No abstract

Down syndrome (DS), or trisomy 21, is one of the critical risk factors for early-onset Alzheimer’s disease (AD), implicating key roles for chromosome 21–encoded genes in the pathogenesis of AD. We previously identified a role for the deubiquitinase USP25, encoded on chromosome 21, in regulating microglial homeostasis in the AD brain; however, whether USP25 affects amyloid pathology remains unknown. Here, by crossing 5×FAD AD and Dp16 DS mice, we observed that trisomy 21 exacerbated amyloid pathology in the 5×FAD brain. Moreover, bacterial artificial chromosome (BAC) transgene–mediated USP25 overexpression increased amyloid deposition in the 5×FAD mouse brain, whereas genetic deletion of Usp25 reduced amyloid deposition. Furthermore, our results demonstrate that USP25 promoted β cleavage of APP and A β generation by reducing the ubiquitination and lysosomal degradation of both APP and BACE1. Importantly, pharmacological inhibition of USP25 ameliorated amyloid pathology in the 5×FAD mouse brain. In summary, we identified the DS-related gene USP25 as a critical regulator of AD pathology, and our data suggest that USP25 serves as a potential pharmacological target for AD drug development.

Optimal control of greenhouse climate is one of the key techniques in digital agriculture. Greenhouse climate, a nonlinear and uncertain system, consists of several major environmental factors such as temperature, humidity, light intensity, and CO2 concentration. Due to the complex coupled correlations, it is a challenge to achieve coordination control of greenhouse environmental factors. This paper proposes a model-free coordination control approach for greenhouse environmental factors based on Q-learning. Coordination control policy is found through systematic interaction with the dynamic environment to achieve optimal control for greenhouse climate with the control cost constraints. In order to decrease systematic trial-and-error risk and reduce the computational complexity in Q-learning algorithm, case-based reasoning (CBR) is seamlessly incorporated into the Q-learning process. The experimental results demonstrate that this approach is practical, highly effective and efficient.

No abstract

This paper describes the Authentication Test Theory of strand space firstly and the theory is expended because of the demands of mobile ad hoc network routing protocol security analysis. By analyzing the existing security DSR routing protocol leaks, a new Ariadne-S protocol model is proposed based on Ariadne routing protocol. And finally it is proved that the returning routing information from the process of routing finding are secure and credible by using strand space model.