K. Jürgen

With the increase in the aging population, the global number of people with Alzheimer's disease (AD) progressively increased worldwide. The situation is aggravated by the fact that there is no the effective pharmacological therapy of AD. Photobiomodulation (PBM) is non-pharmacological approach that has shown very promising results in the therapy of AD in pilot clinical and animal studies. However, the mechanisms of therapeutic effects of PBM for AD are poorly understood. In this study on mice, we demonstrate that photodynamic effects of 5-aminolevulenic acid and laser 635 nm cause reduction of network of the meningeal lymphatic vessels (MLVs) leading to suppression of lymphatic removal of beta-amyloid (Aβ) from the right lateral ventricle and the hippocampus. Using the original protocol of PBM under electroencephalographic monitoring of wakefulness and sleep stages in non-anesthetized mice, we discover that the 7-day course of PBM during deep sleep vs. wakefulness provides better restoration of clearance of Aβ from the ventricular system of the brain and the hippocampus. Our results shed light on the mechanism of PBM and show the stimulating effects of PBM on the brain lymphatic drainage that promotes transport of Aβ via the lymphatic pathway. The effects of PBM on the brain lymphatics in sleeping brain open a new niche in the study of restorative functions of sleep as well as it is an important informative platform for the development of innovative smart sleep technologies for the therapy of AD.

In the last decade, there has been a growing body of literatures addressing the utilization of complex network methods for the characterization of dynamical systems based on time series, which has allowed addressing fundamental questions regarding the structural organization of nonlinear dynamics as well as the successful treatment of a variety of applications from a broad range of disciplines. In this report, we provide an in-depth review of three existing approaches of recurrence networks, visibility graphs and transition networks, covering their methodological foundations, interpretation and the recent developments. The overall aim of this report is to provide the Chinese readers with the future directions of time series network approaches and how the complex network approaches can be applied to their own field of real-world time series analysis.

Abstract Currently, no specific treatments are available for Alzheimer's disease (AD). Mild cognitive impairment (MCI), the preclinical stage of AD, has a high possibility of reversing symptoms through neural regulation. A state dynamics model for single brain regions was developed to simulate blood oxygen level‐dependent signals in a patient with early mild cognitive impairment. Subsequently, the analysis of functional connections was used to comprehensively consider multiple complex network centralities to locate the intervention targets, and a multiple brain region collaborative control scheme was designed. Finally, the reliability and effectiveness of the intervention were verified at the brain region and subnetwork levels. This technique provides a basis for future clinical diagnosis and treatment of AD and MCI.

ABSTRACT This article explores a novel design of a resilient interaction algorithm for multiagent systems (MAS) based on an event‐triggered mechanism, focusing on distributed optimization in the context of False Data Injection Attack (FDIA). A network‐level defense strategy is used based on a virtual system framework, where virtual state variables are introduced to ensure that the local estimate of each agent converges to the optimal solution of the distributed optimization problem, even under unknown FDIA. The article further introduces an event‐triggered strategy that significantly reduces communication overhead, and proper selection criteria are given for picking suitable event‐triggered parameters therein. It is proved that the proposed algorithm also avoids the Zeno behavior. Additionally, a distributed detection method is designed to accurately identify and isolate compromised links, thereby further enhancing the system's resilience. Two numerical simulations are conducted to illustrate the performance of the proposed algorithm, and it is demonstrated that the algorithm can also maintain effectiveness for networks with relatively large‐scale sizes.