of population coverage, epidemic propagation prevention, and the social allocation balance. More specifically, the metropolitan demand for medical emergency resources varies depending on different local epidemic situations. It is therefore difficult to satisfy all objectives at the same time in real applications. In this paper, a data-driven multi-objective optimization method, called as GA-PSO, is proposed to address such problem. It adopts the one-way crossover and mutation operations to modify the particle updating framework in order to escape the local optimum. Taking the megacity Shenzhen in China as an example, experiments show that GA-PSO effectively balances different objectives and generates a feasible allocation strategy. Such a strategy does not only support the decision-making process of the Shenzhen center in terms of disease control and prevention, but it also enables us to control the potential propagation of COVID-19 and other epidemics. © Copyright © 2020 Wang, Deng, Yuan, Zhang, Zhang, Cai, Gao and Kurths.
- ItemAuthor Correction: Estimating global mean sea-level rise and its uncertainties by 2100 and 2300 from an expert survey(London : Springer Nature, 2020) Horton, Benjamin P.; Khan, Nicole S.; Cahill, Niamh; Lee, Janice S. H.; Shaw, Timothy A.; Garner, Andra J.; Kem, Andrew C; Engelhart, Simon E.; Rahmstorf, StefanAn amendment to this paper has been published and can be accessed via a link at the top of the paper. © 2020, The Author(s).
- ItemEstimating global mean sea-level rise and its uncertainties by 2100 and 2300 from an expert survey(London : Springer Nature, 2020) Horton, Benjamin P.; Khan, Nicole S.; Cahill, Niamh; Lee, Janice S. H.; Shaw, Timothy A.; Garner, Andra J.; Kemp, Andrew C.; Engelhart, Simon E.; Rahmstorf, StefanSea-level rise projections and knowledge of their uncertainties are vital to make informed mitigation and adaptation decisions. To elicit projections from members of the scientific community regarding future global mean sea-level (GMSL) rise, we repeated a survey originally conducted five years ago. Under Representative Concentration Pathway (RCP) 2.6, 106 experts projected a likely (central 66% probability) GMSL rise of 0.30–0.65 m by 2100, and 0.54–2.15 m by 2300, relative to 1986–2005. Under RCP 8.5, the same experts projected a likely GMSL rise of 0.63–1.32 m by 2100, and 1.67–5.61 m by 2300. Expert projections for 2100 are similar to those from the original survey, although the projection for 2300 has extended tails and is higher than the original survey. Experts give a likelihood of 42% (original survey) and 45% (current survey) that under the high-emissions scenario GMSL rise will exceed the upper bound (0.98 m) of the likely range estimated by the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, which is considered to have an exceedance likelihood of 17%. Responses to open-ended questions suggest that the increases in upper-end estimates and uncertainties arose from recent influential studies about the impact of marine ice cliff instability on the meltwater contribution to GMSL rise from the Antarctic Ice Sheet. © 2020, The Author(s).
- ItemMonte Carlo basin bifurcation analysis([London] : IOP, 2020) Gelbrecht, Maximilian; Kurths, Jürgen; Hellmann, FrankMany high-dimensional complex systems exhibit an enormously complex landscape of possible asymptotic states. Here, we present a numerical approach geared towards analyzing such systems. It is situated between the classical analysis with macroscopic order parameters and a more thorough, detailed bifurcation analysis. With our machine learning method, based on random sampling and clustering methods, we are able to characterize the different asymptotic states or classes thereof and even their basins of attraction. In order to do this, suitable, easy to compute, statistics of trajectories with randomly generated initial conditions and parameters are clustered by an algorithm such as DBSCAN. Due to its modular and flexible nature, our method has a wide range of possible applications in many disciplines. While typical applications are oscillator networks, it is not limited only to ordinary differential equation systems, every complex system yielding trajectories, such as maps or agent-based models, can be analyzed, as we show by applying it the Dodds-Watts model, a generalized SIRS-model, modeling social and biological contagion. A second order Kuramoto model, used, e.g. to investigate power grid dynamics, and a Stuart-Landau oscillator network, each exhibiting a complex multistable regime, are shown as well. The method is available to use as a package for the Julia language. © 2020 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft.
- ItemEvolution mechanism of principal modes in climate dynamics([London] : IOP, 2020) Zhang, Yongwen; Fan, Jingfang; Li, Xiaoteng; Liu, Wenqi; Chen, XiaosongEigen analysis has been a powerful tool to distinguish multiple processes into different simple principal modes in complex systems. For a non-equilibrium system, the principal modes corresponding to the non-equilibrium processes are usually evolving with time. Here, we apply the eigen analysis into the complex climate systems. In particular, based on the daily surface air temperature in the tropics (30? S–30? N, 0? E–360? E) between 1979-01-01 and 2016-12-31, we uncover that the strength of two dominated intra-annual principal modes represented by the eigenvalues significantly changes with the El Niño/southern oscillation from year to year. Specifically, according to the ‘regional correlation’ introduced for the first intra-annual principal mode, we find that a sharp positive peak of the correlation between the El Niño region and the northern (southern) hemisphere usually signals the beginning (end) of the El Niño. We discuss the underlying physical mechanism and suppose that the evolution of the first intra-annual principal mode is related to the meridional circulations; the evolution of the second intra-annual principal mode responds positively to the Walker circulation. Our framework presented here not only facilitates the understanding of climate systems but also can potentially be used to study the dynamical evolution of other natural or engineering complex systems. © 2020 The Author(s).
- ItemA recurrent plot based stochastic nonlinear ray propagation model for underwater signal propagation([London] : IOP, 2020) Haiyang, Yao; Haiyan, Wang; Yong, Xu; Kurths, JuergenA stochastic nonlinear ray propagation model is proposed to carry out an exploration of the nonlinear ray theory in underwater signal propagation. The recurrence plot method is proposed to quantify the ray chaos and stochastics to optimize the model. Based on this method, the distribution function of the control parameter d is derived. Experiments and simulations indicate that this stochastic nonlinear ray propagation model provides a good explanation and description on the stochastic frequency shift in underwater signal propagation. © 2020 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft.
- ItemDynamical network size estimation from local observations([London] : IOP, 2020) Tang, Xiuchuan; Huo, Wei; Yuan, Ye; Li, Xiuting; Shi, Ling; Kurths, JürgenHere we present a method to estimate the total number of nodes of a network using locally observed response dynamics. The algorithm has the following advantages: (a) it is data-driven. Therefore it does not require any prior knowledge about the model; (b) it does not need to collect measurements from multiple stimulus; and (c) it is distributed as it uses local information only, without any prior information about the global network. Even if only a single node is measured, the exact network size can be correctly estimated using a single trajectory. The proposed algorithm has been applied to both linear and nonlinear networks in simulation, illustrating the applicability to real-world physical networks. © 2020 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft.