Mitochondria are the key source of ATP that fuels cellular functions, and they are also central in cellular signaling, cell division and apoptosis. Dysfunction of mitochondria has been implicated in a wide range of diseases, including neurodegenerative and cardiac diseases, and various types of cancer. One of the key proteins that regulate mitochondrial function is the voltage-dependent anion channel 1 (VDAC1), the most abundant protein on the outer membrane of mitochondria. VDAC1 is the gatekeeper for the passages of metabolites, nucleotides, and ions; it plays a crucial role in regulating apoptosis due to its interaction with apoptotic and anti-apoptotic proteins, namely members of the Bcl-2 family of proteins and hexokinase. Therefore, regulation of VDAC1 is crucial not only for metabolic functions of mitochondria, but also for cell survival. In fact, multiple lines of evidence have confirmed the involvement of VDAC1 in several diseases. Consequently, modulation or dysregulation of VDAC1 function can potentially attenuate or exacerbate pathophysiological conditions. Understanding the role of VDAC1 in health and disease could lead to selective protection of cells in different tissues and diverse diseases. The purpose of this review is to discuss the role of VDAC1 in the pathogenesis of diseases and as a potentially effective target for therapeutic management of various pathologies.

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The ever-increasing mobile data demands have posed significant challenges in the current radio access networks, while the emerging computation-heavy Internet of things (IoT) applications with varied requirements demand more flexibility and resilience from the cloud/edge computing architecture. In this article, to address the issues, we propose a novel air-ground integrated mobile edge network (AGMEN), where UAVs are flexibly deployed and scheduled, and assist the communication, caching, and computing of the edge network. In specific, we present the detailed architecture of AGMEN, and investigate the benefits and application scenarios of drone-cells, and UAV-assisted edge caching and computing. Furthermore, the challenging issues in AGMEN are discussed, and potential research directions are highlighted.

In this paper, we propose a secure unmanned aerial vehicle (UAV) mobile edge computing (MEC) system where multiple ground users offload large computing tasks to a nearby legitimate UAV in the presence of multiple eavesdropping UAVs with imperfect locations. To enhance security, jamming signals are transmitted from both the full-duplex legitimate UAV and non-offloading ground users. For this system, we design a low-complexity iterative algorithm to maximize the minimum secrecy capacity subject to latency, minimum offloading and total power constraints. Specifically, we jointly optimize the UAV location, users' transmit power, UAV jamming power, offloading ratio, UAV computing capacity, and offloading user association. Numerical results show that our proposed algorithm significantly outperforms baseline strategies over a wide range of UAV selfinterference (SI) efficiencies, locations and packet sizes of ground users. Furthermore, we show that there exists a fundamental tradeoff between the security and latency of UAV-enabled MEC systems which depends on the UAV SI efficiency and total UAV power constraints.