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Due to the flammability, explosibility and toxicity of continuous objects (e.g. chemical gas, oil spill, radioactive waste) in petrochemical and nuclear industry, boundary tracking of continuous objects is becoming a critical issue for industrial wireless sensor networks (IWSNs) to achieve disaster reduction. In this article, we fully exploit the collective intelligence and machine learning capability of senor nodes, and propose a continuous objects boundary tracking algorithm for IWSNs. The proposed algorithm first determines an upper bound of the event region covered by continuous objects. A full binary tree-based partition is performed within the event region for coarse-grained boundary area mapping. To study the irregularity of continuous objects in detail, the boundary tracking problem is further transformed into a binary classification problem. A hierarchical soft margin support vector machines training strategy is designed to address the binary classification problem in a distributed fashion. Simulation results demonstrate that the proposed algorithm achieves high tracking accuracy with less boundary nodes. Without additional fault-tolerant mechanisms, the proposed algorithm is inherently robust to the false sensor readings reported by low proportion of faulty nodes, which is expected in harsh industrial environments.

Background This article aims to present research pertaining to the effect of angiotensin receptor-neprilysin double blocker on blocking the inflammatory mechanism mediated by NLRP3 inflammasome on hypertensive nephropathy. ARNI has not only been found to improve cardiac function but is also associated with a reduction in progressive deterioration of kidney function owing to hypertension by exerting anti-inflammation, anti-autophagy, anti-fibrosis and anti-Golgi’s apparatus. We hypothesized that administration of ARNI is more effective than valsartan alone in slowing progression of hypertensive renal disease. Methods Rat models with spontaneous hypertension were randomized into a no treatment group, valsartan group (60 mg/kg), ARNI group (70 mg/kg) or ARNI + A779 group (70 mg/kg + 400ng/kg) daily by gavage. Sprague-Dawley rats were subjected to the control conditions (without hypertension and treatment). The kidney tissue analyses were performed after 12 weeks. We detected the expression levels of NLRP3 and casepase-1 in kidney tissue, and NLRP3 levels in human embryonic kidney cells which were induced by ang II as hypertension cell model by Real-Time Polymerase Chain Reaction. To analyze the impact of ARNI on autophagy, we performed western blot analysis on renal tubules to measure the protein expression of NLRP3 inflammasome, and to measure the protein expression of P62 and LC3. Masson 3 staining method was used to stain renal fibrosis. Immunohistochemistry was performed to determine the expression sites of NLRP3. The Golgi apparatus in morphology of renal tubular cells was determined by transmission electron microscope. Results The untreated hypertensive renal disease rats exhibited tubular and glomerular damage, downregulation of pro-inflammatory, pro-autophagy, pro-fibrotic and pro-Golgi’s apparatus pathways. ARNI administration improved renal function and histology changes and attenuated most of the molecular markers of inflammation, autophagy, fibrosis and Golgi’s apparatus. Conclusions ARNI activation attenuates renal complications of arterial hypertension by reduction of kidney inflammation through selective actions requiring the renal tubular epithelium but not the glomerular endothelial cells and the circumferential mesangial interposition cell Angiotensin Receptor. ARNI was more effective than valsartan therapy alone in delaying the progression of hypertensive renal disease.

Underwater wireless sensor network (UWSN) is a typical application of wireless network in underwater environment, which mainly uses acoustic communication at present. However, due to the characteristics of high bit error rate, very limited bandwidth and high transmission delay, the data transmission collision of underwater communication is very serious. In order to reduce transmission collision and improve network performance, we propose a collision-free time slot scheduling MAC protocol based on multi-level quorum system for high loaded UWSNs. The proposed protocol can allocate different time slots for nodes in the same collision area, while realize space reuse for nodes in different collision areas. Considering the unbalanced data transmission of each node, a multi-level quorum system algorithm is constructed for fairness, which can allocate time slots on demand according to the data transmission amount of each node. In order to ensure reliable transmission of data, a light weight retransmission mechanism is designed to reduce the impact of long delay on channel duty cycle. Simulation results prove that the proposed MAC protocol can effectively avoid transmission collision, reduce transmission delay, improve system energy efficiency, and have good adaptability for different network topologies.

With the boost of ocean development, the study of UASNs has been gaining much attention from researchers. Nevertheless, UASNs are particularly vulnerable to malicious attacks because of their open and unattended nature. Hence, efficient and reliable security mechanisms are required to maintain the normal operation of UASNs. To defend against sudden network faults and malicious attacks, a novel trust model is proposed. The model is divided into three phases. First, a quantified environment model is developed to reflect the impact of the underwater environment on trust evaluation. Then, a trust update model is constructed based on reinforcement learning to confront hybrid attacks. Finally, a trust redemption model is given to reinstate low trust sensor nodes for improving resource utilization of the network. The experimental results prove that this trust model is effective in achieving highly efficient trust updating in the face of changing attack modes.

Among several new technologies, such as social and cognitive mobile computing, wireless sensor networks (WSNs) constitute the founding pillar of the industrial Internet of Things. These networks are expected to play an increasingly important role in our daily lives. Social and cognitive mobile computing requires the sharing of data recorded by sensor nodes. However, the data can be vulnerable to attacks. It is of utmost importance to protect the users privacy while ensuring the security of the WSNs. This investigation is focused on the source-location privacy (SLP) of WSNs. This article proposes a dynamic multipath privacy-preserving routing (DMPPR) scheme based on multiple sinks for protecting the privacy. Different from single sink schemes, the technique of using multiple sink nodes to protect SLP is discussed in this article. Furthermore, a packet-slicing transmission scheme that generates a large number of dynamic routings based on multiple sink nodes is adopted for transmitting the packets. Local adversaries are considered, and to cope with these adversaries, a transmission loop, constructed using real and fake packets, is proposed to confuse the adversaries during the source detection process. The aim is to break the sociality between the sensor nodes. Simulations performed in MATLAB show that the proposed method outperforms similar existing schemes in terms of the secure time, adversary’s capture probability, and node utilization ratio. Moreover, the DMPPR scheme also reduces energy consumption by allowing more nodes in the nonhotspot areas to participate in the packet transmission process.

Source location privacy (SLP) protection is an important means of security protection in wireless sensor networks (WSNs). With the development of underwater acoustic sensor networks (UASNs), security and privacy have attracted increasing attention. In this study, we incorporated SLP into UASNs as the basis for a novel stratification-based source location privacy (SSLP) scheme. In the SSLP scheme, SLP is protected through the cooperation of autonomous underwater vehicles (AUVs) in each network layer. Because fake source nodes and fake data streams are commonly used in WSNs, methods that have similar functions in UASNs are required. Hence, we incorporate a fake source node into the underwater cluster structure to add randomness to the underwater network. Furthermore, fake data streams have been included within the AUV data collection and transmission for each cluster. Simulation results confirm that the SSLP scheme offers improved security in comparison with existing underwater data transmission schemes.

Poisonous pollutants produced in chemical, plastics, or nuclear power industry are easy to leak and result in a large-scale hazardous event region. Recently, industrial wireless sensor networks (IWSNs) are intended to provide situational awareness in industry site and thus hold the promise of profiling the event region. However, low-cost nodes in IWSNs are prone to fail due to prolonged exposure to harsh environment. This article targets the detection of hazardous event region for IWSNs with faulty nodes. A fault-tolerant event region detection algorithm named TPE-FTED is proposed to formulate faulty nodes identification as a trajectory pattern extraction problem. Through online learning of probabilistic model, each node characterizes the distribution of sensing values under different sensing states. A specific set of probabilistic models can be formed as a trajectory which indicates something special happens. Based on the implicit knowledge from generated trajectories, TPE-FTED conducts pattern matching and checks spatiotemporal constraint to identify the declaration of faulty nodes. Simulation results demonstrate that TPE-FTED achieves low false alarm rate as well as high detection accuracy.

Background: Butaselen is an ebselen analog that is under clinical trials for treating hepatic and pulmonary fibrosis. Our previous studies showed that butaselen is mainly present in human plasma in the form of M2, a free Se-methylated metabolite. Objective: This study aimed to investigate the metabolic mechanisms of butaselen. Methods and Results: Butaselen was incubated with human plasma. Butaselen immediately disappeared, and the butaselen-HSA (human serum albumin) adduct was detected by HPLC-HRMS, showing that butaselen covalently binds to HSA. The butaselen-HSA adduct was precipitated using acetonitrile and then incubated with PBS, Cys, and GSH for 1 hour. The product was M1, a reduced form of butaselen. The results indicated that HSA, Cys, and GSH can reduce the butaselen-HSA covalent bond. The binding site for butaselen could be the cysteine-34 residue of HSA through pronase and trypsin hydrolysis. Incubating butaselen with cysteine, butaselen-Cys, butaselen-2Cys, and M1 were generated, indicating the covalent binding and reduction of butaselen by cysteine. We incubated liver microsomes and cytosol with butaselen, 6.22 and 246 nM M2 were generated, respectively. The results demonstrated that cytosolic enzymes are mainly involved in M2 production. The amount of M2 in the liver cytosol decreased from 246 nM to 2.21 nM when 10 mM m-anisic acid (a specific TPMT enzyme inhibitor) was added, showing that TPMT is responsible for M2 formation. Conclusion: Butaselen was covalently bound to HSA, and the binding site was the cysteine-34 residue of HSA. The butaselen-HSA adduct was reduced by free thiol compounds to generate M1. M1 was further metabolized to M2 by cytosolic TPMT. This study provides a basis for studying the pharmacokinetics of selenium-containing drugs.

BACKGROUND Gallbladder squamous cell carcinoma (GBSCC) is a rare subtype of malignancy and accounts for only 2%-3% of gallbladder malignancies. Due to its rapid development, most patients with GBSCC initially present with an advanced stage of the disease and hence a poor prognosis. The clinicopathological and biological features of SCC remain to be fully elucidated, owing to its uncommon occurrence. The majority of currently available data only described individual case reports or series analyses of trivial cases. CASE SUMMARY A 64-year-old man was admitted for progressively poor abdominal distension and pain. Liver computed tomography (CT) showed infiltration of gallbladder carcinoma into the adjacent liver, and enlarged retroperitoneal lymph nodes. The patient underwent radical cholecystectomy. Part of the mass was grey and soft, and the neoplastic section showed a purulent-necrotic lesion. Hematoxylin and eosin staining revealed a moderately differentiated SCC. Immunohistochemical studies showed strong staining of the tumor for AE1/3 and CK5/6. Staining for CK19, CK7, and CAM5.2 was positive in the cytoplasm. Systemic chemotherapy was not administered because of the patient’s poor physical condition. After five months, CT and magnetic resonance cholangiopancreatography showed multiple metastases in the liver and abdominal cavity. CONCLUSION Squamous components of GBSCC may explain the complex biological behavior, and CD109 may be involved in the pathogenesis.

Low-grade chondrosarcoma (LGC) is a very rare intracranial tumor, particularly in the sellar area. Herein, we describe an unusual case of LGC occurring in the sellar area. A 52-year-old man presented with diminution of vision for more than 3 months, but did not exhibit headaches reported in previous cases. MRI showed that the maximum size of the tumor was 7 cm on the left side of the saddle. We characterized the specific pathological characteristics. Histologically, the tumor had polypoid areas and a lobulated growth pattern under low-power examination. At high magnification, the tumor consisted of small cells with hyperchromatic nuclei in the cartilage matrix, with an alternating loose hypocellular zone and rich myxoid area. In our case, LGC needed to be distinguished from chordoma. Immunohistochemically, the tumor cells showed diffuse positivity for S-100 and vimentin, IDH1 was weakly cytoplasm positive. The Ki-67 labeling index was less than 5%. Additionally, AE1/3, EMA, and CK19 were negative, which could be used to exclude chordoma. This case report expands the literature on LGC and will help clinicians and pathologists better understand this entity.

Many studies have addressed the protection of source location privacy (SLP). However, most of the traditional research has not achieved a balance between security and energy consumption. Here, we propose a dynamic ring-based routing (DRBR) scheme to solve this problem. This scheme is divided into three stages. In the first stage, the source node randomly selects an intermediate node to send a data packet to the selected area. During the second stage, the intermediate node sends the data packet to the mixing ring, where the ring nodes combine data packets. The mixed data packets from the mixing ring are sent to the sink node in the third stage. We prove that DRBR not only provides high SLP, but also achieves a desirable trade-off between privacy and energy consumption.

Background The possible regulatory mechanism of MIR31HG in human cancers remains unclear, and reported results of the prognostic significance of MIR31HG expression are inconsistent. Methods The meta‐analysis and related bioinformatics analysis were conducted to evaluate the role of MIR31HG in tumor progression. Results The result showed that high MIR31HG expression was not related to prognosis. However, in the stratified analysis, we found that the overexpression of MIR31HG resulted in worse OS, advanced TNM stage, and tumor differentiation in respiratory system cancers. Moreover, our results also found that MIR31HG overexpression was related to shorter OS in cervical cancer patients and head and neck tumors. In contrast, the MIR31HG was lower in digestive system tumors which contributed to shorter overall survival, advanced TNM stage, and distant metastasis. Furthermore, the bioinformatics analysis showed that MIR31HG was highly expressed in normal urinary bladder, small intestine, esophagus, stomach, and duodenum and low in colon, lung, and ovary. The results obtained from FireBrowse indicated that MIR31HG was highly expressed in LUSC, CESC, HNSC, and LUAD and low in STAD and BLCA. Gene Ontology analysis showed that the co‐expressed genes of MIR31HG were most enriched in the biological processes of peptide metabolism and KEGG pathways were most enriched in Ras, Rap1, and PI3K‐Akt signaling pathway. Conclusion MIR31HG may serve as a potential biomarker in human cancers., Flow diagram of the study search and main results of the meta‐and bioinformatics analysis.

The advent of underwater acoustic sensor networks (UASNs) has enhanced marine environmental monitoring, auxiliary navigation, and marine military defense. One of the core functions of UASNs is data collection. However, current underwater data collection schemes generally encounter problems such as high energy consumption and high latency. Furthermore, the application of multiple autonomous underwater vehicles (AUVs) has contributed to more problems of task assignment and load balancing. This leads to significant failure in data collections and controlling of spontaneous emergencies. To address these problems, a district partition-based data collection algorithm with event dynamic competition in UASNs has been proposed. In this algorithm, the value of information of the packet determines the priority of its transmission to the cluster head. The navigation position of the mobile sink and the area under the responsibility of each AUV are determined by the spatial region division. The path of the AUV in the subregion is then planned using reinforcement learning. Subsequently, the dynamic competition of multiple AUVs is used to handle emergency tasks. The simulation demonstrates that our proposed algorithm significantly reduces energy consumption to guarantee load balancing while reducing end-to-end transmission delay.

Location of sensor nodes is one of the most important and fundamental information for Wireless Sensor Networks (WSNs), because it provides basic support for many location-based applications (e.g., navigation and object tracking) and location-aware protocols (e.g., geographic location-based routing protocols). However, by extracting and analyzing the location information in packets, attackers can easily obtain the real position of source nodes or base station using hop-by-hop backtracking strategy, which is extremely harmful for the normal operation of sensor networks. So, we need to provide location anonymity for sensor networks. In this paper, we present a detail survey of existing Location Privacy Protection (LPP) techniques in WSNs. First, the network model, the attack model and the performance evaluation model are reviewed. Then, this survey provides a review of the literature about location privacy protection, which is classified into the following three categories: 1) source nodes' location privacy preserving, 2) sink nodes' location privacy preserving, and 3) location privacy preserving for both source and sink nodes. The details of location privacy preserving protocols are carefully analyzed, and the key mechanisms in each protocol are elaborated. In addition, the performance, including the network safety period, the packet transmission latency and the energy consumption, is analyzed and compared. Finally, the exiting problems and the future research issues are presented.

BS1801 contains two selenium atoms in its structure, which is a specific inhibitor of thioredoxin reductase intended to treat fibrotic interstitial pneumonia (control pulmonary fibrosis) and liver fibrosis. It is currently in phase I clinical trial. However, there was no report about the metabolic transformation and pharmacokinetics of BS1801. In this study, BS1801 metabolites were characterized in the hepatocytes of different species (monkey, dog, mouse, rat, and human) and plasma specimens using the ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC/Q-TOF MS) method. After incubation, BS1801 could not be detected in the hepatocytes of different species and human plasma. Five metabolites were identified based on the characteristic peak clusters of selenium atoms in the mass spectrum, combined with the product ions obtained by MS-MS through collision-induced-dissociation (CID), including M1 (reduction metabolite), M2 (reduction and Se-methylation metabolite), M4 (M2 further oxidized metabolite) and M5 (Se-methylation and Se-glucuronidation conjugation metabolite), of which the amount of M2 was the highest. By comparing the LC-MS information with the synthesized reference substance, the structure of M2 was confirmed. The principal BS1801 metabolic pathways were identified as reduction and Se-methylation in humans. Subsequently, an accurate and fast LC-MS/MS method was established to verify the major metabolite M2 in human plasma. Acetonitrile-induced protein precipitation was employed to extract M2 from human plasma. The metabolite was separated through XDB-C

Background: The pharmacokinetics and appropriate dose regimens of favipiravir are unknown in hospitalized influenza patients; such data are also needed to determine dosage selection for favipiravir trials in COVID-19. Methods: In this dose-escalating study, favipiravir pharmacokinetics and tolerability were assessed in critically ill influenza patients. Participants received one of two dosing regimens; Japan licensed dose (1600 mg BID on day 1 and 600 mg BID on the following days) and the higher dose (1800 mg/800 mg BID) trialed in uncomplicated influenza. The primary pharmacokinetic endpoint was the proportion of patients with a minimum observed plasma trough concentration (Ctrough) ≥20 mg/L at all measured time points after the second dose. Results: Sixteen patients were enrolled into the low dose group and 19 patients into the high dose group of the study. Favipiravir Ctrough decreased significantly over time in both groups (p 80% of the duration of treatment of the two dose regimens evaluated (18.8% and 42.1% of patients for low and high dose regimen, respectively). Increasing the favipravir dosage predicted a higher proportion of patients reaching this threshold of 20 mg/L, suggesting that dosing regimens of ≥3600/2600 mg might be required for adequate concentrations. The two dosing regimens were well-tolerated in critical ill patients with influenza. Conclusion: The two dosing regimens proposed for uncomplicated influenza did not achieve our pre-defined treatment threshold.

Anorethidrani disuccinate (ACP) is a domestically designed A-decarbonized steroid that is currently being investigated in Phase I clinical trials for the treatment of solid tumors. Only the parent drug exhibited antitumor activity; its sterol metabolite M2 showed obvious antiestrogenic effects. We have developed a rapid, sensitive, and robust liquid chromatography–tandem mass spectrometry (LC-MS/MS) method for the direct quantification of ACP and a chemical derivatization method that can be used to quantify M2 derivatized with glycidyl trimethyl ammonium chloride (GTMA). A simple protein precipitation procedure was performed to quantify ACP. Injections were obtained within 3.5 min on an Eclipse Plus Phenyl-Hexyl column (50 mm × 2.1 mm i.d., 1.8 μm) with gradient elution; the calibration curve was linear over the range of 2.00–8000 ng/mL. For quantification of M2 in plasma, analytes were extracted by protein precipitation and converted to their GTMA derivatives at 60 °C for 2 h at pH 12; the analytes and coelutants were separated on a Luna C8(2) column (50 mm × 2.0 mm i.d., 5.0 μm). The precision (RSD) and accuracy (RE) of the intra- and interday determinations were within 10%. The derivatization procedure is a novel method for sterol determination by LC-MS/MS. The results confirmed the usefulness of this method for characterizing the pharmacokinetic profiles of ACP and its major metabolite M2 in a Phase I pharmacokinetic study.

Aim: This systematic review and meta-analysis aimed to analyze the association between cripto-1 expression and prognosis as well as clinicopathological features of non-small-cell lung cancer (NSCLC) patients. Methods: The electronic databases for all articles about NSCLC and cripto-1 expression were searched. Results: Twelve articles were enrolled in this meta-analysis (3130 samples). In NSCLC patients, cripto-1 was expressed higher than in normal tissues. Cripto-1 expression was closely correlated with lymph node metastasis, histological differentiation and advanced clinical stage of NSCLC patients, but not related to smoking, age and gender. Pooled hazard ratios found that high cripto-1 expression had poor overall survival and progression-free survival. Conclusion: Cripto-1 could serve as a novel biomarker for predicting poor prognosis in NSCLC patients.

With the boost of IoT, WSNs have been a well-liked know-how. However, due to WSNs' open and unmonitored nature, security vulnerabilities pose a significant problem. In this article, aiming at SLP, a major security problem, we propose the CASLP protection scheme in WSNs for IoT. To increase the scope of the transmitting path, the source starts the random walk in a given direction. Then, to maintain CASLP convergence, nodes only select their next relay nodes in a specific range. Last, to further improve SLP, we concatenate arcs from several rings around the sink to form a new closed loop. Compared to a ringbased routing scheme, CASLP can reduce delays and energy consumption at the minor expense of safety time in WSNs.

Background Rhabdomyosarcoma (RMS), a common soft-tissue malignancy in pediatrics, presents high invasiveness and mortality. However, besides known changes in the PAX3/7-FOXO1 fusion gene in alveolar RMS, the molecular mechanisms of the disease remain incompletely understood. The purpose of the study is to recognize potential biomarkers related with RMS and analyse their molecular mechanism, diagnosis and prognostic significance. Methods The Gene Expression Omnibus was used to search the RMS and normal striated muscle data sets. Differentially expressed genes (DEGs) were filtered using R software. The DAVID has become accustomed to performing functional annotations and pathway analysis on DEGs. The protein interaction was constructed and further processed by the STRING tool and Cytoscape software. Kaplan–Meier was used to estimate the effect of hub genes on the ending of sarcoma sufferers, and the expression of these genes in RMS was proved by real-time polymerase chain reaction (RT-PCR). Finally, the expression of CDK1 and CCNB1 in RMS was validated by immunohistochemistry (IHC). Results A total of 1932 DEGs were obtained, amongst which 1505 were up-regulated and 427were down-regulated. Up-regulated genes were largely enriched in the cell cycle, ECM-receptor interaction, PI3K/Akt and p53 pathways, whilst down-regulated genes were primarily enriched in the muscle contraction process. CDK1, CCNB1, CDC20, CCNB2, AURKB, MAD2L1, HIST2H2BE, CENPE, KIF2C and PCNA were identified as hub genes by Cytoscape analyses. Survival analysis showed that, except for HIST2H2BE, the other hub genes were highly expressed and related to poor prognosis in sarcoma. RT-PCR validation showed that CDK1, CCNB1, CDC20, CENPE and HIST2H2BE were significantly differential expression in RMS compared to the normal control. IHC revealed that the expression of CDK1 (28/32, 87.5%) and CCNB1 (26/32, 81.25%) were notably higher in RMS than normal controls (1/9, 11.1%; 0/9, 0%). Moreover, the CCNB1 was associated with the age and location of the patient’s onset. Conclusions These results show that these hub genes, especially CDK1 and CCNB1, may be potential diagnostic biomarkers for RMS and provide a new perspective for the pathogenesis of RMS.

Single-instruction-set architecture (Single-ISA) heterogeneous multi-core processors (HMP) are superior to Symmetric Multi-core processors in performance per watt. They are popular in many aspects of the Internet of Things, including mobile multimedia cloud computing platforms. One Single-ISA HMP integrates both fast out-of-order cores and slow simpler cores, while all cores are sharing the same ISA. The quality of service (QoS) is most important for virtual machine (VM) resource management in multimedia mobile computing, particularly in Single-ISA heterogeneous multi-core cloud computing platforms. Therefore, in this paper, we propose a dynamic cloud resource management (DCRM) policy to improve the QoS in multimedia mobile computing. DCRM dynamically and optimally partitions shared resources according to service or application requirements. Moreover, DCRM combines resource-aware VM allocation to maximize the effectiveness of the heterogeneous multi-core cloud platform. The basic idea for this performance improvement is to balance the shared resource allocations with these resources requirements. The experimental results show that DCRM behaves better in both response time and QoS, thus proving that DCRM is good at shared resource management in mobile media cloud computing.

Nowadays, mini-drones, officially called unmanned aerial vehicles, are widely used in many military and civilian fields. Compared to traditional ad hoc networks, the mobile ad hoc networks established by UAVs are more efficient in completing complex tasks in harsh environments. However, due to the unique characteristics of UAVs (e.g., high mobility and sparse deployment), existing protocols or algorithms cannot be directly used for UAVs. In this article, we focus on the routes designed for UAVs, and aim to present a somewhat complete survey of the routing protocols. Moreover, the performance of existing routing protocols is compared in detail, which naturally leads to a great number of open research problems that are outlined afterward.

Localization is one of the fundamental issues in Wireless Sensor Networks (WSNs). Recently, various localization methods have been proposed. However, using single anchor node introduces quite long localization delay. Therefore, the path planning problem of a Group of Mobile Anchor Nodes (GMAN) is studied in this paper. First, two path planning schemes named GSCAN and GTURN are proposed. Both GSCAN and GTURN use three mobile anchor nodes which traverse the entire network following the designed trajectory to help nearby unknown nodes with localization. Furthermore, in order to improve localization ratio of unknown nodes, two boundary strategies are proposed to guarantee that the movement trajectories of anchor nodes can cover the whole WSN. Simulation results show that GSCAN and GTURN can achieve better localization performance than LMAT, RPGM and Ou’s in terms of higher localization ratio and lower energy consumption.

The increasing demand on the main memory capacity is one of the main big data challenges. Dynamic random access memory (DRAM) does not represent the best choice for a main memory, due to high power consumption and low density. However, the nonvolatile memory, such as the phase-change memory (PCM), represents an additional choice because of the low power consumption and high-density characteristic. Nevertheless, the high access latency and limited write endurance have disabled the PCM to replace the DRAM currently. Therefore, a hybrid memory, which combines both the DRAM and the PCM, has become a good alternative to the traditional DRAM memory. Both DRAM and PCM disadvantages are challenges for the hybrid memory. In this paper, a dynamic adaptive replacement policy (DARP) in the shared last-level cache for the DRAM/PCM hybrid main memory is proposed. The DARP distinguishes the cache data into the PCM data and the DRAM data, then, the algorithm adopts different replacement policies for each data type. Specifically, for the PCM data, the least recently used (LRU) replacement policy is adopted, and for the DRAM data, the DARP is employed according to the process behavior. Experimental results have shown that the DARP improved the memory access efficiency by 25.4%.

1. Anordrin (2α, 17α-diethynyl-A-nor-5α-androstane-2β, 17β-diol diproprionate) is post-coital contraceptive drug that is on the market in China for more than 30 years. This study aims to elucidate enzymes involved in anordrin hydrolysis, and to evaluate the significant role of carboxylesterases in anordrin hydrolysis in humans. 2. Human liver and intestinal microsomes, recombinant human carboxylesterase were selected as enzyme sources. In human liver microsomes, intrinsic clearance was 684 ± 83 μL/min/mg protein, which was considerably higher than the value of intestine microsomes (94.6 ± 13.3 μL/min/mg protein). Carboxylesterase (CES) 1 has more contribution than CES2 in human liver. 3. Inhibition studies were performed using representative esterase inhibitors to confirm esterase isoforms involved in anordrin hydrolysis. Simvastatin strongly inhibited hydrolytic process of anordrin in liver and intestine microsomes, with IC50 values of 10.9 ± 0.1 and 6.94 ± 0.03 μM, respectively. 4. The present study investigated for the first time hydrolytic enzyme phenotypes of anordrin. Anordrin is predominantly catalyzed by CES1 and CES2 to generate the main active metabolite, anordiol. Moreover, anordrin and its metabolite anordiol can be altered by esterase inhibitors, such as simvastatin, upon exposure in vivo.

Synovial sarcoma (SS) is an aggressive soft tissue tumor, with uncertain histological and cellular origin. SYT-SSX is considered to be responsible for sarcoma initiation and progression. The histogenesis and pathogenesis of this tumor are poorly understood, and prognosis of patients of SS is unsatisfactory. Recent studies have shown an association of cancer stem cells with the initiation and development of tumors. We explored immunohistochemical expression level of stem cell associated markers to determine the possible histogenesis and pathogenesis of SS. Fusion gene SYT-SSX was tested to assess diagnostic value and the molecular pathological features. We obtained the clinicopathological data of 20 SS patients, immunohistochemical staining were used to evaluate stem cell-associated markers included CD133, CD29, CD44, nestin, and ALDH1. Fusion gene SYT-SSX was tested by reverse transcriptase-polymerase chain reaction (RT-PCR). Twenty SS cases were observed and the positive immuno-expression results showed CD133 (17/20), CD29 (11/20), CD44 (11/20), nestin (6/20), and ALDH1 (5/20). Fusion gene SYT-SSX was successfully detected by RT-PCR from 18 available samples. The expression of stem cell-associated markers (CD133, CD29, CD44, Nestin, and ALDH1) and clinical data (age, gender, sites, tumor size, histological type, tumor stage, and distant metastases) did not show statistically significant relationship (P>0.05), whereas, statistically significance between ALDH1 and metastases was observed (P

Motivated by the improvement of the localization performance and the utilization rate of virtual beacons in heterogeneous WSNs, in this paper, we propose three Mobile Anchor nodes Path Planning (MAPP) algorithms, namely, IMAPPP-NDC, SMAPP-NDC and MMAPP-NDC. Different from most of the existing MAPP algorithms which divide the region of interest (ROI) into several layers or areas and make mobile anchor nodes traverse the ROI layer by layer or one area after another, the proposed MAPP algorithms combine network-density-based clustering, inter-cluster path planning and intra-cluster path planning together to improve localization performance and the utilization rate of virtual beacons based on the mathematical analysis of the relationship between the communication range r of a sensor node and the side length a of the regular hexagon movement trajectory. In addition, SMAPP-NDC and MMAPP-NDC algorithms employ obstacle avoidance mechanisms to steer clear of obstacles and provide non-collinear beacon points around obstacles.

In mobile communication, the signal that a base station received cannot be regarded as a point source anymore because of the multipath propagation. A distributed source model is more suitable for the realistic scenarios. In this paper, an approach of direction-of-arrival (DOA) estimation is proposed for coherently distributed (CD) sources consisting of circular and noncircular signals in a massive or large-scale multiple-input multiple-output system. The noncircular characteristic can improve the performance of DOA estimation. However, most algorithms are not suitable for DOA estimation where circular and noncircular signals coexist. Based on the analysis of constraint conditions satisfied by the steering vector of mixed signals, a multiple signal classification (MUSIC) like approach is proposed for the DOA estimation of CD sources consisting of circular and noncircular signals. On the conditions of low signal-to-noise ratio, small snapshot numbers, and large source numbers, the pseudopeaking may appear. This phenomenon has been analyzed, and a modified MUSIC-like approach is proposed. Simulation results demonstrate that both two proposed algorithms can estimate more sources than the number of sensors. The estimation performances of the two proposed algorithms outperform the traditional MUSIC algorithm.

Nowadays, the study of underwater WSNs (UWSNs) has become a hot topic. However, UWSNs have not been fully utilized in the complex underwater environment, since there are some difficulties in controlling mobile sensor nodes and underwater environment conditions. In addition, how to ensure the security of UWSNs and the safety of underwater mobile sensor nodes has not been solved well. In this article, we study the problem of trust establishment between nodes in UWSNs. We first give a detailed overview of existing trust management mechanisms. Since UWSNs possess specific characteristics, it is noted that those existing mechanisms are not applicable for UWSNs. We then introduce a trust cloud model that is suitable for trust management in UWSNs.

In Device-to-Device (D2D) communications of massive Multiple-Input Multiple-Output (MIMO) system, the inter-channel interference (ICI) can severely deteriorate the entire system performance. The beamforming technique can be used to alleviate this situation. Thus the localization of the users’ equipment (UE) should be known as a prior. In wireless communication, due to the effect of multipath, the model of incident signal should be regarded as distributed sources instead of point sources. In this paper, we propose a 2-D DOA estimation algorithm for coherently distributed (CD) sources based on conformal array. First, three rational invariance relationships are constructed based on generalized steering vectors (GSVs). Then the propagator method (PM) is used for estimating three rational invariance matrices. Finally, the 2-D DOA of CD sources can be obtained from the eigenvalues of three rational invariance matrices. Without spectrum peaking searching, and estimation and eigendecomposition of sampling covariance matrix, the proposed algorithm has low computational complexity. For the condition with a large amount of data, the distributed and parallel PM is proposed to deal with this problem. Simulation results verify the effectiveness of the proposed algorithm.

Underwater acoustic sensor networks (UASNs) are susceptible to a large number of security threats, e.g., jamming attacks at the physical layer, collision attacks at the data link layer, and DoS attacks at the network layer. Because of the communication, computation, and storage constraints of underwater sensor nodes, traditional security mechanisms, e.g., encryption algorithms, are not suitable for UASNs. A trust model has been recently suggested as an effective security mechanism for open environments such as terrestrial wireless sensor networks (TWSNs), and considerable research has been done on modeling and managing trust relationships among sensor nodes. However, the trust models proposed for TWSNs cannot be directly used in a UASN due to its unique characteristics such as unreliable acoustic channel, dynamic network structure, and weak link connectivity. In this paper, we propose a novel trust model based on cloud theory (TMC) for UASNs. The objective of TMC is to solve uncertainty and fuzziness of trust based on cloud theory, which ultimately improves trust evaluation accuracy. Moreover, simulation results demonstrate that our algorithm outperforms other related works in terms of detection ratio of malicious nodes, successful packet delivery ratio, and network lifetime.

Recent breakthroughs in wireless technologies have greatly spurred the emergence of industrial wireless sensor networks (IWSNs). To facilitate the adaptation of IWSNs to industrial applications, concerns about networks’ full coverage and connectivity must be addressed to fulfill reliability and real-time requirements. Although connected target coverage (CTC) algorithms in general sensor networks have been extensively studied, little attention has been paid to reveal both the applicability and limitations of different coverage strategies from an industrial viewpoint. In this paper, we analyze characteristics of four recent energy-efficient coverage strategies by carefully choosing four representative connected coverage algorithms: 1) communication weighted greedy cover; 2) optimized connected coverage heuristic; 3) overlapped target and connected coverage; and 4) adjustable range set covers. Through a detailed comparison in terms of network lifetime, coverage time, average energy consumption, ratio of dead nodes, etc., characteristics of basic design ideas used to optimize coverage and network connectivity of IWSNs are embodied. Various network parameters are simulated in a noisy environment to obtain the optimal network coverage. The most appropriate industrial field for each algorithm is also described based on coverage properties. Our study aims to provide IWSNs designers with useful insights to choose an appropriate coverage strategy and achieve expected performance indicators in different industrial applications.

Data collection is the core function of underwater acoustic sensor networks (UASNs). Lately, ambulatory data gathering methods are being popularized in real applications. However, due to present mobile underwater data collection investigations that are on the basis of 2-D scenarios, the associated approaches are not suitable for 3-D UASNs. Additionally, mobile-element-assisted data collection usually brings special issues on obstacle avoidance. Accordingly, we propose a probabilistic neighborhood location-point covering set-based data collection algorithm with obstacle avoidance for 3-D UASNs. The proposed algorithm initially generates a space lattice set to establish the probabilistic neighborhood location-point covering set for data collection, so as to optimize the data collection latency. Then, an autonomous underwater vehicle traverses only location points in the constructed covering set with a hierarchical grid-based obstacle avoidance strategy. The simulation experiments are performed to verify the proposed algorithm compared with other existing underwater data collection algorithms. Simulations show that our proposed algorithm achieves better performance in terms of data collection latency, data collection efficiency, and obstacle avoidance.

Wireless multimedia sensor networking (WMSN) is an efficient technology and has been widely used in multimedia data transport and applications. The key to the success of multimedia data transport is the transmission quality. Real-time critical multimedia requires efficient routing for data delivery with guaranteed QoS. However, satisfying the stringent QoS requirements of multimedia transmission usually translates to high energy consumption. How to efficiently minimize the energy consumption while ensuring QoS requirements is an acute problem. Therefore, in this article, we call routing protocols that can balance out the trade-off between network lifetime and QoS requirements “green routing protocols.” First, a detailed survey of existing routing protocols for WMSNs is presented, which are classified into two categories based on network structures. Moreover, the performance of existing routing protocols is compared in detail. Finally, future research issues of green routing protocols in WMSNs are presented and carefully discussed.

Ewing's sarcoma (ES) is a small cell malignant tumor that occurs in the bone of children or adolescents. ES can also occur in extraskeletal organs, such as the pancreas, thyroid, liver, proximal phalanx, and, rarely, cervix. Only 15 published case reports have discussed ES arising in the cervix. We report a 76-year-old woman who had groin mass. ES was diagnosed in accordance with morphological and immunohistochemical maps. Fluorescence in situ hybridization and RT-PCR (reverse transcription PCR) revealed ESWR1 gene rearrangement and fusion gene formation (EWS-FLI-1), both of which confirmed the diagnosis of ES. Although the patient underwent surgical resection, the patient died without chemotherapy and radiotherapy. This case is the first one to involve a patient aged over 70 years and the fifth one to show metastasis occurrence.

Objective: Liposarcoma is a mesenchymal malignant tumor characterized by adipocyte differentiation which is divided into four subtypes with different prognosis. Accurate histopathological diagnosis is essential for precise treatment. Perilipins, including PLIN1, PLIN2, PLIN3, PLIN4, PLIN5, is a family of lipid droplet-associated proteins that participate in lipid metabolism regulation. The role that perilipins play in sarcomas is not clear. This study aims to assess perilipins expression in subtypes of liposarcoma and various non-lipomatous sarcomas. Methods: A large set of 245 soft tissue sarcoma paraffin-embedded samples including 66 liposarcomas and 179 non-lipomatous sarcomas were collected for tissue microarray and immunohistochemistry to assess perilipins expression. Results: PLIN1 expression was shown in most liposarcomas (41/66) and was absent in non-lipomatous sarcomas (0/179). PLIN4 expression was shown in some liposarcomas (21/66) and was almost negative in non-lipomatous sarcomas (2/179). PLIN1 and PLIN4 expressions in liposarcoma were higher (both P

Ketamine is an N-methyl-d-aspartate receptor antagonist that is usually used clinically as a racemic mixture. Its two enantiomers exhibit different pharmacological activities. To determine whether the enantiomers have different pharmacokinetic profiles, a chiral liquid chromatography-tandem mass spectrometry method was developed and validated for the determination of ketamine enantiomers in dog plasma. The enantiomers of ketamine were extracted from 50 μL of plasma by methyl tert-butyl ether. Adequate chromatographic retention and baseline resolution of the enantiomers were achieved within a runtime of 5 min on a chiral column coated with polysaccharide derivatives, using a gradient mobile phase of acetonitrile and 10 mm ammonium bicarbonate aqueous solution. Ketamine enantiomers were detected by mass spectrometry with multiple reaction monitoring mode using the transitions of m/z 238.3 → 125.9 for the analytes and m/z 237.1 → 194.1 for carbamazepine (internal standard). The method was linear over the concentration range from 0.5 to 500 ng/mL for each enantiomer. The lower limit of quantification (LLOQ) for each enantiomer was 0.5 ng/mL. The intra- and inter-day precision was

Additional file 2: Table S2. DEGs between RMS and normal striated muscle samples.