Alzheimer's disease (AD) is a progressive neurodegenerative disease with the symptom of cognitive impairment. The deposition of amyloid β (Aβ) peptide is believed to be the primary cause to neuronal dystrophy and eventually dementia. Aβ is the proteolytic product from its precursor amyloid precursor protein (APP) by β- and γ- secretase. An optional cleavage by α-secretase happens inside the Aβ domain. ADAM17 is supposed to be the regulated α-secretase of APP. Enhanced activity of ADAM17 leads to the increasing secretion of neuroprotective soluble APP α fragment and reduction of Aβ generation, which may be benefit to the disease. ADAM17 is then considered the potential therapeutic target for AD. Microglia activation and neuroinflammation is another important event in AD pathogenesis. Interestingly, ADAM17 also participates in the cleavage of many other membrane-bound proteins, especially some inflammatory factors related to microglia activation. The facilitating role of ADAM17 in inflammation and further neuronal damage has also been illustrated. In results, the activation of ADAM17 as the solution to AD may be a tricky task. The comprehensive consideration and evaluation has to be carried out carefully before the final treatment. In the present review, the distinct role of ADAM17 in AD-related APP shedding and neuroinflammatory microglial activation will be carefully discussed.

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In inter-datacenter elastic optical networks, multi-controller deployment is adopted to improve the stability and scalability of the control plane. As the network scale increases, the traditional multi-controller deployment scheme ignores the dynamic characteristics of traffic, resulting in unbalanced load among multiple controllers. In response to this problem, the existing switch migration mechanism is proposed to achieve balanced distribution of control loads. However, most of the existing research work does not consider the additional cost of switch migration, and the load balancing performance of the controller is not significantly improved after switch migration. In this paper, we propose a cost-aware switch migration (CASM) strategy for controller load balancing. The proposed CASM strategy first measures the controller load through multiple performance indicators that affect the controller load, and then judges whether the controller is overloaded or underloaded based on the controller’s response time to the request message, thereby improving the load balancing performance of the controller. Additionally, when selecting the switch to be migrated, the CASM selects the optimal switch for migration based on minimizing the migration cost, thereby reducing the cost of switch migration. The performance evaluation shows that CASM significantly improves load balancing performance of controllers and reduces the migration cost compared to existing solutions.

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