Introduction: The aim of the study was to test and validate the performance of the 2012 Briganti nomogram as a predictor for pelvic lymph node invasion (LNI) in men who underwent radical prostatectomy (RP) with extended pelvic lymph node dissection (PLND), to examine their performance and to analyse the therapeutic impact of using different nomogram cut-off . Material and methods: The study group consisted of 222 men with clinically localized prostate cancer (PCa) who underwent RP with ePLND between 01/2012 and 10/2018. Measurements included: preoperative PSA, clinical stage (CS), primary and secondary biopsy Gleason pattern and percentage of positive cores. The area under curve (AUC) of the receiver operator characteristic analysis was appointed to quantify accuracy of the primary nomogram model to predict LNI. The extent of estimation associated with the use of this model was graphically depicted using calibration plots. Results: The median number of removed lymph nodes was 16 (IQR 12-21). A total of 53 of 222 patients (23,9%) had LNI. Preoperative clinical and biopsy characteristics differed significantly (all p<0.005) between men with and without LNI. A nomogram-derived cut-off of 7% could lead to a reduction of 43% (95/222) of lymph node dissection, while missing 19% (10/53) of patients with LNI. The sensitivity, specificity, and negative predictive value associated with the 7% cut-off were 81.1%, 50.3%, and 96.3%, respectively. Conclusions: Analysed nomogram demonstrated high accuracy for LNI prediction. A nomogram-derived cutoff of 7% confirmed good performance characteristics within a first external validation cohort from Poland.

Mitochondrial alternative oxidase 1a (AOX1a) plays an extremely important role in critical node of seed viability. However, the regulatory mechanism is still poorly understood. The study aims to identify regulatory mechanisms by comparing between OsAOX1a-RNAi and wild type (WT) rice seed during artificial aging treatment. Gain weight and P50 significantly decreased in OsAOX1a-RNAi rice seed, indicating that there might be impaired in seed development and storability. Compared to WT seeds in the 100%, 90%, 80%, and 70% germination, respectively, NADH and succinate-dependent O2 consumption, the activity mitochondrial malate dehydro-genase and ATP contents were decreased in OsAOX1a-RNAi seeds in the 100%, 90%, 80%, and 70% germination, respectively, indicating that mitochondrial status in the OsAOX1a-RNAi seeds after imbibition was weaken than the WT. In addition to, the reduced abundance of complex I N and P module subunits might showed that the capacity of mitochondrial electron transfer chain was significantly inhibited in the OsAOX1a-RNAi seed at critical node of seed viability. Above results might indicated that the ATP production was impaired in OsAOX1a-RNAi seeds during ageing. Therefore, we conclude that the activities of mitochondrial metabolism and alternative pathways were severely inhibited in OsAOX1a-RNAi seeds at critical node of viability, which was leading to accelerate the collapse of seed viability. The precise regulatory mechanism of the alternative pathway at the critical node of viability still needs to be further analyzed.

Lymph nodes are secondary lymphoid organs that appear as bean-like nodules usually <1 cm in size, and they are localized throughout the body. Many antigen-presenting cells such as dendritic cells and macrophages reside in lymph nodes, where they mediate host defense responses against pathogens such as viruses and bacteria. In cancers, antigen-presenting cells induce cytotoxic T lymphocytes (CTLs) to react to cancer cell–derived antigens. Macrophages located in the lymph node sinus are of particular interest in relation to anti-cancer immune responses because many studies using both human specimens and animal models have suggested that lymph node macrophages play a key role in activating anti-cancer CTLs. The regulation of lymph node macrophages therefore represents a potentially promising novel approach in anti-cancer therapy.

With the development of satellite load technology and very-large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. Limited by severe size, weight, and power consumption constraints, a key challenge of on-board SAR imaging system design is to achieve high real-time processing performance. In addition, with the rise of multi-mode SAR applications, the reconfiguration of the on-board processing system is beginning to receive widespread attention. This paper presents a multi-mode SAR imaging chip with SoC architecture based on the reconfigurable double-operation engines and multilayer switching network. We decompose the commonly used extend chirp scaling (CS) SAR imaging algorithm into 8 types of double-operation engines according to the computing orders, and design a three-level switching network to connect these engines for data transition. The CPU is responsible for engine scheduling based on data flow driven with instructions to implement each part of the CS algorithm. Thus, multi-mode floating-point SAR imaging processing can be integrated into a single Application-Specific Integrated Circuit (ASIC) chip instead of relying on distributed technologies. As a proof of concept, a prototype measurement system with chip-included board is implemented, and the performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging. A chip requires 9.2 s, 50.6 s and 7.4 s for a stripmap with 16,384×16,384 granularity, multi-channel stripmap with 65.536×8192 granularity and multi-channel scan mode with 32,768×4096 granularity and 6.9 W for the system hardware to process the SAR raw data.

Lymph node invasion in prostate cancer is a significant prognostic factor indicating worse prognosis. While it affects significantly both survival rates and recurrence, proper management remains a heated issue. Thorough evaluation of risk factors associated with nodal involvement, such as lymph node density or extracapsular extension, is crucial to establish potential expansion of the disease and to substratify patients clinically. There are multiple strategies that may be taken into consideration for patients with positive lymph nodes. Nowadays therapeutic methods are generally based on observation, radiotherapy, and androgen deprivation therapy. However current guidelines are incoherent in terms of indication of the most effective management approach. Future management strategies will be expected to reach for novel diagnostic tools and therapies, such as photodynamic therapy or diagnostic imaging with prostate specific membrane antigen. Nevertheless, this heterogeneous group of men remains a vast therapeutic concern, and both clarification of the guidelines and optimal substratification of patients is required.

This paper outlines the detection procedure of intrusion as provided by Tripwire tool along-with the enhancement to be made in design and implementation to achieve the optimum performance level of Tripwire. It operates on effective and swift performance mechanism in order to report the system admin about the possible intrusion detected in the system with security assurance in cutting edge computer structures, which is very important in order to provide the integrity and reliability of information. In order to deal with this emerging issue in the historical research, the basic level of security is provided in the system by making enhancement in the existing tripwire tool for UNIX file system. The proposed methodological working of tripwire makes it more effective by adopting reliable and instantaneous mechanism to deal with specifically anomalies and unwanted access in the UNIX file system.

The heterogeneous structure implies that a few nodes may be crucial in maintaining network structural and functional properties. Identifying these crucial nodes correctly and quickly is a primary issue as contemporarily may face the mushrooming of large-scale datasets. Besides, the ‘weight issue’ is always ignored in this field which edge weight may play a positive/negative role in contributing to the node importance in different weighted networks. This paper provides a novel algorithm, Weighted Expectation Algorithm (WEA), which aims to ensure accuracy and speed of computation by taking advantage of dynamic programming to better handle the task of large-scale networks. Additionally, the weight issue that edge weights may contribute differently is addressed by a simply quantitative definition. Two standard experiments show WEA can maintain the network structure in connectivity well (by the lowest average robustness 0.192) and identify the node importance better in the spreading function test of spreading dynamics (by the highest average Kendall’s tau-b 0.678). In addition, the time complexities of different algo-rithms are evaluated, and their time-consuming are tested, proving that WEA consumes a rela-tively short time.

The purpose of this review is to summarize current knowledge on lymph node dissection (LND) in prostate cancer (PCa) patients undergoing radical prostatectomy (RP). Despite a growing body of evidence, utility, therapeutic and prognostic value of such approach as well as optimal extent of LND, remain unsolved issues. Although LND is the most accurate staging procedure, the direct therapeutic effect is still not evident from the current literature which limits the possibility of establishing clear recommendations. This indicates the need for further robust and adequately designed high quality clinical trials.

Epithelioid hemangioendothelioma (EHE) is an extremely rare vascular sarcoma with variable aggressive clinical behavior. In this retrospective study we aimed to investigate prognostic factors based on clinicopathologic findings in a molecular/immunohistochemical confirmed nationwide multicenter cohort of 57 EHE. Patients had unifocal disease (n=29), multifocal disease (n=5), lymph node metastasis (n=8) and/or distant metastasis (n=15) at the time of diagnosis. The overall survival rate was 69.6% at 1 year and 50.5% at 5 years. Survival did not correlate with sex, age or histo-pathological parameters. No survival differences were observed between multifocal and metastatic disease suggesting that multifocality represents early metastases and treatment options are limited in comparison to unifocal disease. In unifocal tumors, survival could be predicted using the risk stratification model of Shibayama et al. dividing the cases into low (n=4), intermediate (n=15) and high (n=3) risk-groups. Larger tumor size (>3cm) and higher mitotic count (>1/10HPF) was asso-ciated with progressive unifocal disease course. Lymph node metastases at time of diagnosis oc-curred in 14.0% of the cases and was mainly associated with tumor localization in the head and neck area proposing lymph node dissection. In conclusion, our results demonstrate the aggressive behavior of EHE, emphasize the prognostic value of a previous described risk stratification model and may provide new insights regarding tumor focality, therapeutic strategies and prognosis.

Histologically poor differentiation is associated with lymph node metastasis. Thus, pathological evaluation of biopsy specimens is crucial when treating stomach cancers. Deep learning of WSIs is challenging because the images are enormous. Given the computing limitations, patch-level supervised learning methods have been proposed. However, valuable information is lost when dividing WSIs into smaller patches. Another drawback is the need for pixel-level annotation by a pathologist. It is acceptable to differentiate, i.e., grade, gastric cancer at the holistic tissue level (i.e., under low magnification). We developed a weakly supervised learning technique for tissue-level gastric adenocarcinoma histological differentiation (well-to-moderately or poorly differentiated) and applied global reasoning to tissue-level features. The tissue-level AUROCs of the histological differentiation classifiers were 0.953, 0.969, and 0.943, respectively when data from five hospitals were subjected to threefold cross-validation. Comparison of the Grad-CAM heatmaps of the trained classifier and the pathologists’ annotations confirmed that our weakly supervised model exhibited performed well.

Stem cells are nurtured and regulated by a specialized microenvironment known as stem cell niche. While the functions of the niches are well defined, their structure and location remain unclear. We have identified in rat bone marrow, the seat of hematopoietic stem cells, extensively vascularized node-like compartments that fit the requirements for stem cell niche and which we called hemmules. Hemmules are round or oval structures of about one millimeter in diameter that are surrounded by a fine capsule, have afferent and efferent vessels, are filled with the extracellular matrix and mesenchymal, hematopoietic, endothelial stem cells, and contain cells of the megakaryocyte family, which are known for homeostatic quiescence and contribution to the bone marrow environment. We propose that hemmules are the long sought hematopoietic stem cell niches and that they are prototypical of stem cell niches in other organs.

Background: The lymph nodes staging system can predict the prognosis of gastric signet ring cell carcinoma (SRCC), but the optimal system for early and advanced SRCC remains unknown. Methods: This study retrospectively analyzed 693 SRCC patients who underwent radical resection in the Department of Gastrointestinal Surgery, Harbin Medical University Cancer Hospital. The predicted performance of three lymph node staging systems, including pN staging, lymph node metastasis rate (LNR), and log odds of positive lymph nodes (LODDS), was compared using the receiver characteristic operating curve (ROC). The kaplan⁃meier method and the log⁃rank test analyze the overall survival of patients. The Cox risk regression model identifies independent risk factors associated with patient outcomes. The nomogram was made by R studio. Results: The 693 SRCC included 165 early SRCC and 528 advanced SRCC. ROC showed that LODDS had better predictive performance than pN and LNR in predicting prognosis regardless of early or advanced SRCC. LODDS can be used to predict the prognosis of early and advanced SRCC and was an independent risk factor associated with patient outcomes (P=0.002, P<0.001). Furthermore, the nomogram constructed by LODDS and clinicopathological features had good predictive performance. Conclusion: LODDS showed a clear prognostic superiority over both pN and LNR in early and advanced SRCC.

A run-of-the-mill remote sensor arrange comprises numerous vitality compelled sensor hubs that are arbitrarily sent is the sensor field. Vitality is one of the most significant parts of planning an information dispersal convention for applications, for example, war zone checking, living space observing, and so on. We present EGDD, an Energy-effective Grid-based Data Dissemination plot for arbitrarily conveyed remote sensor systems. The proposed conspire is vitality effective for dealing with both sink and source portability. EGDD depends on a virtual framework-based foundation for information scattering from various versatile sources to different portable sinks. The virtual lattice of square size is built by the main source showing up in the sensor field dependent on the remaining vitality of the sensor hubs. Moreover, we proposed an askew sending calculation for inquiry and information sending which guarantees that just a single spread hub advances the question and information at once. In EGDD, substitute scattering hubs are chosen ahead of time during the lattice development procedure and the least limit vitality level is characterized for spread hubs. When the vitality of a dispersal hub arrives at the base edge esteem, it is supplanted by another spread hub. The reenactment results show that the proposed EGDD conspire is more vitality proficient when contrasted with other information scattering conventions.

A novel drive current model covering the effects of source/drain voltage (VDS) and gate voltage (VGS) and incorporating drift and diffusion current on the surface channel at the nano-node level, especially beyond 28nm node is presented. The effect of the diffusion current added is more satisfactory to describe the behavior of the drive current in nano-node MOSFETs, fabricated with the atomic-layer-deposition (ALD) technology. This breakthrough in model establishment can expose the long and short channel devices together. Introducing the variables of VDS and VGS, the mixed current model more effectively and meaningfully demonstrates the drive current of MOSFETs under the operation of horizontal, vertical, or mixed electrical field. In comparison between the simulation and experimental consequences, the electrical performance is impressive. The error between both is less than 1%, better than the empirical adjustment to issue a set of drive current models.

As Heterogeneous Wireless Sensor Network (HWSN) fulfill the requirements of researchers in the design of real life application to resolve the issues of unattended problem. But, the main constraint face by researchers is energy source available with sensor nodes. To prolong the life of sensor nodes and hence HWSN, it is necessary to design energy efficient operational schemes. One of the most suitable routing scheme is clustering approach, which improves stability and hence enhances performance parameters of HWSN. A novel solution proposed in this article is to design energy efficient clustering protocol for HWSN, to enhance performance parameters by EECPEP-HWSN. Propose protocol is designed with three level nodes namely normal, advance and super node respectively. In clustering process, for selection of cluster head we consider three parameters available with sensor node at run time, i.e., initial energy, hop count and residual energy. This protocol enhance the energy efficiency of HWSN, it improves performance parameters in the form of enhance energy remain in the network, force to enhance stability period, prolong lifetime and hence higher throughput. It is been found that proposed protocol outperforms than LEACH, DEEC and SEP with about 188, 150 and 141 percent respectively.

As a new distributed machine learning (ML) approach, federated learning (FL) shows the great potential to preserve data privacy by enabling distributed data owners to collaboratively build a global model without sharing their raw data. However, the heterogeneity in terms of data distribution and hardware configurations make it hard to select participants from the thousands of nodes. In this paper, we propose a multi-objective node selection approach to improve time-to-accuracy performance while resisting malicious nodes. We firstly design a deep reinforcement learning assisted FL framework. Then the problem of multi-objective node selection under this framework is formulated as a Markov decision process (MDP), which aims to reduce the training time and improve model accuracy simultaneously. Finally, a deep Q-netwok (DQN) based algorithm is proposed to efficiently solve the optimal set of participants for each iteration. Simulation results show that the proposed method not only significantly improves the accuracy and training speed of FL, but has stronger robustness to resist malicious nodes.

Marangoni flow in foam fractionation in the lamellar film for the interior and exterior of a micro-foam was investigated. The three-dimensional node-film-Plateau Border system was modeled using computational fluid dynamics. The importance of the surfactant concentration of the foam fractionation column and air-liquid interface mobility on the Marangoni velocity in the film was emphasized. The study found that an increase in surfactant concentration in the reflux column significantly increases the Marangoni velocities. Additionally, a mobile interface results in a higher Marangoni flow, while a rigid interface leads to less intensive flow. The behavior of the Marangoni flow in both interior and exterior foam was explored, revealing that the flow in exterior foam has different behavior due to the presence of the wall, which reduces the Marangoni velocity compared to interior films.

Introduction: The aim of our study was to evaluate the efficacy and toxicity of a daily-adaptive MR-guided SBRT on 1.5 T MR-linac in patients affected by lymphnode oligometastases from PCa. Materials and Methods: The present study is a prospective observational study conducted in a single institution (protocol n°: MRI / LINAC n. 23748). Patients with oligometastatic lymphnodes from PCa treated with daily-adaptive MR-guided SBRT on 1.5T MR-linac were included in the study. Minimum required follow-up of 3 months after SBRT. Primary end-point was local progression-free survival (LPFS). Secondary end-points were: nodal progression-free survival (NPFS), and progression-free survival (PFS), and toxicity. Results: 118 lymphnode oligometastases from PCa were treated with daily-adaptive 1.5T MR-guided SBRT in 63 oligometastatic patients. 63.5% patients were oligoprogressive and 36.5% oligoprogressive. Two-year LPFS was 94.5%. Median NPFS was 22.3 months, and the 2-year NPFS was 46.5%. Having received hormone therapy before SBRT was correlated with lower NPFS at the multivariate analysis (1-y NPFS 87.1% versus 42.8%; p= 0.002 - HR 0.199, 95% CI 0.073-0.549). Furthermore, the oligorecurrent state during ADT was correlated with a lower NPFS than the oligoprogressive state. Median PFS was 10.3 months, the 2-year PFS was 32.4%. Patients treated with hormone therapy before SBRT had a significantly lower 1-year PFS the others (28% versus 70.4%; p= 0.01 - HR 0.259, 95% CI 0.117-0.574). No acute and late toxicities occurred during treatment. Conclusion: the present is the largest prospective study of 1.5T lymphnode SBRT on MR-linac in patients with PCa. Lymphnode SBRT by 1.5T MR-linac provides high local control rates with an excellent toxicity profile.

Sentinel lymph node dissection (sLND) using a magnetometer and superparamagnetic iron oxide nanoparticles (SPIONs) as a tracer was successfully applied in prostate cancer (PCa). Radioisotope-guided sLND combined with extended pelvic LND (ePLND) achieved better node removal, increasing the number of affected nodes or the detection of sentinel lymph nodes outside the established ePLND template. We determined the diagnostic value of additional magnetometer-guided sLND after intraprostatic SPION-injection in high-risk PCa. This retrospective study included 104 high-risk PCa patients (PSA >20 ng/ml and/or Gleason score ≥8 and/or cT2c) from a prospective cohort who underwent radical prostatectomy with magnetometer-guided sLND and ePLND. The diagnostic accuracy of sLND was assessed using ePLND as a reference standard. Lymph node metastases were found in 61 of 104 patients (58.7%). sLND had a 100% diagnostic rate, 96.6% sensitivity, 95.6% specificity, 96.6% positive predictive value, 95.6% negative predictive value, 3.4% false negative rate, and 4.4% false positive rate (detecting lymph node metastases outside the ePLND template). These findings demonstrate the high sensitivity and additional diagnostic value of magnetometer-guided sLND, exceeding that of ePLND through the individualized extension of PLND or the detection of sentinel lymph nodes / lymph node metastases outside the established node template in high-risk PCa.

Megalin (LRP2) is a rapidly recycling multiligand endocytic receptor, primarily expressed in polarized epithelial cells. Despite megalin could promote tumor growth and invasiveness through several mechanisms, it has been understudied in the field of molecular oncology so far. The present study aimed to evaluate the impact of megalin expression in oral squamous cell carcinoma (OSCC) on disease progression. Megalin expression was evaluated immunohistochemically in 63 OSCC specimens. Data obtained were retrospectively compared with patients’ clinicopathological features and survival. The proportion of megalin-expressing cells in primary OSCC tissue was significantly associated with metastatic spreading to lymph nodes, vascular invasion and lower overall survival rate. Results obtained by the study suggest that megalin can be considered as a novel molecule involved in OSCC pathogenesis, but also useful as a potential biomarker for cancer progression.

In heterogeneous networks, the random walks based on meta-path requires prior knowledge and lacks flexibility. And the random walks based on non-meta-path only considers the number of node types, but does not consider the influence of schema and topology between node types in real networks. To solve the above problems, this paper proposes a novel model HNE-RWTIC (Heterogeneous Network Embedding Based on Random Walks of Type & Inner Constraint). Firstly, to realize the flexible walks, we design a Type strategy, which is the node type selection strategy based on the co-occurrence probability of node types. Secondly, to achieve the uniformity of node sampling, we design an Inner strategy, which is the node selection strategy based on the adjacency relationship between nodes. The Type & Inner strategy can realize the random walks based on meta-path, the flexibility of the walks, and can sample the node types and nodes uniformly in proportion. Thirdly, based on the above strategy, a transition probability model is constructed; then, we obtain the nodes embedding based on the random walks and Skip-Gram. Finally, in classification and clustering tasks, we conducted a thorough empirical evaluation of our method on three real heterogeneous networks. Experimental results shown that F1-Score and NMI of HNE-RWTIC outperform state-of-the-art approaches.

The use of unmanned aerial vehicle (UAV) during emergency response of a disaster has been widespread in recent years and the terrain images captured by the cameras on board these vehicles are significant sources of information for such disaster monitoring operations. Thus, analyzing such images are important for assessing the terrain of interest during such emergency response operations. Further, these UAVs are mainly used in disaster monitoring systems for the automated deployment of sensor nodes in real time. Therefore, deploying and localizing the wireless sensor nodes optimally, only in the regions of interest that are identified by segmenting the images captured by UAVs, hold paramount significance thereby effecting their performance. In this paper, the highly effective nature-inspired Plant Growth Simulation Algorithm (PGSA) has been applied for the segmentation of such terrestrial images and also for the localization of the deployed sensor nodes. The problem is formulated as a multi-dimensional optimization problem and PGSA has been used to solve it. Furthermore, the proposed method has been compared to other existing evolutionary methods and simulation results show that PGSA gives better performance with respect to both speed and accuracy unlike other techniques in literature.

Abstract Objective: To review the relevant literature on the use of atrioventricular node ablation and pacing in patients with heart failure and atrial fibrillation. Methods: A PubMed/MEDLINE and SCOPUS search was performed in order to assess the clinical outcomes of atrioventricular node ablation and pacemaker implantation, as well as the complications that may occur. Results: Several clinical trials, observational analyses and meta-analyses have shown that “pace and ablate” strategy not only improves symptoms but also can enhance cardiac performance in patients with heart failure and atrial fibrillation. Although this procedure is effective and safe, some complications may occur including worsening of heart failure, permanent fibrillation, arrhythmias and sudden death. Regarding the implantation of pacemaker, cardiac resynchronization therapy is shown to be the optimal choice compared to right ventricle apical pacing. His bundle pacing is a promising alternative to cardiac resynchronization therapy and has shown beneficial effects, while left bundle brunch pacing is an innovative modality. Conclusions: Atrioventricular node ablation and implantation of pacemaker is shown to have beneficial effects on clinical outcomes of patients with atrial fibrillation ± heart failure who do not respond or are intolerant to medical treatment. Cardiac resynchronization therapy is the treatment of choice and His bundle pacing seems to be an effective alternative way of pacing in these patients.

This paper analyzed the main diseases of the friction high-strength bolt (FHSB) joints in order to study the characteristics of the corrosion products of the joints in steel bridge and the influence factors. Seven representative FHSB connection pairs and eight steel plate samples were selected from the Dongying Shengli Yellow River Bridge, which has been in operation for 33 years. Then Scanning Electron Microscope (SEM), Energy Dispersive Spectroscopy (EDS) and X-Ray Diffraction (XRD) were used to analyze the microscopic morphology and chemical composition of the corroded surface of the samples. Finally, this paper discussed the relationship between the corroded sample surface and the environmental corrosion. The research results showed that construction quality problems, such as non-standard hole expansion, segmental slab joint dislocation and contact surface pollution, accelerated corrosion of the contact surface. With the increase of corrosion degree of joints, the contact surface of aluminum spraying layer gradually changed from a rugged and dense state to a smooth and porous powder state. With the corrosion of the steel plate substrate, the contact surface gradually changed from a fluffy stratified state to a surface bonding state. It was inferred that the friction coefficient of the FHSB connection node on the corroded aluminum sprayed contact surface first decreased and then increased. The corroded node samples detected not only a large number of S and Cl elements, but also the oxides of Mn, Si and other elements as well as FeS. It was speculated that node corrosion was also related to atmospheric (acid rain) and industrial dust and other corrosive environments. Almost all samples detected the component SiO2 of the Yellow River soil, as well as Mg, Ca, K, Na and other elements at the same time, which is basically consistent with the component elements of the Yellow River soil. Therefore, it was inferred that it was related to the inclusion of the Yellow River soil.

Targeted radioisotope-guided sentinel lymph node dissection (sLND) has shown high diagnostic accuracy in prostate cancer (PCa). To overcome the downsides of the radioactive tracers, magnetometer-guided sLND using superparamagnetic iron oxide nanoparticles (SPIONs) was successfully applied in PCa. This prospective study (SentiMag Pro II, DRKS00007671) determined the diagnostic accuracy of magnetometer-guided sLND in intermediate- and high-risk PCa. Fifty intermediate- or high-risk PCa patients (PSA≥10 ng/ml and/or Gleason score ≥7; median PSA 10.8 ng/ml, IQR 7.4–19.2 ng/ml) were enrolled. After intraprostatic SPIONs injection a day earlier, patients underwent magnetometer-guided sLND and eLND, followed by radical prostatectomy. SLNs were detected in vivo and in ex vivo samples. Diagnostic accuracy of sLND was assessed using eLND as the reference. SLNs were detected in all patients (detection rate 100%), with 447 SLNs (median 9, IQR 6–12) being identified and 966 LNs (median 18, IQR 15-23) being removed. Thirty-six percent (18/50) of patients had LN metastases (median 2, IQR 1–3). Magnetometer-guided sLND had 100% sensitivity, 97.0% specificity, 94.4% positive predictive value, 100% negative predictive value, 0.0% false negative rate, and 3.0% additional diagnostic value (LN metastases only in SLNs outside the eLND template). In vivo, one positive SLN/LN-positive patient was missed, resulting in a sensitivity of 94.4%. In conclusion, this new magnetic sentinel procedure has high accuracy for nodal staging in intermediate- and high-risk PCa. The reliability of intraoperative SLN detection using this magnetometer system requires verification in further multicentric studies.

LoRa and its upper layers definition LoRaWAN is one of the most promising LPWAN technologies for implementing the Internet of Things (IoT). Although being a popular technology, several works in the literature have revealed various weaknesses regarding the security of LoRaWAN v1.0 (the official 1st draft). By using all these recommendations from the academia and industry, the LoRa-Alliance has worked on the v1.0 to develop an enhanced version and provide more secure and trustable architecture. The result of these efforts ended-up with LoRaWAN v1.1, which was released on Oct 11, 2017. This manuscript aims at demystifying the security aspects and provide a comprehensive Security Risk Analysis related to latest version of LoRaWAN. Besides, it provides several remedies to the recognized vulnerabilities. To the best of authors’ knowledge, this work is one of its first kind by providing a detailed security analysis related to latest version of LoRaWAN. According to our analysis, end-device physical capture, rogue gateway and replay attacks are found to be threating for safety operation of the network. Eventually, v1.1 of LoRaWAN is found to be less vulnerable to attacks compared to v1.0, yet possesses several security implications that need to be addressed and fixed for the upcoming releases.

The objective of this study was to evaluate the efficacy of one-step nucleic acid amplification (OSNA) for the detection of sentinel lymph node (SLN) metastasis compared to standard pathological ultrastaging in patients with early-stage endometrial cancer (EC). A total of 526 SLNs from 191 patients with EC were included in the study. 379 SLNs (147 patients) were evaluated by both methods, OSNA and standard pathological ultrastaging. The central 1-mm portion of each lymph node was subjected to semi-serial sectioning at 200-μm intervals and examined by hematoxylin-eosin and immunohistochemistry with CK19; the remaining tissue was analysed by OSNA for CK19 mRNA. The OSNA assay detected metastases in 19.7% of patients (14.9% micrometastasis and 4.8% macrometastasis), whereas pathological ultrastaging detected metastasis in 8.8% of patients (3.4% micrometastasis and 5.4% macrometastasis). Using the established cut-off value for detecting SLN metastasis by OSNA in EC (250 copies/μl), the sensitivity of the OSNA assay was 92%; specificity was 82%; diagnostic accuracy was 83%, and the negative predictive value was 99%. Discordant results between both methods were recorded in 20 patients (13.6%). OSNA resulted in an upstaging in 12 patients (8.2%). OSNA could aid in the identification of patients requiring adjuvant treatment at the time of diagnosis.

In zebrafish inner ear, hair cell orientation in anterior and posterior maculae of the embryonic otic vesicle is different (about 30–40 degrees): this is rather unusual in planar polarity mechanism of action, instead suggests that kinocilia may be rotationally polarized. In mice node, the innermost monociliated cells generate a left-ward fluid flow sensed by the immotile primary cilia of Left peri-nodal cells: the Nodal signaling pathway is then expressed asymmetrically, in the Left lateral plate mesoderm, breaking symmetry in visceral organs (situs solitus); however, Right peri-nodal cells also, if artificially excited by a right-ward flow, break symmetry and activate the Nodal cascade, though inverting visceral organ asymmetry (situs inversus); surprisingly, peri-nodal cells prove to be adept at distinguishing flow directionality. Recently, in the Kupffer vesicle (the zebrafish laterality organ), chiral primary cilia orientation has been described: primary cilia, in the left and right side, are symmetrically oriented, showing a mirror average divergence of about 15–20 degrees from the midline. This finding, taken together with the mirror behavior of mouse perinodal cells and zebrafish hair cells, champions the idea of primary cilia enantiomerism.

Over the past several years there has been much debate with regards to the prognostic and clinical significance of pancreatic ductal adenocarcinoma (PDAC) with lymph nodes metastasis. The PDAC gene-expression knowledge and the biologic alterations underlying the lymph node involvement convey a clinical implication in dealing with the theranostic window.To this end, we provide an original bioinformatic dissection of the gene-expression differences of PDAC according to the nodal involvement from a large public available dataset. Comprehensive transcriptomic analysis from 143 RNA-seq patient’s derived samples indicated that WNT increased activation and a peculiar immune-microenvironment identify subjects with nodal involvement.In frame of this thinking, we validated the WNT pathway role in increasing the likelihood of lymphatic dissemination in vitro. Moreover, we demonstrated for the first time in a PDAC model the potential therapeutic window that XAV-939, a specific WNT pathway inhibitor, has in re-educating a tumour permissive immune system. Finally, we outline the potential implication on bystander molecular drivers exerted by WNT molecular inhibition, providing a picture of the proteomic oncogenic landscape changes elicited by XAV-939 on PDAC cells and their clinical implication. Our findings hold the promise to identify novel immune-based therapeutic strategies targeting WNT to enhance PDAC cytotoxicity and restore anti-PDAC immunity in nodes-positive disease.

Background: Tuberculosis (TB) manifests itself primarily in the lungs as pulmonary disease (PTB) and sometimes disseminates to other organs to cause extra-pulmonary TB, such as lymph node TB (LNTB). This study aimed to investigate the role of host genetic polymorphism in immunity related genes to find a genetic basis for such differences. Methods: Sixty-three, Single nucleotide polymorphisms (SNPs) in twenty-three, TB-immunity related genes including eleven innate immunity (SLCA11, VDR, TLR2, TLR4, TLR8, IRGM, P2RX7, LTA4H, SP110, DCSIGN and NOS2A) and twelve cytokine (TNFA, IFNG, IL2, Il12, IL18, IL1B, IL10, IL6, IL4, IL1RA, IL8 and TNFB) genes were investigated to find genetic associations in both PTB and LNTB as compared to healthy community controls. The serum cytokine levels were correlated for association with the genotypes. Results: PTB and LNTB showed differential genetic associations. The genetic variants in the cytokine genes (IFNG, IL12, IL4, TNFB and IL1RA and TLR2,4 associated with PTB susceptibility and cytokine levels but not LNTB (p &lt; 0.05). Similarly, genetic variants in LTA4H, P2RX7, DCSIGN and SP110 showed susceptibility to LNTB and not PTB. Pathway analysis showed abundance of cytokine related variants for PTB and apoptosis related variants for LNTB. Conclusions: PTB and LNTB outcomes of TB infection have a genetic component and should be considered for any future susceptibility and functional studies.

This research takes Cuiwei Village in Qianshan District of Zhuhai City as an example. Through field research, the village is investigated and analyzed, and the street scale, spatial structure, functional characteristic streets, internal commercial distribution forms, and functions of Cuiwei Historic District are studied. analysis. On this basis, based on the convex space method and the line-of-sight analysis method in the space syntax theory, with the help of Depthmap software, the complex street node, that is, the space of the two nodes A and B, is established through the establishment of a visual field model. It includes the analysis of the integration degree of the horizon, the concentration of the horizon, the connection value of the horizon and the spatial characteristics of the historical area, as well as the traditional buildings that are the most representative of the village, namely the Three Kings Temple and the Webster's Mansion. When R=N and radius R=3, observe the changes in the two parameters of the visual integration and visual depth of the two historical buildings. And with the help of Baidu Time Machine photos in different periods to observe and record the changes in the store and the characteristics of people's behavior, and draw conclusions.

In this paper, the methodology using Insect Intelligent Building (I^2B) technology for establishing energy consumption monitoring system of public buildings is prevailed. The computing process node and distributed algorithm are utilized to implement the energy consumption collection and data transmission and data pre-processing. Taking a commercial building as a case study, CPNs are applied to set up the building energy consumption monitoring system, with the Spanning Tree Algorithm for generating network topology，and BPNN method for solving abnormal data and recovering missing data. The research results demonstrate the proposed method can effectively improve the performance of plug-and-play and self-identified and self-configuration of energy consumption monitoring system.

In this study we discuss critical issues in modelling the structure and function of lymph nodes (LNs), with emphasis on how LN physiology is related to its multi-scale structural organization. In addition to macroscopic domains such as B-cell follicles and the T cell zone, there are vascular networks which play a key role in the delivery of information to the inner parts of the LN, i.e., the conduit and blood microvascular networks. We propose object-oriented computational algorithms to model the 3D geometry of the fibroblastic reticular cell (FRC) network and the microvasculature. Assuming that a conduit cylinder is densely packed with collagen fibers, the computational flow study predicted that the diffusion should be a dominating process in mass transport than convective flow. The geometry models are used to analyze the lymph flow properties through the conduit network in unperturbed- and damaged states of the LN. The analysis predicts that elimination of up to 60–90 % of edges is required to stop the lymph flux. This result suggests a high degree of functional robustness of the network.

Some concepts/hypotheses have been proposed to explain the general rules behind the complexity of tumorigenesis. Characterization of the property of cancer cells and neural stem cells indicates that neural stemness underlies tumorigenicity and pluripotency, leading to the proposal that tumorigenesis represents a process of progressive loss of original cell identity and gain of neural stemness. This reminds of a most fundamental process required for the development of the nervous system and body axis during embryogenesis, i.e., embryonic neural induction. The principle of neural induction is that, in response to extracellular signals that are secreted by the Spemann-Mangold organizer in amphibians or the node in mammals and inhibit epidermal fate in ectoderm, the ectodermal cells assume the neural default fate and turn into neuroectodermal cells. These cells further differentiate into the nervous system and also some non-neural cells via interaction with adjacent tissues. Failure in neural induction leads to failure of embryogenesis, and ectopic neural induction due to ectopic organizer or node activity or activation of embryonic neural genes causes a formation of secondary body axis or conjoined twins. A similar principle underlies tumorigenesis. Increasing evidence has demonstrated that the core property of cancer cells is neural stemness. Therefore, cancer cells are cells with the loss of original cell identity and gain of neural stemness, and consequently tumorigenicity and pluripotency, due to various intra-/extracellular insults in postnatal animals. Unlike that pluripotent cells (embryonic pluripotent cells, neural stem cells and cancer cells) can differentiate and integrate into embryonic development, cancer cells are capable of self-renewal and differentiation, but cannot integrate into normal tissues in a 2 postnatal animal, ultimately leading to tumor formation. Neural induction and the unique property of neural stemness provide an inclusive explanation for embryogenesis, conjoined twin formation and tumorigenesis. Based on these findings, I discuss about some confusion in cancer research, e.g., epithelial-mesenchymal transition, and propose to distinguish the causality and associations, and the causal and supporting factors involved in tumorigenesis, and suggest revisiting the focus of cancer research. Integration of evidence from developmental and cancer biology indicates that neural stemness determines tumorigenicity and pluripotency, and neural induction drives embryogenesis in gastrulating embryos but a similar process drives tumorigenesis in a postnatal animal.

The ability to predict the skin sensitization potential of small organic molecules is of high importance to the development and safe application of cosmetics, drugs and pesticides. One of the most widely accepted methods for predicting this hazard is the rodent local lymph node assay (LLNA). The goal of this work was to develop in silico models for the prediction of the skin sensitization potential of small molecules that go beyond the state of the art, with larger LLNA data sets and, most importantly, a robust and intuitive definition of the applicability domain, paired with additional indicators of the reliability of predictions. We explored a large variety of molecular descriptors and fingerprints in combination with random forest and support vector machine classifiers. The most suitable models were tested on holdout data, on which they yielded competitive performance (Matthews correlation coefficients up to 0.52; accuracies up to 0.76; areas under the receiver operating characteristic curves up to 0.83). The most favorable models are available via a public web service at https://nerdd.zbh.uni-hamburg.de/skinDoctor/ that, in addition to predictions, provides assessments of the applicability domain and indicators of the reliability of the individual predictions.

Ultra-wideband wavelength division multiplexed networks enable operators to use more effectively the bandwidth offered by a single fiber pair and thus make significant savings, both in operational and capital expenditures. The main objective of this study is to minimize optical node resources, such as transponders, multiplexers and wavelength selective switches, needed to provide and maintain high quality of network services, in ultra-wideband wavelength division multiplexed networks, at low cost. A model based on integer programming is proposed, which includes a detailed description of optical network nodal resources. The developed optimization tools are used to study the ultra-wideband wavelength division multiplexed network performance when compared with the traditional C-band wavelength division multiplexed networks. The analysis is carried out for realistic networks of different dimensions and traffic demand sets.

This review article is focused on the analysis of the state of the art of sensors for guided 9 ultrasonic waves for the detection and localization of impacts, therefore of interest for the structural 10 health monitoring (SHM). The recent developments in sensor technologies are then reported and 11 discussed through the many references in recent scientific literature. The physical phenomena re-12 lated to impact event and the main physical quantities are then introduced to discuss their im-13 portance in the development of the hardware and software components for SHM systems. An im-14 portant aspect of the article is the description of the different ultrasonic sensor technologies cur-15 rently present in the literature and what advantages and disadvantages they could bring, in relation 16 to the various phenomena investigated. In this context, the analysis of the front-end electronics is 17 deepened, the type of data transmission both in terms of wired and wireless technology and in terms 18 of online and offline signal processing. The integration aspects of sensors for the creation of net-19 works with autonomous nodes with the possibility of powering through energy harvesting devices 20 and the embedded processing capacity is also studied. Finally, the emerging sector of processing 21 techniques using deep learning and artificial intelligence concludes the review by indicating the 22 potential for the detection and autonomous characterization of the impacts.