Network-Scale Traffic Signal Control via Multiagent Reinforcement Learning With Deep Spatiotemporal Attentive Network.

The continuous development of intelligent traffic control systems has a profound influence on urban traffic planning and traffic management. Indeed, as big data and artificial intelligence continue to evolve, the traffic control strategy based on deep reinforcement learning (RL) has been proven to be a promising method to improve the efficiency of intersections and save people's travel time. However, the existing algorithms ignore the temporal and spatial characteristics of intersections. In this article, we propose a multiagent RL based on the deep spatiotemporal attentive neural network (MARL-DSTAN) to determine the traffic signal timing in a large-scale road network. In this model, the state information captures the spatial dependency of the entire road network by leveraging the graph convolutional network (GCN) and integrates the information based on the importance of intersections via the attention mechanism. Meanwhile, to accumulate more valuable samples and enhance the learning efficiency, the recurrent neural network (RNN) is introduced in the exploration stage to constrain the action search space instead of fully random exploration. MARL-DSTAN decomposes the large-scale area into multiple base environments, and the agents in each base environment use the idea of "centralized training and decentralized execution" to learn to accelerate the algorithm convergence. The simulation results show that our algorithm significantly outperforms the fixed timing scheme and several other state-of-the-art baseline RL algorithms.

mTOR inhibitor PP242 increases antitumor activity of sulforaphane by blocking Akt/mTOR pathway in esophageal squamous cell carcinoma.

BACKGROUND: Sulforaphane (SFN) is a kind of isothiocyanate from cruciferous vegetables with extensive anti-tumor activity. Esophageal squamous cell carcinoma (ESCC) is a popular malignancy in East Asia, East and South Africa, while the more efficient medicines and therapeutic strategies are still lack. This study aims to explore the anti-tumor activity of SFN alone and combined with Akt/mTOR pathway inhibitors as well as the potential molecular mechanism in ESCC. METHODS AND RESULTS: Cell proliferation, migration, cell cycle phase, apoptosis and protein expression were detected with MTT assay, clone formation experiment, wound healing assays, flow cytometry and Western blot, respectively, after ESCC cells ECa109 and EC9706 treated with SFN alone or combined with Akt/mTOR inhibitors. Xenograft models were used to evaluate the efficiency and mechanism of SFN combined with PP242 in vivo. The results showed that SFN significantly inhibited the viability and induced apoptosis of ECa109 and EC9706 cells by increasing expression of Cleaved-caspase 9. SFN combined with PP242, but not MK2206 and RAD001, synergetic inhibited proliferation of ESCC cells. Moreover, compared to SFN alone, combination of SFN and PP242 had stronger inhibiting efficiency on clone formation, cell migratory, cell cycle phase and growth of xenografts, as well as the more powerful apoptosis-inducing effects on ESCC. The mechanism was that PP242 abrogated the promoting effects of SFN on p-p70S6K (Thr389) and p-Akt (Ser473) in ESCC. CONCLUSIONS: Our findings demonstrate that PP242 enhances the anti-tumor activity of SFN by blocking SFN-induced activation of Akt/mTOR pathway in ESCC, which provides a rationale for treating ESCC using SFN combined with Akt/mTOR pathway inhibitors.

Cooperative Intersection with Misperception in Partially Connected and Automated Traffic.

The emerging connected and automated vehicle (CAV) has the potential to improve traffic efficiency and safety. With the cooperation between vehicles and intersection, CAVs can adjust speed and form platoons to pass the intersection faster. However, perceptual errors may occur due to external conditions of vehicle sensors. Meanwhile, CAVs and conventional vehicles will coexist in the near future and imprecise perception needs to be tolerated in exchange for mobility. In this paper, we present a simulation model to capture the effect of vehicle perceptual error and time headway to the traffic performance at cooperative intersection, where the intelligent driver model (IDM) is extended by the Ornstein-Uhlenbeck process to describe the perceptual error dynamically. Then, we introduce the longitudinal control model to determine vehicle dynamics and role switching to form platoons and reduce frequent deceleration. Furthermore, to realize accurate perception and improve safety, we propose a data fusion scheme in which the Differential Global Positioning system (DGPS) data interpolates sensor data by the Kalman filter. Finally, a comprehensive study is presented on how the perceptual error and time headway affect crash, energy consumption as well as congestion at cooperative intersections in partially connected and automated traffic. The simulation results show the trade-off between the traffic efficiency and safety for which the number of accidents is reduced with larger vehicle intervals, but excessive time headway may result in low traffic efficiency and energy conversion. In addition, compared with an on-board sensor independently perception scheme, our proposed data fusion scheme improves the overall traffic flow, congestion time, and passenger comfort as well as energy efficiency under various CAV penetration rates.

Inhibiting autophagy enhances sulforaphane-induced apoptosis via targeting NRF2 in esophageal squamous cell carcinoma.

Sulforaphane (SFN), a natural anti-tumor compound from cruciferous vegetables, has been reported to induce protective autophagy to cancer cells, which might impair the anti-tumor efficiency of SFN. However, the accurate function and mechanism of SFN inducing autophagy in cancers are still obscure, especially in esophageal squamous cell carcinoma (ESCC), one of malignancies with high incidence in North China. Here, we mainly explored the potential function of autophagy upon SFN treatment in ESCC and molecular mechanism. We demonstrated that SFN could inhibit cell proliferation and induce apoptosis by activating caspase pathway. Moreover, we found activation of NRF2 pathway by SFN was responsible for the induction of autophagy and also a disadvantage element to the anti-tumor effects of SFN on ESCC, indicating that SFN might induce protective autophagy in ESCC. We, therefore, investigated effects of autophagy inhibition on sensitivity of ESCC cells to SFN and found that chloroquine (CQ) could neutralize the activation of SFN on NRF2 and enhance the activation of SFN on caspase pathway, thus improved the anti-tumor efficiency of SFN on ESCC in vitro and in vivo. Our study provides a preclinical rationale for development of SFN and its analogs to the future treatment of ESCC.

miR-199a-3p suppresses progression of esophageal squamous cell carcinoma through inhibiting mTOR/p70S6K pathway.

Dysregulation of microRNA contributes to multiple tumorigenic processes. Although downregulation of miR-199a-3p has been shown in many cancers, its effects on esophageal squamous cell carcinoma (ESCC) and the regulatory mechanism are still obscure. Here, we aim to evaluate the biological function and underlying mechanisms of miR-199a-3p in ESCC as well as its value to clinical treatment of ESCC. We first analyzed expression of miR-199a-3p in esophageal cancer by bioinformatic analysis and found that there were different opinions about expression of miR-199a-3p in esophageal cancer, and the following qRT-PCR assay demonstrated which was markedly downregulated in ESCC cells. Next, we increased the expression of miR-199a-3p in ESCC cells using miR-199a-3p mimics and demonstrated that overexpression of miR-199a-3p significantly inhibited cell proliferation, migration and invasion, as well as induced cell cycle retard and promoted apoptosis in ESCC. Furthermore, we explored the functional targets of miR-199a-3p and identified that overexpression of miR-199a-3p inhibited mTOR/p70S6K pathway, but stimulated PI3K/Akt pathway. Finally, we demonstrated that overexpression of miR-199a-3p enhanced proliferation-inhibiting effects of MK2206, an inhibitor of Akt, to ESCC cells, which might be related that MK2206 eliminated the activation of miR-199a-3p to p-Akt. These findings discover that miR-199a-3p might participate in the carcinogenesis process of ESCC, which provides a new insight for treatment of ESCC.

OP16 induces deadly autophagy and apoptosis of cells by inhibiting Akt in esophageal squamous cell carcinoma.

BACKGROUND: OP16, a derivative of the novel ent-kaurene diterpenoid compound separated from Rabdosia rubescens, has been confirmed for its efficacy and safety in the treatment of esophageal squamous cell carcinoma (ESCC) in our previous study. However, the precise mechanisms of tumor lethality mediated by OP16 have not yet been fully characterized. AIMS: To investigate the effects and molecular mechanism of OP16 on autophagy and apoptosis of ESCC cells. METHODS: Effects and mechanism of OP16 on autophagy of ESCC cells were first detected by Western blot, immunofluorescence, mRFP-GFP-LC3 adenovirus infection and transmission electron microscope. Next, function of autophagy and apoptosis induced by OP16 on cell death was investigated by flow cytometry and CCK-8 assay. Finally, molecular mechanism of OP16 affecting autophagy and apoptosis of ESCC cells was explored by Western blot. RESULTS: We demonstrated that OP16 could induce autophagy by promoting the formation of autophagosome and autolysosome, and promote autophagic cell death in ESCC. Furthermore, we also found that OP16 could promote cell apoptosis by activating mitochondria apoptosis pathway in ESCC. Finally, we demonstrated that OP16 affecting autophagy and mitochondria apoptosis pathway was mediated by phosphorylation of Akt. CONCLUSION: Our data show that OP16 could promote cell death through affecting autophagy and mitochondria apoptosis pathway mediated by Akt in ESCC, which enriches the theoretical mechanism of anti-tumor effects of OP16 and provides a basis for treatment of OP16 on ESCC.

RICTOR/mTORC2 affects tumorigenesis and therapeutic efficacy of mTOR inhibitors in esophageal squamous cell carcinoma.

Dysregulation of mTORC1/mTORC2 pathway is observed in many cancers and mTORC1 inhibitors have been used clinically in many tumor types; however, the mechanism of mTORC2 in tumorigenesis is still obscure. Here, we mainly explored the potential role of mTORC2 in esophageal squamous cell carcinoma (ESCC) and its effects on the sensitivity of cells to mTOR inhibitors. We demonstrated that RICTOR, the key factor of mTORC2, and p-AKT (Ser473) were excessively activated in ESCC and their overexpression is related to lymph node metastasis and the tumor-node-metastasis (TNM) phase of ESCC patients. Furthermore, we found that mTORC1/ mTORC2 inhibitor PP242 exhibited more efficacious anti-proliferative effect on ESCC cells than mTORC1 inhibitor RAD001 due to RAD001-triggered feedback activation of AKT signal. Another, we demonstrated that down-regulating expression of RICTOR in ECa109 and EC9706 cells inhibited proliferation and migration as well as induced cell cycle arrest and apoptosis. Noteworthy, knocking-down stably RICTOR significantly suppresses RAD001-induced feedback activation of AKT/PRAS40 signaling, and enhances inhibition efficacy of PP242 on the phosphorylation of AKT and PRAS40, thus potentiates the antitumor effect of RAD001 and PP242 both in vitro and in vivo. Our findings highlight that selective targeting mTORC2 could be a promising therapeutic strategy for future treatment of ESCC.

An Energy Efficient Design of Computation Offloading Enabled by UAV.

The data volume is exploding due to various newly-developing applications that call for stringent communication requirements towards 5th generation wireless systems. Fortunately, mobile edge computing makes it possible to relieve the heavy computation pressure of ground users and decrease the latency and energy consumption. What is more, the unmanned aerial vehicle has the advantages of agility and easy deployment, which gives the unmanned aerial vehicle enabled mobile edge computing system opportunities to fly towards areas with communication demand, such as hotspot areas. However, the limited endurance time of unmanned aerial vehicle affects the performance of mobile edge computing services, which results in the incomplete mobile edge computing services under the time limit. Consequently, this paper concerns the energy-efficient scheme design of the unmanned aerial vehicle while providing high-quality offloading services for ground users, particularly in the regions where the ground communication infrastructures are overloaded or damaged after natural disasters. Firstly, the model of energy-efficient design of the unmanned aerial vehicle is set up taking the constraints of the energy limitation of the unmanned aerial vehicle, the data causality, and the speed of the unmanned aerial vehicle into account. Subsequently, aiming at maximizing the energy efficiency of the unmanned aerial vehicle in the unmanned aerial vehicle enabled mobile edge computing system, the bits allocation in each time slot and the trajectory of the unmanned aerial vehicle are jointly optimized. Secondly, a successive convex approximation based alternating algorithm is brought forward to deal with the non-convex energy efficiency maximization problem. Finally, it is proved that the proposed energy efficient scheme design of the unmanned aerial vehicle is superior to other benchmark schemes by the simulation results. Besides, how the performance of proposed scheme design change under different parameters is discussed.

On-Demand Channel Bonding in Heterogeneous WLANs: A Multi-Agent Deep Reinforcement Learning Approach.

In order to meet the ever-increasing traffic demand of Wireless Local Area Networks (WLANs), channel bonding is introduced in IEEE 802.11 standards. Although channel bonding effectively increases the transmission rate, the wider channel reduces the number of non-overlapping channels and is more susceptible to interference. Meanwhile, the traffic load differs from one access point (AP) to another and changes significantly depending on the time of day. Therefore, the primary channel and channel bonding bandwidth should be carefully selected to meet traffic demand and guarantee the performance gain. In this paper, we proposed an On-Demand Channel Bonding (O-DCB) algorithm based on Deep Reinforcement Learning (DRL) for heterogeneous WLANs to reduce transmission delay, where the APs have different channel bonding capabilities. In this problem, the state space is continuous and the action space is discrete. However, the size of action space increases exponentially with the number of APs by using single-agent DRL, which severely affects the learning rate. To accelerate learning, Multi-Agent Deep Deterministic Policy Gradient (MADDPG) is used to train O-DCB. Real traffic traces collected from a campus WLAN are used to train and test O-DCB. Simulation results reveal that the proposed algorithm has good convergence and lower delay than other algorithms.

Inhibition of autophagy improves resistance and enhances sensitivity of gastric cancer cells to cisplatin.

Autophagy plays critical roles in tumorigenesis, while the effects of autophagy on chemoresistance of cancer cells had great disparity. This study aims to explore the impacts of autophagy on the sensitivity and resistance of gastric cancer cells to cisplatin (DDP). We firstly demonstrated that there was stronger autophagy activity in gastric cancer SGC-7901 cells than that in DDP-resisting SGC-7901/DDP cells. Then, we discovered that inhibiting autophagy by chloroquine (CQ) significantly enhanced the proliferation-inhibiting and apoptosis-inducing effects of DDP to SGC-7901 and SGC-7901/DDP cells. Moreover, CQ could partially reverse the resistance of SGC-7901/DDP cells to DDP in a concentration-dependent manner. However, the autophagy inducer everolimus (RAD001) had no obvious effects on the sensitivity of gastric cells to DDP. Mechanistically, we demonstrated that CQ might enhance the sensitivity of SGC-7901cells and improve the resistance of SGC-7901/DDP cells to DDP through inhibiting the mTORC1 pathway, especially to SGC-7901/DDP cells. Additionally, we found interfering Beclin-1 using Beclin-1 shRNA also enhanced the proliferation-inhibiting and apoptosis-inducing effects of DDP on gastric cancer cells by inhibiting phosphorylation of Akt. Our study shows that inhibiting autophagy could improve the chemoresistance and enhanced sensitivity of gastric cancer cells to DDP and provide a rationale for the administration of cisplatin combined with CQ for treating patients with gastric cancer.

Energy-Efficient UAV-Enabled MEC System: Bits Allocation Optimization and Trajectory Design.

The unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC) system is attracting a lot of attentions for the potential of low latency and low transmission energy consumption, due to the advantages of high mobility and easy deployment. It has been widely applied to provide communication and computing services, especially in Internet of Things (IoT). However, there are still some challenges in the UAV-enabled MEC system. Firstly, the endurance of the UAV is limited and further impacts the performance of the system. Secondly, mobile devices are battery-powered and the batteries of some devices are hard to change. Therefore, in this paper, a UAV-enabled MEC system in which the UAV is empowered to have computing capability and provides tasks offloading service is studied. The total energy consumption of the UAV-enabled system, which includes the energy consumption of the UAV and the energy consumption of the ground users, is minimized under the constraints of the UAV's energy budget, the number of each task's bits, the causality of the data and the velocity of the UAV. The bits allocation of uploading data, computing data, downloading data and the trajectory of the UAV are jointly optimized with the goal of minimizing the total energy consumption. Moreover, a two-stage alternating algorithm is proposed to solve the non-convex formulated problem. Finally, the simulation results show the superiority of the proposed scheme compared with other benchmark schemes. Finally, the performance of the proposed scheme is demonstrated under different settings.

LSD1 regulates Notch and PI3K/Akt/mTOR pathways through binding the promoter regions of Notch target genes in esophageal squamous cell carcinoma.

Background: The aberrant activation of Lysine-specific demethylase 1(LSD1), Notch and PI3K/Akt/mTOR signaling pathways were frequently happened in many cancers, including esophageal squamous cell carcinoma (ESCC). However, the regulatory relationship between LSD1 and Notch as well as PI3K/Akt/mTOR pathways is still unclear. Purpose: This study aimed to explore the regulatory effects and mechanisms of LSD1 on Notch and PI3K/Akt/mTOR pathway in ESCC. Results: Firstly, we demonstrated that LSD1 and proteins in Notch and PI3K/Akt/mTOR pathway were expressed in ESCC cells. Secondly, inhibition of LSD1 by tranylcypromine (TCP) or shRNA could decrease the expressions of related proteins in Notch and PI3K/Akt/mTOR signaling pathways in ESCC cells. Finally, we found that LSD1 could bind to the promoter regions of Notch3, Hes1 and CR2, and the combinations between them were reduced by TCP in ESCC. Conclusion: Summarily, this study indicated that LSD1 might positively regulate Notch and PI3K/Akt/mTOR pathways through binding the promoter regions of related genes in Notch pathway in ESCC.

Multi-Location-Aware Joint Optimization of Content Caching and Delivery for Backhaul-Constrained UDN.

Mobile edge caching is regarded as a promising way to reduce the backhaul load of the base stations (BSs). However, the capacity of BSs' cache tends to be small, while mobile users' content preferences are diverse. Furthermore, both the locations of users and user-BS association are uncertain in wireless networks. All of these pose great challenges on the content caching and content delivery. This paper studies the joint optimization of the content placement and content delivery schemes in the cache-enabled ultra-dense small-cell network (UDN) with constrained-backhaul link. Considering the differences in decision time-scales, the content placement and content delivery are investigated separately, but their interplay is taken into consideration. Firstly, a content placement problem is formulated, where the uncertainty of user-BS association is considered. Specifically, different from the existing works, the specific multi-location request pattern is considered that users tend to send content requests from more than one but limited locations during one day. Secondly, a user-BS association and wireless resources allocation problem is formulated, with the objective of maximizing users' data rates under the backhaul bandwidth constraint. Due to the non-convex nature of these two problems, the problem transformation and variables relaxation are adopted, which convert the original problems into more tractable forms. Then, based on the convex optimization methods, a content placement algorithm, and a cache-aware user association and resources allocation algorithm are proposed, respectively. Finally, simulation results are given, which validate that the proposed algorithms have obvious performance advantages in terms of the network utility, the hit ratio of the cache, and the quality of service guarantee, and are suitable for the cache-enabled UDN with constrained-backhaul link.

Dynamic Speed Control of Unmanned Aerial Vehicles for Data Collection under Internet of Things.

With the new advancements in flight control and integrated circuit (IC) technology, unmanned aerial vehicles (UAVs) have been widely used in various applications. One of the typical application scenarios is data collection for large-scale and remote sensor devices in the Internet of things (IoT). However, due to the characteristics of massive connections, access collisions in the MAC layer lead to high power consumption for both sensor devices and UAVs, and low efficiency for the data collection. In this paper, a dynamic speed control algorithm for UAVs (DSC-UAV) is proposed to maximize the data collection efficiency, while alleviating the access congestion for the UAV-based base stations. With a cellular network considered for support of the communication between sensor devices and drones, the connection establishment process was analyzed and modeled in detail. In addition, the data collection efficiency is also defined and derived. Based on the analytical models, optimal speed under different sensor device densities is obtained and verified. UAVs can dynamically adjust the speed according to the sensor device density under their coverages to keep high data collection efficiency. Finally, simulation results are also conducted to verify the accuracy of the proposed analytical models and show that the DSC-UAV outperforms others with the highest data collection efficiency, while maintaining a high successful access probability, low average access delay, low block probability, and low collision probability.

FLI-06 suppresses proliferation, induces apoptosis and cell cycle arrest by targeting LSD1 and Notch pathway in esophageal squamous cell carcinoma cells.

Aberrant activation of the Notch signaling plays an important role in progression of esophageal squamous cell carcinoma (ESCC) and may represent a potential therapeutic target for ESCC. FLI-06 is a novel Notch inhibitor, preventing the early secretion of Notch signaling. However, little information about the antitumor activity of FLI-06 has been reported so far. To evaluate the anti-tumor activity and possible molecular mechanism of FLI-06 to ESCC cells, the effects of FLI-06 on cell viability, apoptosis and cell cycle were evaluated by CCK-8 and flow cytometry assays, respectively, in ESCC cell lines ECa109 and EC9706, and the expressions of proteins in Notch signaling pathway and LSD1 were investigated after cells were treated with FLI-06 by Western blotting. The results showed that FLI-06 blocked proliferation, induced apoptosis and G1 phase arrest of ESCC cells in a dose-dependent manner. Mechanistically, we found FLI-06 could inhibit Notch signaling pathway by decreasing the expressions of Notch3, DTX1 and Hes1. Interestingly, we also found that the expression of LSD1 (histone lysine specific demethylase 1), which is dysregulated in multiple tumors, was also inhibited by FLI-06. In addition, inhibition of Notch pathway by γ-secretase inhibitor GSI-DAPT could also inhibit LSD1 expression. The current study demonstrated that FLI-06 exerts antitumor activity on ESCC by inhibiting both LSD1 and Notch pathway, which provides the theory support for the treatment of ESCC with FLI-06.

Down-regulation of Rictor enhances cell sensitivity to PI3K inhibitor LY294002 by blocking mTORC2-medicated phosphorylation of Akt/PRAS40 in esophageal squamous cell carcinoma.

PI3K/Akt/mTOR signaling pathway plays a vital role in regulating cell survival, differentiation, metabolism and migration, which is frequently hyperactive in a number of cancers, including esophageal squamous cell carcinoma (ESCC). As the core subunit of mTORC2, Rictor is shown to be amplified in ESCC patients' tissues and plays an important role in regulation of Akt. The objective of this study is to evaluate the effects of Rictor knockdown on cell sensitivity to PI3K inhibitor LY294002 in ESCC cells and ESCC xenografts as well as its mechanisms. We found LY294002 obviously restrained cell proliferation in dose-dependent and time-dependent manners by inhibiting PI3K/Akt/mTOR/p70S6K signaling pathway, whereas triggered mTORC2-medicated phosphorylation of Akt (Ser473)/PRAS40 (Thr246) in ECa109 and EC9706 cells. Stable knockdown of Rictor by shRNA enhanced the inhibitory effects of LY294002 on cell proliferative, migration and colony formation, as well as promoted its effects on cell cycle arrest and cell apoptosis in vitro. Furthermore, stable knockdown of Rictor enhanced the antitumor effects of LY294002 by inhibiting tumor growth and promoting cell apoptosis in vivo. Mechanistic assay revealed that knockdown of Rictor could attenuate LY294002-induced phosphorylation of Akt (Ser473)/PRAS40 (Thr246). Our results provide rationale that combined inhibition of Rictor/mTORC2 and PI3K for the treatment of ESCC.

OP16, a novel ent-kaurene diterpenoid, potentiates the antitumor effect of rapamycin by inhibiting rapamycin-induced feedback activation of Akt signaling in esophageal squamous cell carcinoma.

Hyperactivation of mTOR signaling pathway has been viewed as a significant molecular pathogenesis of cancer. However, inhibition of mTOR by rapamycin and its analogs could induce numerous negative feedback loops to attenuate their therapeutic efficacy. As a traditional Chinese herbal medicine, Rabdosia rubescens has been used to treat esophageal squamous cell carcinoma (ESCC) for hundreds of years, and its major effective component is oridonin. Here we reported that OP16, a novel analog of oridonin, showed potent inhibition of cell proliferation and Akt phosphorylation in ESCC cells. The combination of OP16 and rapamycin possesses synergistic anti-proliferative and pro-apoptotic effects both in ESCC cells and ESCC xenografts, and no obvious adverse effect was observed in vivo. Mechanistic analysis revealed that OP16 could inhibit rapamycin-induced Akt activation through the p70S6K-mediated negative feedback loops, and the combination of OP16 and rapamycin was more effective in activating caspase-dependent apoptotic signaling cascade. This study supports the combined use of OP16 with rapamycin as a feasible and effective therapeutic approach for future treatment of ESCC.

Overload Control for Signaling Congestion of Machine Type Communications in 3GPP Networks.

Because of the limited resources on radio access channels of third generation partnership projection (3GPP) network, one of the most challenging tasks posted by 3GPP cellular-based machine type communications (MTC) is congestion due to massive requests for connection to radio access network (RAN). In this paper, an overload control algorithm in 3GPP RAN is proposed, which proactively disperses the simultaneous access attempts in evenly distributed time window. Through periodic reservation strategy, massive access requests of MTC devices are dispersed in time, which reduces the probability of confliction of signaling. By the compensation and prediction mechanism, each device can communicate with MTC server with dynamic load of air interface. Numerical results prove that proposed method makes MTC applications friendly to 3GPP cellular network.

Downregulation of p70S6K Enhances Cell Sensitivity to Rapamycin in Esophageal Squamous Cell Carcinoma.

It has been demonstrated that mTOR/p70S6K pathway was abnormally activated in many cancers and rapamycin and its analogs can restrain tumor growth through inhibiting this pathway, but some tumors including esophageal squamous cell carcinoma (ESCC) appear to be insensitive to rapamycin in recent studies. In the present study, we explored the measures to improve the sensitivity of ESCC cells to rapamycin and identified the clinical significance of the expression of phosphorylated p70S6K (p-p70S6K). The results showed that, after downregulating the expression of p70S6K and p-p70S6K by p70S6K siRNA, the inhibitory effects of rapamycin on cell proliferation, cell cycle, and tumor growth were significantly enhanced in vitro and in vivo. Furthermore, p-p70S6K had strong positive expression in ESCC tissues and its expression was closely related to lymph node metastasis and the TNM staging. These results indicated that p-p70S6K may participate in the invasion and metastasis in the development of ESCC and downregulation of the expression of p-p70S6K could improve the sensitivity of cells to rapamycin in ESCC.

Low-frequency repetitive transcranial magnetic stimulation on Parkinson motor function: a meta-analysis of randomised controlled trials.

OBJECTIVES: Previous studies have demonstrated inconsistent findings regarding the efficacy of low-frequency repetitive transcranial magnetic stimulation (rTMS) in treating motor symptoms of Parkinson's disease (PD). Therefore, this meta-analysis was conducted to assess the efficacy of low-frequency rTMS. METHODS: A comprehensive literature search (including PubMed, CCTR, Embase, Web of Science, CNKI, CBM-disc, NTIS,EAGLE, Clinical Trials, Current Controlled Trials, International Clinical Trials Registry) was conducted dating until June 2014. The key search terms ('Parkinson', 'PD', 'transcranial magnetic stimulation', 'TMS', 'RTMS' and 'noninvasive brain stimulation') produced eight high-quality randomised controlled trials (RCT) of low-frequency rTMS versus sham stimulation. RESULTS: These eight studies, composed of 319 patients, were meta-analysed through assessment of the decreased Unified Parkinson's Disease Rating Scale (UPDRS part III) score. Pooling of the results from these RCTs yielded an effect size of -0.40 (95%CI=-0.73 to -0.06, p<0.05) in UPDRS part III, which indicated that low-frequency rTMS could have 5.05 (95%CI=-1.73 to -8.37) point decrease in UPDRS part III score than sham stimulation. DISCUSSION: Low-frequency rTMS had a significant effect on motor signs in PD. As the number of RCTs and PD patients included here was limited, further large-scale multi-center RCTs were required to validate our conclusions.