Mitochondrial dysfunction and oxidative stress are thought to play a dominant role in the pathogenesis of Parkinson’s disease (PD). Mogroside V (MV), extracted from
Siraitia grosvenorii
, exhibits ...antioxidant-like activities. The aim of this study was to investigate the function of MV in neuroprotection in PD and to reveal its mechanism of action. To that end, we firstly set up mice models of PD with unilateral striatum injection of 0.25 mg/kg rotenone (Rot) and co-treated with 2.5 mg/kg, 5 mg/kg, and 10 mg/kg MV by gavage. Results showed that Rot-induced motor impairments and dopaminergic neuronal damage were reversed by treatment of 10 mg/kg MV. Then, we established cellular models of PD using Rot-treated SH-SY5Y cells, which were divided into six groups, including control, Rot, and co-enzyme Q10 (CQ10), as well as MV groups, MV25, MV50, and MV100 treated with 25 μM, 50 μM, and 100 μM MV doses, respectively. Results demonstrated that MV effectively attenuates Rot neurotoxicity through a ROS-related intrinsic mitochondrial pathway. MV reduced overproduction of reactive oxygen species (ROS), recovered the mitochondrial membrane potential (MMP), and increased the oxygen consumption rate and adenosine triphosphate (ATP) production in a dose-dependent manner. Hence, treatment with MV led to a reduction in the number of apoptotic cells, as reflected by Annexin-V/propidium iodide co-staining using flow cytometry and TdT-mediated dUTP Nick-End Labeling (TUNEL) assay. In addition, the Sirtuin3 (SIRT3) protein level and activity were decreased upon exposure to Rot both in substantia nigra (SN) of mice and SH-SY5Y cells. SIRT3 impairment hyperacetylated a key mitochondrial antioxidant enzyme, superoxide dismutase 2 (SOD2). MV alleviates SIRT3 and SOD2 molecular changes. However, after successfully inhibiting SIRT3 by its specific inhibitor 3-1H-1, 2, 3-triazol-4-yl pyridine (3TYP), MV was not able to reduce ROS levels, reverse abnormal MMP, or decrease apoptotic cells. Motor impairments and dopaminergic neuronal injury in the SN were alleviated with the oral administration of MV in Rot-treated PD mice, indicating a relationship between protection against defective motility and preservation of dopaminergic neurons. Therefore, we conclude that MV can alleviate Rot-induced neurotoxicity in a PD model, and that SIRT3 may be an important regulator in the protection of MV.
Autonomous underwater vehicles (AUVs)-assisted mobile data collection in underwater wireless sensor networks (UWSNs) has received significant attention because of their mobility and flexibility. To ...satisfy the increasing demand of diverse application requirements for underwater data collection, such as time-sensitive data freshness, emergency event security as well as energy efficiency, in this paper, we propose a novel multi-modal AUV-assisted data collection scheme which integrates both acoustic and optical technologies and takes advantage of their complementary strengths in terms of communication distance and data rate. In this scheme, we consider the age of information (AoI) of the data packet, node transmission energy as well as energy consumption of the AUV movement, and we make a trade-off between them to retrieve data in a timely and reliable manner. To optimize these, we leverage a deep reinforcement learning (DRL) approach to find the optimal motion trajectory of AUV by selecting the suitable communication options. In addition to that, we also design an optimal angle steering algorithm for AUV navigation under different communication scenarios to reduce energy consumption further. We conduct extensive simulations to verify the effectiveness of the proposed scheme, and the results show that the proposed scheme can significantly reduce the weighted sum of AoI as well as energy consumption.
Deploying wireless sensor networks in the ocean poses many challenges due to the harsh conditions of the ocean and the nonnegligible node mobility. In this paper, we propose hybrid ocean sensor ...networks called drifting restricted floating ocean sensor networks (DR-OSNs) for long-term maritime surveillance monitoring tasks, which combines both the advantages of wireless sensor networks and underwater wireless acoustic sensor networks. We present a localization scheme termed localization for double-head maritime sensor networks (LDSN) for DR-OSNs, which leverages the unique characteristics of DR-OSNs to establish the whole localization system after the network is deployed from a plane or a ship, and it does not need the presence of designated anchor nodes deployed underwater. The whole localization process consists of three steps with algorithms self-moored node localization (SML), underwater sensor localization (USD), and floating-node localization algorithm (FLA). The first step is for the super group nodes to localize their underwater moored nodes via an SML algorithm by leveraging the free-drifting movement of their surface nodes. Once the moored nodes in the super group nodes have localized themselves, they turn into anchor nodes underwater. Thus, in the second step, with the help of these new anchor nodes, the unlocalized underwater moored nodes use the USD algorithm to localize their positions. In the last step, when the free-drifting floating nodes without a Global Positioning System (GPS) module need to know their instant position, they apply the FLA to figure out their position. We conduct extensive simulations to evaluate the scheme, with the results indicating that LDSN achieves high localization accuracy and is an effective localization scheme for DR-OSNs.
Localization is a critical issue for Underwater Acoustic Sensor Networks (UASNs). Existing localization algorithms mainly focus on localizing unknown nodes (location-unaware) by measuring their ...distances to beacon nodes (location-aware), whereas ignoring additional challenges posed by harsh underwater environments. Especially, underwater nodes move constantly with ocean currents and measurement noises vary with distances. In this paper, we consider a special drifting-restricted UASN and propose a novel beacon-free algorithm, called MAP-PSO. It consists of two steps: MAP estimation and PSO localization. In MAP estimation, we analyze nodes' mobility patterns, which provide the priori knowledge for localization, and characterize distance measurements under the assumption of additive and multiplicative noises, which serve as the likelihood information for localization. Then the priori and likelihood information are fused to derive the localization objective function. In PSO localization, a swarm of particles are used to search the best location solution from local and global views simultaneously. Moreover, we eliminate the localization ambiguity using a novel reference selection mechanism and improve the convergence speed using a bound constraint mechanism. In the simulations, we evaluate the performance of the proposed algorithm under different settings and determine the optimal values for tunable parameters. The results show that our algorithm outperforms the benchmark method with high localization accuracy and low energy consumption.
Localization is one of the critical services in Underwater Acoustic Sensor Networks (UASNs). Due to harsh underwater environments, the nodes often move with currents continuously. Consequently, the ...acoustic signals usually propagate with varying speeds in non-straight lines and the noise levels change frequently with the motion of the nodes. These limitations pose huge challenges for localization in UASNs. In this paper, we propose a novel localization method based on a variational filtering technique, in which the spatial correlation and temporal dependency information are utilized to improve localization performance. In the method, a state evolution model is employed to characterize the mobility pattern of the nodes and capture the uncertainty of the location transition. Then, a measurement model is used to reflect the relation between the measurements and the locations considering the dynamics of the acoustic speed and range noise. After that, a variational filtering scheme is adopted to determine the nodes' locations, which consists of two phases: variational prediction and update. In the former phase, the coarse estimation of each node' location is computed based on its previous location; in the latter phase, the coarse location is optimized by incorporating the measurements from the reference nodes as precisely as possible. At last, an iterative localization scheme is applied, in which a node labels itself as a reference node if the confidence of its location estimation is higher than the predefined threshold. We conducted extensive simulations under different parameter settings, and the results indicate that the proposed method has better localization accuracy compared to a typical SLMP algorithm while maintaining relatively high localization coverage. Moreover, spatial⁻temporal variational filtering (STVF) is more robust to the change of the parameter settings compared to SLMP.
The software-defined networking paradigm enables wireless sensor networks as a programmable and reconfigurable network to improve network management and efficiency. However, several challenges arise ...when implementing the concept of software-defined networking in maritime wireless sensor networks, as the networks operate in harsh ocean environments, and the dominant underwater acoustic systems are with limited bandwidth and high latency, which render the implementation of software-defined networking central-control difficult. To cope with the problems and meet demand for high-speed data transmission, we propose a radio frequency–acoustic software-defined networking-based multi-modal wireless sensor network which leverages benefits of both radio frequency and acoustic communication systems for ocean monitoring. We first present the software-defined networking-based multi-modal network architecture, and then explore two examples of applications with this architecture: network deployment and coverage for intrusion detection with both grid-based and random deployment scenarios, and a novel underwater testbed design by incorporating radio frequency–acoustic multi-modal techniques to facilitate marine sensor network experiments. Finally, we evaluate the performance of deployment and coverage of software-defined networking-based multi-modal wireless sensor network through simulations with several scenarios to verify the effectiveness of the network.
Localization has always been an essential application of underwater acoustic sensor networks (UASNs), which plays an important role in routing strategies design, node recycling, and so on. The ...complex ocean condition, prior infrastructure deployment, and time synchronization among beacons challenge the application of the UASN's localization. To solve these problems, we propose a novel underwater acoustic sensor networks localization algorithm based on the virtual node assistance. The algorithm is classified into two parts based on the current marine environment, including Virtual node Assisted Static (VAS) localization algorithm and Virtual node Assisted Dynamic (VAD) localization algorithm. An auxiliary node, which does not directly participate in the localization, is deployed for virtual node setup, error measurement, and RSSI ranging. The GPS-equipped ship utilizes virtual node and geometry to realize the UASN's localization without complicated deployment procedures and time synchronization. The simulation results show that our proposed algorithm can achieve the properties, including high localization coverage and small localization error as well as low communication overhead in the UASNs.
Abstract MicroRNAs (miRNAs) play an important role in multiple biological processes, and many miRNAs have been shown to regulate cell proliferation and apoptosis. In this study, we investigated the ...role of miR-15b-5p in cell proliferation and apoptosis in PC12 cells. We found that overexpression of miR-15b-5p could decrease cell proliferation and induce apoptosis and cytotoxic activities in PC12 cells. Bioinformatics analysis and luciferase activities assays showed that miR-15b-5p might target extracellular signal-regulated kinase 1 (ERK1) by binding to its 3′-untranslated region (3′-UTR). Moreover, we also found that overexpression of ERK1 could attenuate the effects of miR-15b-5p in PC12 cells. Finally, our results suggest that miR-15b-5p might inhibit cell proliferation and induce apoptosis in PC12 cells by targeting ERK1.
Ship Detection with Wireless Sensor Networks Hanjiang Luo; Kaishun Wu; Zhongwen Guo ...
IEEE transactions on parallel and distributed systems,
07/2012, Letnik:
23, Številka:
7
Journal Article
Recenzirano
Surveillance is a critical problem for harbor protection, border control or the security of commercial facilities. The effective protection of vast near-coast sea surfaces and busy harbor areas from ...intrusions of unauthorized marine vessels, such as pirates smugglers or, illegal fishermen is particularly challenging. In this paper, we present an innovative solution for ship intrusion detection. Equipped with three-axis accelerometer sensors, we deploy an experimental Wireless Sensor Network (WSN) on the sea's surface to detect ships. Using signal processing techniques and cooperative signal processing, we can detect any passing ships by distinguishing the ship-generated waves from the ocean waves. We design a three-tier intrusion detection system with which we propose to exploit spatial and temporal correlations of an intrusion to increase detection reliability. We conduct evaluations with real data collected in our initial experiments, and provide quantitative analysis of the detection system, such as the successful detection ratio, detection latency, and an estimation of an intruding vessel's velocity.
Underwater acoustic sensor networks (UWA-SNs) are envisioned to perform monitoring tasks over the large portion of the world covered by oceans. Due to economics and the large area of the ocean, ...UWA-SNs are mainly sparsely deployed networks nowadays. The limited battery resources is a big challenge for the deployment of such long-term sensor networks. Unbalanced battery energy consumption will lead to early energy depletion of nodes, which partitions the whole networks and impairs the integrity of the monitoring datasets or even results in the collapse of the entire networks. On the contrary, balanced energy dissipation of nodes can prolong the lifetime of such networks. In this paper, we focus on the energy balance dissipation problem of two types of sparsely deployed UWA-SNs: underwater moored monitoring systems and sparsely deployed two-dimensional UWA-SNs. We first analyze the reasons of unbalanced energy consumption in such networks, then we propose two energy balanced strategies to maximize the lifetime of networks both in shallow and deep water. Finally, we evaluate our methods by simulations and the results show that the two strategies can achieve balanced energy consumption per node while at the same time prolong the networks lifetime.
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