Search

The security of wireless information transmission in large-scale multi-input and multioutput (MIMO) is the focus of research in wireless communication. Recently, a new artificial noise—SCO-AN which shows no orthogonality to the channel, is proposed to overcome the shortcomings of traditional artificial noise. In the previous research, the optimization function of SCO-AN is not convex, and its extremum cannot be obtained. Usually, nonconvex optimization algorithms or iterative relaxation algorithms are used to get the maximum value of the optimization objective function. Nonconvex optimization algorithms or iterative relaxation algorithms are greatly affected by the initial value, and the extremum cannot be obtained by a nonconvex optimization algorithm or iterative relaxation algorithm. In this paper, we creatively apply the strong law of large numbers to obtain the optimal value of the optimization function of SCO-AN under the condition of large-scale MIMO: the strong law of large numbers is applied to obtain the ergodic lower bound (ELB) expression of SC for SCO-AN. The power allocation (PA) problem of the SCO-AN system is discussed. We use a statistical method to get the formula for calculating the optimal power distribution coefficient of the SCO-AN system. The transmitter can use the optimal power ratio of PA to distribute the transmitted power without using the PA algorithm. The effect of imperfect channel state information is discussed. Through simulation, we found that more power should be generated for SCO-AN if the channel estimation is imperfect and the proposed method can achieve better security performance in the large-scale MIMO system.

Background: Studies have reported that synaptic failure occurs before the Alzheimer’s disease (AD) onset. The systemic Porphyromonas gingivalis (P. gingivalis) infection is involved in memory decline. We previously showed that leptomeningeal cells, covering the brain, activate glial cells by releasing IL-1β in response to systemic inflammation. Objective: In the present study, we focused on the impact of leptomeningeal cells on neurons during systemic P. gingivalis infection. Methods: The responses of leptomeningeal cells and cortical neurons to systemic P. gingivalis infection were examined in 15-month-old mice. The mechanism of IL-1β production by P. gingivalis infected leptomeningeal cells was examined, and primary cortical neurons were treated with P. gingivalis infected leptomeningeal cells condition medium (Pg LCM). Results: Systemic P. gingivalis infection increased the expression of IL-1β in leptomeninges and reduced the synaptophysin (SYP) expression in leptomeninges proximity cortex in mice. Leptomeningeal cells phagocytosed P. gingivalis resulting in lysosomal rupture and cathepsin B (CatB) leakage. Leaked CatB mediated NLRP3 inflammasome activation inducing IL-1β secretion in leptomeningeal cells. Pg LCM decreased the expression of synaptic molecules, including SYP, which was inhibited by an IL-1 receptor antagonist pre-treatment. Conclusion: These observations demonstrate that P. gingivalis infection is involved in synaptic failure by inducing CatB/NLRP3 inflammasome-mediated IL-1β production in leptomeningeal cells. The periodontal bacteria-induced synaptic damage may accelerate the onset and cognitive decline of AD.

Background: Synaptic failure is the earliest sign before Alzheimer’s disease (AD) onset and closely associated with cognitive decline. Clinical studies have shown that periodontitis is positively correlated with both the onset and progression of AD, and preclinical studies have shown that Porphyromonas gingivalis (P. gingivalis) and its virulence factors induced memory decline in mice. However, the mechanisms underlying the involvement of P. gingivalis in memory decline remain unclear.Methods: Fifteen-month-old female C57/BL6J mice were intraperitoneally injected with P. gingivalislearning and memory were evaluated by step through passive avoidance tests. Immunofluorescent staining was used to examine the expression of IL-1β and synaptic markers. Primary leptomeningeal cells and primary cortical neurons were used to evaluate the its effects on synaptic generation and plasticity. The expression of related molecules was examined by Q-PCR and Western blotting. Pharmacological and genetic approaches were used to explore the roles of leptomeningeal cells in synaptic changes after P. gingivalis infection. Results: P. gingivalis infection induced the increased expression of IL-1β in leptomeninges and decreased expression of synaptophysin (SYP) in the cortex proximity of the leptomeninges, which was accompanied by memory decline in middle-aged mice. NLRP3 inflammasome activation was involved in augmenting the IL-1β secretion by primary leptomeningeal cells after P. gingivalis infection. Cathepsin B (CatB) mediated the activation of both NLRP3 inflammasome and NF-κB in P. gingivalis-infected primary leptomeningeal cells. In contrast, P. gingivalis-infected leptomeningeal cells induced an IL-1β-dependent decrease in pre- and post-synaptic molecules in primary cortical neurons, as determined by the pharmacological blockage of the IL-1 receptor. P. gingivalis-infected leptomeningeal cells also induced the IL-1β-dependent suppression of BDNF signaling in cultured N2a neurons. Furthermore, propolis produced by honeybees, suppressed the expression of IL-1β but increased that of BDNF in P. gingivalis-infected leptomeningeal cells. Conclusion: The CatB-mediated IL-1β production was augmented in leptomeningeal cells, resulting in synaptic failure and blockage of BDNF signaling in neurons during P. gingivalis infection. These findings highlight a new mechanism underlying the involvement of periodontitis in AD initiation and suggest that CatB may be an early intervention therapeutic target for delaying the onset of AD during P. gingivalis infection.

Background: Synaptic failure is the earliest sign before Alzheimer’s disease (AD) onset and closely associated with cognitive decline. Clinical studies have shown that periodontitis is positively correlated with both the onset and pathological progression of AD, and preclinical studies have shown that Porphyromonas gingivalis (P. gingivalis), the key pathogen in periodontitis, and its virulence factors induced memory decline in mice. However, the mechanisms underlying the involvement of P. gingivalis in memory decline remain unclear. Methods: We used primary leptomeningeal cells and primary cortical neurons to evaluate the effects of leptomeningeal cells on synaptic generation and plasticity after P. gingivalis infection in vitro. The expression of the related molecules was examined by mRNA in real time and by protein levels using Western blotting. Pharmacological and genetic approaches were used to explore the mechanism underlying the involvement of leptomeningeal cells in synaptic changes after P. gingivalis infection. Results: NLRP3 inflammasome activation was involved in augmenting the IL-1β secretion by primary leptomeningeal cells after P. gingivalis infection, as determined by the knockdown of NLRP3 with siRNA. Cathepsin B (CatB) mediated the activation of both NLRP3 inflammasomes and NF-κB for the production of IL-1β by P. gingivalis-infected primary leptomeningeal cells, as determined by the pharmacologically specific inhibition of CatB. In contrast, P. gingivalis-infected leptomeningeal cells induced an IL-1β-dependent decrease in pre- and post-synaptic molecules in primary cortical neurons, as determined by the pharmacological blockage of the IL-1 receptor. P. gingivalis-infected leptomeningeal cells also induced the IL-1β-dependent suppression of BDNF signaling in cultured N2a neurons, a stable mouse neural cell line. Furthermore, propolis, which is produced by honeybees, suppressed the expression of IL-1β but increased that of BDNF in P. gingivalis-infected leptomeningeal cells. Conclusion: The CatB-mediated IL-1β production was augmented in leptomeningeal cells, resulting in synaptic failure and blockage of BDNF signaling in neurons during P. gingivalis infection. These findings highlight a new mechanism underlying the involvement of periodontitis in AD initiation and suggest that CatB may be an early intervention therapeutic target for delaying the onset of AD during P. gingivalis infection.

Background: Alzheimer’s disease (AD) and bone loss are clinically exacerbated. However, the mechanism of exacerbation remains understood. Objective: We tested our hypothesis that periodontitis is involved in the exacerbation, contributing to AD pathologies. Methods: The bone, memory, and inflammation in bone and brain were examined in 12-month-old mice after systemic exposure to lipopolysaccharide from Porphyromonas gingivalis (P gLPS) for 3 consecutive weeks. Results: Compared with control mice, bone loss in tibia (26% decrease) and memory decline (47% decrease) were induced in mice with a positive correlation after exposure to P gLPS (r = 0.7378, p = 0.0011). The IL-6 and IL-17 expression in tibia was negatively correlated with the bone volume/total tissue volume (r = –0.6619, p = 0.0052; r = –0.7129, p = 0.0019), while that in the cortex was negatively correlated with the memory test latency (r = –0.7198, p = 0.0017; p = 0.0351, r = –0.5291). Furthermore, the IL-17 expression in microglia was positively correlated with Aβ42 accumulation in neurons (r = 0.8635, p

The secure transmission problem of MIMO wireless system in fading channels is studied in this paper. We add a secrecy capacity optimization artificial noise(SCO-AN) to the transported signal for improving the security performance of the system. The closed-form expression of secrecy capacity's lower bound is obtained. Base on the closed-form expression of secrecy capacity's lower bound, We optimize the power allocation between the information-bearing signal and the SCO-AN. By calculating, the optimal ratio of power alloation betwenn the information-bearing signal and the SCO-AN is obtained. Through simulation, the results shows the secrecy capacity increases with more receiving antennas and less eavesdropping antennas.And more power should be allocated to the SCO-AN with the increase of the colluding eavedroppers.More over, we study the effect of channel estimation error on power allocation between information-bearing signal and SCO-AN and find that more power should be allocated to decrease eavesdroppers capacity if the channel estimation is not perfect.

Artificial noise(AN) is a core technique in physical layer security field which has been widely studied.AN reduces the channel capacity of eavesdroppers without affecting the channel capacity of the communicator so that AN can increase secrecy capacity.Secrecy capacity is defined as channel capacity of the communicator minus channel capacity of eavesdroppers.The AN is prohibited from affecting the channel capacity of the legal receiving channel. This condition brings good performance to AN as well as limitations.Recently, the secrecy capacity optimization artificial noise (SCO-AN) is proposed to increase the secrecy capacity more effectively.SCO-AN can reduce the channel capacity of the communicator to a small extent while greatly reducing the channel capacity of the eavesdropper. So, SCO-AN can further expand the secrecy capacity on the basis of AN. Due to the limitation of transmit power, SCO-AN cannot be added indefinitely, so it is an important issue to increase the secrecy capacity as much as possible under a certain power limit.In this paper, a secrecy capacity function with SCO-AN added under certain power constraints is established.Because this function is non-convex, the traditional convex optimization algorithm cannot be applied. A sequence quadratic program(SQP) is adopted to solve this power allocation problem.Simulation results show that SQP can effectively improve the secrecy capacity under a certain power limit.

BACKGROUND Bone tissue engineering, a powerful tool to treat bone defects, is highly dependent on use of scaffolds. Both silk fibroin (SF) and chitosan (Cs) are biocompatible and actively studied for reconstruction of tissue engineering. Gelatin (Gel) is also widely applied in the biomedical field due to its low antigenicity and physicochemical stability. MATERIAL AND METHODS In this study, 4 different types of scaffolds were constructed - SF, SF/Cs, SF/Gel, and SF/Cs/Gel - and we compared their physical and chemical properties as well as biological characterization of these scaffolds to determine the most suitable scaffold for use in bone regeneration. First, these scaffolds were produced via chemical cross-linking method and freeze-drying technique. Next, the characterization of internal structure was studied using scanning electron microscopy and the porosity was evaluated by liquid displacement method. Then, we compared physicochemical properties such as water absorption rate and degradation property. Finally, MC3T3-E1 cells were inoculated on the scaffolds to study the biocompatibility and osteogenesis of the three-dimensional (3D) scaffolds in vitro. RESULTS The composite scaffold formed by all 3 components was the best for use in bone regeneration. CONCLUSIONS We conclude that the best scaffold among the 4 studied for MC3T3-E1 cells is our SF/Cs/Gel scaffold, suggesting a new choice for bone regeneration that can be used to treat bone defects or fractures in clinical practice.

In this paper, the decision-level data fusion techniques are extended to the multiuser detection (MUD) field. Then two novel MUD algorithms, that is the chairman arbitrating decision-level fusion criterion (CA-DFC) based MUD algorithm and the veto logic decision-level fusion criterion (VL-DFC) based MUD algorithm, are proposed for DS-UWB communication systems. In CA-DFC based method, the chairman can make his arbitration among the preliminary decisions from sub-optimal detectors by his own rule. In the VL-DFC based method, the undetermined bits in these preliminary decisions are considered to construct a simplified solution space, and then the chairman can make his final decision within this space. Simulation results demonstrate that the performances of CA-DFC and VL-DFC based MUD algorithms are superior to those of other sub-optimal MUD algorithms, and even close to that of OMD. Moreover, both of these proposed algorithms have lower computational complexity than OMD, which reveals their efficiency. Compared with CA-DFC, VL-DFC based algorithm achieves a little improvement in its performance, at the cost of the increment in its computational complexity. Thus, they can be applied to different practical situations.