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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.

Mitogen-activated protein kinase kinase kinase 3 (MAP3K3), a member of the serine/threonine protein kinase family, is ubiquitously expressed and acts as an oncogene. However, the expression and exact molecular mechanism of MAP3K3 in ovarian carcinoma (OC) remain unclear. Here, we found that MAP3K3 protein was highly expressed in 70.5% of high-grade serous ovarian carcinoma (HGSOC) samples. MAP3K3 overexpression was significantly associated with the FIGO stage and chemotherapy response. Additionally, MAP3K3 overexpression was associated with reduced disease-free survival and overall survival. In vitro experiments showed that MAP3K3 overexpression promoted cell proliferation, inhibited apoptosis, and enhanced the migration and invasion of OC cells. Moreover, in vivo tumourigenesis experiments confirmed that silencing MAP3K3 significantly reduced the growth rate and volume of transplanted tumours in nude mice. Drug sensitivity experiments demonstrated that differential expression of MAP3K3 in OC cell lines correlates with chemotherapy resistance. Functionally, the MAP3K3 gene regulated the malignant biological behaviour of OC cells by mediating NF-κB signalling pathways, affecting the downstream epithelial-mesenchymal transition and cytoskeletal protein expression. Our results unveiled the role of MAP3K3 in mediating NF-κB signalling to promote the proliferation, invasion, migration, and chemotherapeutic resistance of OC cells, highlighting a potential new therapeutic and prognostic target.

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.

Outlier detection in the Internet of Things (IoT) is an essential challenge issue studied in numerous fields, including fraud monitoring, intrusion detection, secure localization, trust management, and so on. Conventional outlier detection technologies cannot be used directly in IoT due to the open nature of wireless communication as well as the resource-constrained characteristics of end nodes. Therefore, this article provides a comprehensive survey of new outlier detection approaches based on machine learning for IoT. The approaches are first carefully discussed based on their adopted machine learning algorithms. In addition, the performance of them with respect to the advantages and the drawbacks are compared in detail, which naturally leads to some open research issues that are analyzed afterward. The work is supported by the National Key Research and Development Program, No. 2017YFE0125300, the National Natural Science Foundation of China-Guangdong Joint Fund under Grant No. U1801264, the Jiangsu Provincial Six Talent Peaks Project No. XYDXX-012 and the Jiangsu Key Research and Development Program, No. BE2019648 , and Project of Fujian University of Technology, No. GY-Z19066.

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.

Recent breakthroughs in wireless charging technologies have greatly promoted the development of rechargeable wireless sensor networks (WSNs). To improve the lifetime of WSNs in many applications, the charging efficiency of mobile chargers (MCs) and the energy supplement of MCs should be improved. Although optimized charging path schemes in WSNs have been studied extensively, little attention has been paid to determine the energy consumption of MCs while charging and their movement during the charging tasks. In this paper, we analyze the relationship of the movement energy consumption of MCs and their energy transfer to the nodes and put forward our algorithm for improving the charging efficiency of the MCs. We divide the entire network into different charging regions and propose three charging schemes based on different situations in each region. The idea of cooperation among the MCs to charge MCs further enhances the charging efficiency of the MCs. A simulation demonstrates the advantages of our algorithm for improving the lifetime and charging efficiency of the MCs. This paper aims to improve the lifetime of WSNs and to decrease the cost for charging nodes and results in a longer lifetime for WSNs in applications with limited energy.

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

Underwater acoustic sensor networks (UASNs) have been widely applied in underwater scenarios where numerous anchoring or floating sensor nodes collaborate in performing some specific assignments, such as information collection or data transmission. In recent years, the trust model has been known as an important tool in responding to attackers inside the network. Although there are a number of trust models recently been suggested as effective methods for terrestrial networks, it is infeasible to directly apply these trust models in UASNs due to the complex underwater environment and the unreliable underwater acoustic communication. For the purpose of achieving accurate and robust trust evaluation for UASNs, a synergetic trust model based on SVM (STMS) is proposed in this paper. The network is divided into a certain number of interconnected clusters in which cluster heads and cluster members (CMs) are synergetic to perform functions. The STMS is mainly comprised of three parts. In the first part, three kinds of trust evidences, which are refined elaborately to reflect most of the attack results, are generated by CMs. In the second part, the support vector machine (SVM) technology is adopted in training a trust prediction model for evaluating accurate trust value. Furthermore, the mechanism of double cluster heads is presented to improve network security and lifetime in the third part. Simulation results demonstrate that STMS performs better than other related works in the sparse deployment environment, which is reflected in the aspect of detect accuracy of malicious nodes, success rate of communication and network lifetime. - 1967-2012 IEEE. Manuscript received May 3, 2019; revised July 16, 2019; accepted August 25, 2019. Date of publication September 3, 2019; date of current version November 12, 2019. The work was supported in part by the National Key Research and Development Program under Grant 2018YFC0407900, in part by the National Natural Science Foundation of China under Grants 61572172, 61602152, and 61872124, and in part by the Open fund of State Key Laboratory of Acoustics under Grant SKLA201901. The review of this article was coordinated by Prof. J. Weng. (Corresponding author: Guangjie Han.) G. Han, Y. He, and J. A. Ansere are with the College of Internet of Things Engineering, Hohai University, Changzhou 213022, China (e-mail: hanguangjie@gmail.com; heyuhhu2018@outlook.com; jaansere@hhu.edu.cn). Scopus

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

The past years have seen a rapid development of autonomous underwater vehicle-aided (AUV-aided) data-gathering schemes in underwater acoustic sensor networks (UASNs). The use of AUVs efficiently reduces energy consumption of sensor nodes. However, all AUV-aided solutions face severe problems in data collection delay, especially in a large-scale network. In this paper, to reduce data collection delay, we propose a prediction-based delay optimization data collection algorithm (PDO-DC). On the contrary to the traditional delay optimization algorithms, Kernel Ridge Regression (KRR) is utilized via cluster member nodes to obtain the corresponding prediction models. Then, the AUV can obtain all cluster data by traversing less cluster head nodes, which can effectively reduce the collection delay of the AUV. The experimental results demonstrate that the proposed method is both feasible and effective. - 2019 IEEE. Manuscript received December 10, 2018; revised March 19, 2019; accepted April 27, 2019. Date of publication May 2, 2019; date of current version July 16, 2019. The work was supported in part by the National Key Research and Development Program, 2018YFC0407900 and in part by the National Natural Science Foundation of China under Grants 61572172, 61602152, and 61872124, and in part by the Open Fund of State Key Laboratory of Acoustics under Grant SKLA201901. The review of this paper was coordinated by Dr. P. Lin. (Corresponding author: Guangjie Han.) G. Han and S. Shen are with the Department of Information and Communication Systems, Hohai University, Changzhou 213022, China (e-mail: hanguangjie@gmail.com; shensongjiehhuc@outlook.com). Scopus

Background The replacement of hydrogen with deuterium invokes a kinetic isotope effect. Thus, this method is an attractive way to slow down the metabolic rate and modulate pharmacokinetics.

As an extension of wireless sensor network in underwater environment, underwater acoustic sensor networks (UASNs) have caused widespread concern of academia. In UASNs, the efficiency and reliability of data transmission are very challenging due to the complex underwater environment in variety of ocean applications, such as monitoring abnormal submarine oil pipelines. Motivated by the importance of energy consumption in many deployments of UASNs, we therefore propose an energy-efficient data transmission scheme in this paper, called energy-efficiency grid routing based on 3D cubes (EGRCs) in UASNs, considering the complex properties of underwater medium, such as 3D changing topology, high propagation delay, node mobility and density, as well as rotation mechanism of cluster-head nodes. First, the whole network model is regarded as a 3D cube from the grid point of view, and this 3D cube is divided into many small cubes, where a cube is seen as a cluster. In the 3D cube, all the sensor nodes are duty-cycled in the media access control layer. Second, in order to make energy efficient and extend network lifetime, the EGRC shapes an energy consumption model considering residual energy and location of sensor nodes to select the optimal cluster-heads. Moreover, the EGRC utilizes residual energy, locations, and end-to-end delay for searching for the next-hop node to maintain the reliability of data transmission. Simulation validations of the proposed algorithm are carried out to show the effectiveness of EGRC, which performs better than the representative algorithms in terms of energy efficiency, reliability, and end-to-end delay.

Wireless charging techniques provide a more flexible and promising way to solve the energy constraint problem in industrial wireless rechargeable sensor networks (IWRSNs). Although considerable research has been done on wireless charging algorithms, most of it only focuses on passively replenishing nodes having insufficient energy. In this paper, we propose a grid-based joint routing and charging algorithm for IWRSNs to solve the charging problem in a proactive way. On the one hand, a new routing protocol is designed according to charging characteristics of the charger to achieve local energy balance. On the other hand, different charging times are allocated at different charging points on the basis of energy consumption caused by the routing process to achieve global energy balance. Simulation results verify superiority of our proposed algorithm in solving the balancing energy problem and improving survival rates of nodes.

Mitogen-activated protein kinase kinase kinase 3 (MAP3K3) is ubiquitously expressed in numerous tissues and is activated by various extracellular stimuli to regulate processes, such as cell proliferation and differentiation. Recent studies have identified potentially pathologic conditions of MAP3K3 as an oncogene that promotes tumor progression and metastasis in a number of malignancies. However, the clinical significance of MAP3K3 expression in ovarian carcinoma (OC) remains unclear. In this study, the correlation between MAP3K3 expression and OC prognosis was assessed by immunohistochemistry. MAP3K3 overexpression was observed in 59.1% (55/93) of OCs and was significantly associated with histological type and grade, chemotherapy response, and challenge model (P < .05, respectively). MAP3K3 overexpression was also used as an independent prognostic marker for decreased disease-free survival and overall survival. In OC cell lines, MAP3K3 expression was evaluated by Western blot analysis, quantitative real-time polymerase chain reaction, and immunofluorescence. High MAP3K3 expression is significantly detected in SKOV3, C13*, and A2780 cells. All these findings suggested that MAP3K3 overexpression is an independent poor prognostic indicator of OC and can be a clinically effective biomarker of OC.

In Underwater Wireless Sensor Networks (UWSNs), the geographic routing is a preferred choice for data transmission due to the unique characteristics of underwater environment such as the three dimensional topology, the limited bandwidth and power resources. This paper focuses on underwater routing protocols in the network layer, where underwater sensor nodes can collaborate with each other to transfer data information. The three dimensional underwater network is first divided into small cube spaces, thus data packets are supposed to be collaboratively transmitted by unit of small cubes logically. By taking complex properties of underwater medium into consideration such as three dimensional topology, high propagation delay and path loss of acoustic channel, we propose two novel multi-path strategies called Greedy Geographic Forwarding based on Geospatial Division (GGFGD) and Geographic Forwarding based on Geospatial Division (GFGD). The proposed two algorithms mainly consist of two phases, choosing the next target small cube, and choosing the next hop node in the target small cube. Furthermore, all the sensor nodes in the network are duty-cycled in the MAC layer. Finally, performance analysis is derived, and simulation results illustrate the performance improvement in finding route paths, optimal length of found paths. In addition, energy consumption of route finding is reduced and propagation delay of data transmission is decreased. HighlightsIn this paper, two geographic multipath routing algorithms named GGFGD and GFGD were proposed.First, the network is logically divided into Small Cube (SC) spaces.Then, based on the SCs and the relative position of sensor nodes, some target SCs are selected.Only the neighbor nodes in the selected target SCs are used for data directional transmission.Moreover, we take sleep schedule into account, which helps to save energy consumption and prolong network lifetime.

Localization is one of the key technologies in wireless sensor networks (WSNs), since it provides fundamental support for many location-aware protocols and applications. Constraints on cost and power consumption make it infeasible to equip each sensor node in the network with a global position system (GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use mobile anchor nodes (MANs), which are equipped with GPS units moving among unknown nodes and periodically broadcasting their current locations to help nearby unknown nodes with localization. A considerable body of research has addressed the mobile anchor node assisted localization (MANAL) problem. However, to the best of our knowledge, no updated surveys on MAAL reflecting recent advances in the field have been presented in the past few years. This survey presents a review of the most successful MANAL algorithms, focusing on the achievements made in the past decade, and aims to become a starting point for researchers who are initiating their endeavors in MANAL research field. In addition, we seek to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful advances in this research field.

As the smart cities emerged for more comfortable urban spaces, services, such as health, transportation, and so on, need to be promoted. In addition, the cloud computing provides flexible allocation, migration of services, and better security isolation; therefore, it is the infrastructure for the smart cities. Single instruction-set architecture (ISA) heterogeneous multi-core processors have higher performance per watt than their symmetric counterparts and are popular in current processors. In current cloud computing, which integrates a few fast out-of-order cores, coupled with a large number of simpler, slow cores, all cores expose the same ISA. The best way to leverage the effectiveness of these systems is to accelerate sequential CPU-bound threads using fast cores, and to improve the throughput of parallel memory-bound threads using slow cores. However, shared hardware resources, such as memory, respond to requests from all cores, which interfere with each other, leading to both low speed for fast cores and low throughput for slow cores. In this paper, we propose a dynamic resource partitioning (DRP) method for single-ISA heterogeneous multi-cores, which partitions the shared resources according to both threads’ requirements for the shared resources and the performance of their running cores. The key principle is to profile both threads’ resource characteristics at run-time and the performance of the cores that the threads are running on to estimate demands for resources. Then, we use the estimation to direct our resource partitioning. Moreover, we integrate our DRP with current memory scheduling policies to improve the system performance further for the two methods being orthogonal.

Underwater acoustic sensor networks (UASNs) have been widely used in many applications where a variable number of sensor nodes collaborate with each other to perform monitoring tasks. A trust model plays an important role in realizing collaborations of sensor nodes. Although many trust models have been proposed for terrestrial wireless sensor networks (TWSNs) in recent years, it is not feasible to directly use these trust models in UASNs due to unreliable underwater communication channel and mobile network environment. To achieve accurate and energy efficient trust evaluation in UASNs, an attack-resistant trust model based on multidimensional trust metrics (ARTMM) is proposed in this paper. The ARTMM mainly consists of three types of trust metrics, which are link trust, data trust, and node trust. During the process of trust calculation, unreliability of communication channel and mobility of underwater environment are carefully analyzed. Simulation results demonstrate that the proposed trust model is quite suitable for mobile underwater environment. In addition, the performance of the ARTMM is clearly better than that of conventional trust models in terms of both evaluation accuracy and energy consumption. Qing Lan Project, Natural Science Foundation of JiangSu Province of China, No. BK20131137, The Applied Basic Research Program of Nantong Science and Technology Bureau, No. BK2013032, National Science Foundation of China, No. 61401107 and Jiangsu Province Ordinary University Graduate Innovation Project, No. CXZZ13_02 Scopus

The growing gap between microprocessor speed and DRAM speed is a major problem that computer designers are facing. In order to narrow the gap, main memory is expected to grow significantly in both speed and capacity for it is a major shared resource among cores in a multi-core system, which will lead to increasing power consumption, perhaps replacing the dominant consuming fraction of processor. Therefore, it is critical to address the power issue without seriously decreasing performance in the main memory subsystem. In this paper, we propose a periodically active rank scheduling (PARS) to optimize power efficiency for DRAM in smart phones. Our scheduling features a three-step design. First, we partition all threads in the system into groups. Second, we modify page allocation policy to achieve threads in the same group which occupies the same rank but different banks of DRAM. Finally, we sequentially schedule threads in one group after another while only active running group׳s ranks to retain other ranks low power status. As a result, our scheduling periodically activates one rank after another to optimize memory power efficiency. We implement PARS in Linux 2.6.39 kernel running randomly generated workloads containing single-threaded and multi-threaded benchmark. Experimental results show that PARS can improve both the memory power efficiency by 26.8% and performance by 4.2% average relative to default system while reducing negligible fairness.

Industrial wireless sensor networks (IWSNs) have been widely used in many application scenarios, and data collection is an extremely significant part of IWSNs. Moreover, a mobile sink is widely used in industrial wireless sensor networks to collect sensory data and alleviate the “hot spot” problem effectively. However, usage of a mobile sink introduces some challenges, such as updating of a mobile sink’s location and planning of a mobile sink’s trajectory. Meanwhile, the impact of different distribution types of events on data collection has not been sufficiently valued in designing of data collection algorithm for IWSNs yet. To overcome these challenges, a virtual grid-based real-time data collection algorithm for applications with centrally distributed events (VGDCA-C) is proposed in this paper to gain a reliable data gathering for IWSNs. In the target application scenarios, the events are distributed centrally, so we mainly focus on how to shorten the routing paths and decrease the transmission delay. In our VGDCA-C, a mobile sink can adjust its movement dynamically according to the changes in event areas. The adjustment of a mobile sink movement strategy includes two aspects. The first one is the dynamic adjustment of a mobile sink’s parking time, and the second one denotes the moving toward event area of a mobile sink. Thus, a mobile sink adjusts its location such that it can get closer to the event area. Hence, the total length of routing is getting shorter so that source nodes can upload sensory data faster. Analysis and simulation results show that compared with the existing work, our VGDCA-C increases the network lifetime and decreases transmission delay.

UASNs are widely used in many applications, and many studies have been conducted. However, most current research projects have not taken network security into consideration, despite the fact that a UASN is typically vulnerable to malicious attacks due to the unique characteristics of an underwater acoustic communication channel (e.g., low communication bandwidth, long propagation delays, and high bit error rates). In addition, the significant differences between UASNs and terrestrial wireless sensor networks entail the urgent and rapid development of secure communication mechanisms for underwater sensor nodes. For the above mentioned reasons, this article aims to present a somewhat comprehensive survey of the emerging topics arising from secure communications in UASNs, which naturally lead to a great number of open research issues outlined afterward.