Dysregulated neurite outgrowth and synapse formation underlie many psychiatric disorders, which are also manifested by wolfram syndrome (WS). Whether and how the causative gene WFS1 deficiency affects synapse formation remain elusive. By mirroring human brain development with cerebral organoids, WFS1-deficient cerebral organoids not only recapitulate the neuronal loss in WS patients, but also exhibit significantly impaired synapse formation and function associated with reduced astrocytes. WFS1 deficiency in neurons autonomously delays neuronal differentiation with altered expressions of genes associated with psychiatric disorders, and impairs neurite outgrowth and synapse formation with elevated cytosolic calcium. Intriguingly, WFS1 deficiency in astrocytes decreases the expression of glutamate transporter EAAT2 by NF-κB activation and induces excessive glutamate. When co-cultured with wildtype neurons, WFS1-deficient astrocytes lead to impaired neurite outgrowth and increased cytosolic calcium in neurons. Importantly, disrupted synapse formation and function in WFS1-deficient cerebral organoids and impaired neurite outgrowth affected by WFS1-deficient astrocytes are efficiently reversed with Riluzole treatment, by restoring EAAT2 expression in astrocytes. Furthermore, Riluzole rescues the depressive-like behavior in the forced swimming test and the impaired recognition and spatial memory in the novel object test and water maze test in Wfs1 conditional knockout mice. Altogether, our study provides novel insights into how WFS1 deficiency affects synapse formation and function, and offers a strategy to treat this disease.

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The emergence of power dispatching automation systems has greatly improved the efficiency of power industry operations and promoted the rapid development of the power industry. However, with the convergence and increase in power data flow, the data dispatching network and the main station dispatching automation system have encountered substantial pressure. Therefore, the method of online data resolution and rapid problem identification of dispatching automation systems has been widely investigated. In this paper, we perform a comprehensive review of automated dispatching of massive dispatching data from the perspective of intelligent identification, discuss unresolved research issues and outline future directions in this area. In particular, we divide intelligent identification over power big data into data acquisition and storage processes, anomaly detection and fault discrimination processes, and fault tracing for dispatching operations during communication. A detailed survey of the solutions to the challenges in intelligent identification over power big data is then presented. Moreover, opportunities and future directions are outlined.