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The ongoing expansion of the Industrial Internet of Things (IIoT) is enabling the possibility of effective Industry 4.0, where massive sensing devices in heterogeneous environments are connected through dedicated communication protocols. This brings forth new methods and models to fuse the information yielded by the various industrial plant elements and generates emerging security challenges that we have to face, providing ad-hoc functions for scheduling and guaranteeing the network operations. Recently, the large development of Software-Defined Networking (SDN) and Artificial Intelligence (AI) technologies have made feasible the design and control of scalable and secure IIoT networks. This paper studies how AI and SDN technologies combined can be leveraged towards improving the security and functionality of these IIoT networks. After surveying the state-of-the-art research efforts in the subject, the paper introduces a candidate architecture for AI-enabled Software-Defined IIoT Network (AI-SDIN) that divides the traditional industrial networks into three functional layers. And with this aim in mind, key technologies (Blockchain-based Data Sharing, Intelligent Wireless Data Sensing, Edge Intelligence, Time-Sensitive Networks, Integrating SDN&TSN, Distributed AI) and improve applications based on AI-SDIN are also discussed. Further, the paper also highlights new opportunities and potential research challenges in control and automation of IIoT networks.

Abstract Studies have indicated dietary restriction of methionine/cystine provided a therapeutic benefit in diseases such as cancer. However, the molecular and cellular mechanisms that underlie the interaction between methionine/cystine restriction (MCR) and effects on esophageal squamous cell carcinoma (ESCC) have remained elusive. Here, we discovered the dietary restriction of methionine/cystine has a large effect on cellular methionine metabolism as assayed in a ECA109 derived xenograft model. RNA-seq and enrichment analysis suggested the blocked tumor progression was affected by ferroptosis, together with the NFκB signaling pathway activation in ESCC. Consistently, GSH content and GPX4 expression were downregulated by MCR both in vivo and in vitro. The contents of Fe2+ and MDA were negatively correlated with supplementary methionine in a dose-dependent way. Mechanistically, MCR and silent of SLC43A2, a methionine transporter, diminished phosphorylation of IKKα/β and p65. Blocked NFκB signaling pathway further decreased the expression of SLC43A2 and GPX4 in both mRNA and protein level, which in turn downregulated the methionine intake and stimulated ferroptosis, respectively. ESCC progression was inhibited by enhanced ferroptosis and apoptosis and impaired cell proliferation. In this study, we proposed a novel feedback regulation mechanism underlie the correlation between dietary restriction of methionine/cystine and ESCC progression. MCR blocked cancer progression via stimulating ferroptosis through the positive feedback loop between SLC43A2 and NFκB signaling pathways. Our results provided the theoretical basis and new targets for ferroptosis-based clinical antitumor treatments for ESCC patients.

IntroductionIn 2021, the World Health Organization published a new classification system for central nervous system tumors. This study reclassified the adult diffuse glioma (ADG) into astrocytoma, oligodendroglioma, and glioblastoma (GBM) according to the new tumor classification.MethodsThe association of TERT promoter (pTERT) mutation, MGMT methylation, and CD47/TIGIT expression with patient prognosis was investigated.ResultsImmunohistochemical analysis showed that the expression levels of CD47 and TIGIT in tumor tissues were significantly higher than those in normal brain tissues. CD47 levels were higher in GBM and grade 4 astrocytoma tissues. TIGIT expression was also higher in patients with GBM. The high expressions of CD47, TIGIT, and CD47/TIGIT were positively correlated with MGMT unmethylation but not pTERT mutation. Moreover, MGMT unmethylation was associated with poor overall survival in astrocytoma. High CD47, TIGIT, and CD47/TIGIT levels were associated with significantly reduced survival in ADG and GBM. GBM, MGMT unmethylation, and high CD47 expression were independent prognostic factors for overall survival in ADG.DiscussionCollectively, these results showed that the MGMT unmethylation and high levels of CD47 and TIGIT are associated with a poor prognosis in ADG. Patients with high CD47 and TIGIT expression may benefit from anti-CD47 and TIGIT immunotherapy.

Background and objective The treatment mode of lung cancer is epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) as a first-line treatment for patients with EGFR mutant in non-small cell lung cancer (NSCLC). At the same time programmed death receptor 1 (PD-1) and its programmed death receptor ligand 1 (PD-L1) inhibitors therapy as the representative immune checkpoint inhibitors (ICIs) has a significant effect in the treatment of lung cancer. The aim of this study was to investigate the correlation between the expression of PD-1 and PD-L1 in NSCLC and clinicopathologic feature, EGFR gene mutation. Methods The protein expression of PD-1 and PD-L1 was detected by immunohistochemistry from 127 patients with NSCLC and EGFR gene mutation was detected by quantitative polymerase chain reaction (qPCR) to analyze its relation with clinicopathologic feature. Also, the correlation between protein expression of PD-1 and PD-L1 and EGFR mutation. Results The PD-1 positive expression in NSCLC tumor cells and tumor infiltrating immune cells is 53.5% (68/127), PD-L1 is 57.5% (73/127). The PD-1 and PD-L1 expression significantly higher in well-differentiated and moderately-differentiated carcinoma than poorly differentiated carcinoma, I+II than III+IV in clinical staging (P

Abstract 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.

It was observed that when the short vertical line array (SVLA) is located in the deeper part of the water column, where sound velocity is lower, a groove always exists in the receiving array response in the horizontal direction for distant sound sources in the shallower part of the water column, where the sound velocity is higher. Normal mode modeling is used to explain this result. According to the normal mode theory, the receiving array response of the SVLA to a distant sound source can be expressed in terms of modal beams weighted in accordance with the normal mode amplitude. This modal representation offers a physical interpretation of the receiving array response to a distant sound source in terms of normal modes. The environmental effects of the shape of the sound velocity profile and geo-acoustic properties of the seabed on the receiving array response are analyzed. Based on the results, three conditions for the existence of the groove in the receiving array response are obtained: 1) a gradient in the sound velocity profile, 2) an SVLA in a water column in which the sound velocity is lower and low-order normal modes are trapped, and 3) a distant sound source in a shallow water column in which the sound velocity is higher, and acoustic source couples weakly with low-order normal modes and strongly with high-order normal modes. Finally, the receiving array response of the SVLA to ocean noise and distant sound source are analyzed and discussed using the Mediterranean Sea data. It is shown that the receiving array response to ocean noise differs from that to a distant sound source. Utilizing this difference, the array can be steered carefully to improve the output signal-to-noise ratio and increase the passive detection range against a submerged target in shallow water.

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.

Abstract 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.

Abstract Background Novel therapies tailored to the molecular composition of esophageal squamous cell carcinoma (ESCC) are needed to improve patient survival. We investigated the regulatory network of long intergenic non-protein coding RNA, regulator of reprogramming (linc-ROR) and sex-determining region Y-box 9 (SOX9), and their therapeutic relevance in ESCC. Methods Linc-ROR and SOX9 expression were examined in ESCC specimens, cell lines, and cultured tumorspheres. We investigated the effects of linc-ROR on SOX9 expression and malignant phenotypes by CCK8, colony formation, Transwell, and sphere-forming assay. The linc-ROR/SOX9 interaction mediated by multiple microRNAs (miRNAs) was confirmed by bioinformatic analysis, luciferase assay, and RNA-binding protein immunoprecipitation, transient overexpression or antagonizing endogenous candidate miRNAs. The effect of linc-ROR depletion on tumor growth was assessed by xenograft assay. Results A positive correlation between linc-ROR and SOX9 expression was found in clinical ESCC specimens (r = 0.562, P = 0.036), cell lines, and tumorspheres. Silencing of linc-ROR significantly inhibited cell proliferation, motility, chemoresistance, and self-renewal capacity. Mechanistically, linc-ROR modulating the derepression of SOX9 by directly sponging multiple miRNAs including miR-15b, miR-33a, miR-129, miR-145, and miR-206. Antagonizing these miRNAs counteracted with linc-ROR silencing, whereas the repression of SOX9 abrogated malignant phenotypes induced by the cocktail of miRNA inhibitors. Moreover, linc-ROR disruption was sufficient to attenuate tumor growth and cancer stem cell marker expression in vivo. Conclusions Our results demonstrate that the linc-ROR–miRNA–SOX9 regulatory network may represent a novel therapeutic target for ESCC.

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.

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.

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.

Vicagrel, a structural analog of clopidogrel, is now being developed as a thienopyridine antiplatelet agent in a phase II clinical trial in China. Some studies have shown that vicagrel undergoes complete first-pass metabolism in human intestine, generating the hydrolytic metabolite 2-oxo-clopidogrel via carboxylesterase-2 (CES2) and subsequently the active metabolite H4 via CYP450s. This study aimed to identify hydrolases other than CES2 that are involved in the bioactivation of vicagrel in human intestine. This study is the first to determine that human arylacetamide deacetylase (AADAC) is involved in 2-oxo-clopidogrel production from vicagrel in human intestine. In vitro hydrolytic kinetics were determined in human intestine microsomes and recombinant human CES and AADAC. The calculated contribution of CES2 and AADAC to vicagrel hydrolysis was 44.2 and 53.1% in human intestine, respectively. The AADAC-selective inhibitors vinblastine and eserine effectively inhibited vicagrel hydrolysis in vitro. In addition to CES2, human intestine AADAC was involved in vicagrel hydrolytic activation before it entered systemic circulation. In addition, simvastatin efficiently inhibited the production of both 2-oxo-clopidogrel and active H4; further clinical trials are needed to determine whether the hydrolytic activation of vicagrel is influenced by coadministration with simvastatin. This study deepens the understanding of the bioactivation and metabolism properties of vicagrel in humans, which can help further understand the bioactivation mechanism of vicagrel and the variations in the treatment responses to vicagrel and clopidogrel.

The Kazakh population in Xinjiang Province in northwestern China exhibits a high incidence of esophageal squamous cell carcinoma (ESCC). Although the etiology of esophageal carcinoma (EC) has not been elucidated, there are reports of the involvement of an immunologic mechanism. In the current study, 268 Kazakh ESCC patients and 500 age- and sex-matched control subjects were recruited. DNA was extracted from paraffin-embedded tumor specimens from the patients and peripheral blood lymphocytes from the controls and used for LMP2/LMP7 genotyping. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis was performed to detect LMP2/LMP7 gene single-nucleotide polymorphisms (SNPs). We found a clear increased risk of ESCC in the Kazakh population for the heterozygous LMP2 R/C genotype and the homozygous C/C genotype (OR = 1.470, 95%CI = 1.076-2.008, p = 0.015 forLMP2R/C; OR = 2.048, 95% CI = 1.168-3.591, p = 0.011 for LMP2 C/C). Conversely, the heterozygous LMP7 Q/K polymorphism was found to decrease the risk of ESCC in this population (OR = 0.421, 95% CI = 0.286-0.621, p = 8.83×10-6). Moreover, LMP2 R/C+C/C genotype was associated with increased tumor invasion depth (p = 0.041). Haplotype analysis showed that haplotype A, which includes wild-type homozygous LMP2/TAP1 and mutant LMP7, decreases susceptibility to ESCC in the Kazakh population; in contrast, haplotype E, which includes wild-type homozygous LMP2/LMP7/TAP1, acts as a risk factor for increased susceptibility to ESCC. This is the first study to report that the heterozygous LMP2 R/C and homozygous C/C genotypes increase susceptibility to ESCC in the Kazakh population and that the heterozygous LMP7 Q/K genotype decreases susceptibility to ESCC in this population. Nevertheless, neither LMP2 nor LMP7 was associated with human papillomavirus (HPV) infection. Understanding LMP2/LMP7 genetic variability will provide a new therapeutic perspective for Kazakh patients with ESCC.

In Underwater Wireless Sensor Networks (UWSNs), localization is one of most important technologies since it plays a critical role in many applications. Motivated by widespread adoption of localization, in this paper, we present a comprehensive survey of localization algorithms. First, we classify localization algorithms into three categories based on sensor nodes’ mobility: stationary localization algorithms, mobile localization algorithms and hybrid localization algorithms. Moreover, we compare the localization algorithms in detail and analyze future research directions of localization algorithms in UWSNs.

A wireless sensor network (WSN) consists of many resource constraint sensor nodes, which are always deployed in unattended environment. Therefore, the sensor nodes are vulnerable to failure and malicious attacks. The failed nodes have a heavily negative impact on WSNs’ real-time services. Therefore, we propose a task allocation algorithm based on score incentive mechanism (TASIM) for WSNs. In TASIM, the score is proposed to reward or punish sensor nodes’ task execution in cluster-based WSNs, where cluster heads are responsible for task allocation and scores’ calculation. Based on the task scores, cluster members can collaborate with each other to complete complex tasks. In addition, the uncompleted tasks on failed nodes can be timely migrated to other cluster members for further execution. Furthermore, the uncompleted tasks on death nodes can be reallocated by cluster heads. Simulation results demonstrate that TASIM is quite suitable for real-time task allocation. In addition, the performance of the TASIM is clearly better than that of conventional task allocation algorithms in terms of both network load balance and energy consumption.

Marine environmental monitoring provides crucial information and support for the exploitation, utilization, and protection of marine resources. With the rapid development of information technology, the development of three-dimensional underwater acoustic sensor networks (3D UASNs) provides a novel strategy to acquire marine environment information conveniently, efficiently and accurately. However, the specific propagation effects of acoustic communication channel lead to decreased successful information delivery probability with increased distance. Therefore, we investigate two probabilistic neighborhood-based data collection algorithms for 3D UASNs which are based on a probabilistic acoustic communication model instead of the traditional deterministic acoustic communication model. An autonomous underwater vehicle (AUV) is employed to traverse along the designed path to collect data from neighborhoods. For 3D UASNs without prior deployment knowledge, partitioning the network into grids can allow the AUV to visit the central location of each grid for data collection. For 3D UASNs in which the deployment knowledge is known in advance, the AUV only needs to visit several selected locations by constructing a minimum probabilistic neighborhood covering set to reduce data latency. Otherwise, by increasing the transmission rounds, our proposed algorithms can provide a tradeoff between data collection latency and information gain. These algorithms are compared with basic Nearest-neighbor Heuristic algorithm via simulations. Simulation analyses show that our proposed algorithms can efficiently reduce the average data collection completion time, corresponding to a decrease of data latency.

Balancing energy consumption and prolonging network lifetime have been hot topics in energy limited wireless sensor networks (WSNs). It is generally known that multiple sensor nodes collaborating with each other to perform tasks are an important means of energy balancing. In addition, a reasonable task allocation strategy is also an efficient method for task performing and energy saving. Furthermore, in order to save energy consumption, many WSNs are organized into clusters. Therefore, in this paper, we propose a distributed task allocation strategy for collaborative applications (DTAC) in cluster-based WSNs. In DTAC, the service abilities of sensor nodes are first evaluated and then the sensor nodes are classified into different ranking domains. Based on the service abilities of cluster members, the service ability of each cluster is calculated. A complex task can be first allocated to several clusters, and then scheduled on collaborative cluster members. Simulation results demonstrate that, compared with current related works, DTAC is much more efficient for complex task processing in terms of reducing energy consumption, shortening execution time, and balancing network loads.

Rhabdomyosarcoma (RMS) is the most common pediatric soft tissue sarcoma with poor prognosis. The genetic etiology of RMS remains largely unclear underlying its development and progression. To reveal novel genes more precisely and new therapeutic targets associated with RMS, we used high-resolution array comparative genomic hybridization (aCGH) to explore tumor-associated copy number variations (CNVs) and genes in RMS. We confirmed several important genes by quantitative real-time polymerase chain reaction (QRT-PCR). We then performed bioinformatics-based functional enrichment analysis for genes located in the genomic regions with CNVs. In addition, we identified miRNAs located in the corresponding amplification and deletion regions and performed miRNA functional enrichment analysis. aCGH analyses revealed that all RMS showed specific gains and losses. The amplification regions were 12q13.12, 12q13.3, and 12q13.3-q14.1. The deletion regions were 1p21.1, 2q14.1, 5q13.2, 9p12, and 9q12. The recurrent regions with gains were 12q13.3, 12q13.3-q14.1, 12q14.1, and 17q25.1. The recurrent regions with losses were 9p12-p11.2, 10q11.21-q11.22, 14q32.33, 16p11.2, and 22q11.1. The mean mRNA level of GLI1 in RMS was 6.61-fold higher than that in controls (p = 0.0477) by QRT-PCR. Meanwhile, the mean mRNA level of GEFT in RMS samples was 3.92-fold higher than that in controls (p = 0.0354). Bioinformatic analysis showed that genes were enriched in functions such as immunoglobulin domain, induction of apoptosis, and defensin. Proto-oncogene functions were involved in alveolar RMS. miRNAs that located in the amplified regions in RMS tend to be enriched in oncogenic activity (miR-24 and miR-27a). In conclusion, this study identified a number of CNVs in RMS and functional analyses showed enrichment for genes and miRNAs located in these CNVs regions. These findings may potentially help the identification of novel biomarkers and/or drug targets implicated in diagnosis of and targeted therapy for RMS.

Invasion and metastasis are the major causes of death in patients with esophageal squamous cell carcinoma (ESCC). Epithelial-mesenchymal transition (EMT) is a critical step in tumor progression and transforming growth factor-β1 (TGF-β1) signaling has been shown to play an important role in EMT. In this study, we investigated how TGF-β1 signaling pathways contributed to EMT in three ESCC cell lines as well as 100 patients of nomadic ethnic Kazakhs residing in northwest Xinjiang Province of China. In vitro analyses included Western blotting to detect the expression of TGF-β1/Smad and EMT-associated proteins in Eca109, EC9706 and KYSE150 cell lines following stimulation with recombinant TGF-β1 and SB431542, a potent inhibitor of ALK5 that also inhibits TGF-β type II receptor. TGF-β-activated Smad2/3 signaling in EMT was significantly upregulated as indicated by mesenchymal markers of N-cadherin and Vimentin, and in the meantime, epithelial marker, E-cadherin, was markedly downregulated. In contrast, SB431542 addition downregulated the expression of N-cadherin and Vimentin, but upregulated the expression of E-cadherin. Moreover, the TGF-β1-induced EMT promoted invasion capability of Eca109 cells. Tumor cells undergoing EMT acquire fibroblastoid-like phenotype. Expressed levels of TGF-β1/Smad signaling molecules and EMT-associated proteins were examined using immunohistochemical analyses in 100 ESCC tissues of Kazakh patients and 58 matched noncancerous adjacent tissues. The results showed that ESCC tissues exhibited upregulated expression of TGF-β1/Smad. We also analyzed the relationship between the above proteins and the patients' clinicopathological characteristics. The TGF-β1/Smad signaling pathway in human Eca109 ESCC cells may carry similar features as in Kazakh ESCC patients, suggesting that TGF-β1/Smad signaling pathway may be involved in the regulation of EMT in ethnic Kazakh patients with ESCC from Xinjiang, China.

Mobile sink is widely used for data collection in wireless sensor networks. It can avoid ‘hot spot’ problems but energy consumption caused by multihop transmission is still inefficient in real-time application scenarios. In this paper, a greedy scanning data collection strategy (GSDCS) is proposed, and we focus on how to reduce routing energy consumption by shortening total length of routing paths. We propose that the mobile sink adjusts its trajectory dynamically according to the changes of network, instead of predetermined trajectory or random walk. Next, the mobile sink determines which area has more source nodes, then it moves toward this area. The benefit of GSDCS is that most source nodes are no longer needed to upload sensory data for long distances. Especially in event-driven application scenarios, when event area changes, the mobile sink could arrive at the new event area where most source nodes are located currently. Hence energy can be saved. Analytical and simulation results show that compared with existing work, our GSDCS has a better performance in specific application scenarios.

Localization is one of the hottest research topics in Underwater Wireless Sensor Networks (UWSNs), since many important applications of UWSNs, e.g., event sensing, target tracking and monitoring, require location information of sensor nodes. Nowadays, a large number of localization algorithms have been proposed for UWSNs. How to improve location accuracy are well studied. However, few of them take location reliability or security into consideration. In this paper, we propose a Collaborative Secure Localization algorithm based on Trust model (CSLT) for UWSNs to ensure location security. Based on the trust model, the secure localization process can be divided into the following five sub-processes: trust evaluation of anchor nodes, initial localization of unknown nodes, trust evaluation of reference nodes, selection of reference node, and secondary localization of unknown node. Simulation results demonstrate that the proposed CSLT algorithm performs better than the compared related works in terms of location security, average localization accuracy and localization ratio.