Developing effective drugs for Alzheimer’s disease (AD), the most common cause of dementia, has been difficult because of complicated pathogenesis. Here, we report an efficient, network-based drug-screening platform developed by integrating mathematical modeling and the pathological features of AD with human iPSC-derived cerebral organoids (iCOs), including CRISPR-Cas9-edited isogenic lines. We use 1300 organoids from 11 participants to build a high-content screening (HCS) system and test blood–brain barrier-permeable FDA-approved drugs. Our study provides a strategy for precision medicine through the convergence of mathematical modeling and a miniature pathological brain model using iCOs.

Summary The brain controls various cognitive functions in a robust and efficient way. What is the control architecture of brain networks that enables such robust and optimal control? Is this brain control architecture distinct from that of other complex networks? Here, we developed a framework to delineate a control architecture of a complex network that is compatible with the behavior of the network and applied the framework to structural brain networks and other complex networks. As a result, we revealed that the brain networks have a distributed and overlapping control architecture governed by a small number of control nodes, which may be responsible for the robust and efficient brain functions. Moreover, our artificial network evolution analysis showed that the distributed and overlapping control architecture of the brain network emerges when it evolves toward increasing both robustness and efficiency.

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Plasma density irregularities in low-latitude and midlatitude F regions are normally understood in terms of equatorial plasma bubbles (EPBs) and traveling ionospheric disturbances (TIDs), respectively. Referring to the ground-based observations, such as total electron content (TEC) maps and all-sky airglow images, EPBs and TIDs can be distinguished by their propagation directions or alignments (

 Deep fades observed in a GPS L1/L5 strong scintillation dataset have been characterized in terms of availability for GNSS navigation.  A stochastic model based on a Markov chain accurately generates realistic correlated fading processes of GNSS signals under scintillation. New Markov chain model confirms that use of dual-frequency GNSS signals significantly enhances aviation availability during scintillation.