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Xiao-Dong Zhang,1 Jiang Yang,2 Sha-Sha Song,1 Wei Long,1 Jie Chen,1 Xiu Shen,1 Hao Wang,1 Yuan-Ming Sun,1 Pei-Xun Liu,1 Saijun Fan11Tianjin Key Laboratory of Molecular Nuclear Medicine, Institute of Radiation Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, People's Republic of China; 2Department of Biological Systems Engineering, University of Wisconsin-Madison, Madison, WI, USAAbstract: The use of nanoparticles holds promise for medical applications, such as X-ray imaging, photothermal therapy and radiotherapy. However, the in vivo toxicity of inorganic nanoparticles raises some concern regarding undesirable side effects which prevent their further medical application. Ultrasmall sub-5.5 nm particles can pass through the barrier for renal clearance, minimizing their toxicity. In this letter we address some recent interesting work regarding in vivo toxicity and renal clearance, and discuss the possible strategy of utilizing ultrasmall nanomaterials. We propose that small hydrodynamic sized nanoclusters can achieve both nontoxic and therapeutic clinical features.Keywords: in vivo clearance, gold nanoparticles, small size

Jie Chen, Hao Wang, Wei Long, Xiu Shen, Di Wu, Sha-Sha Song, Yuan-Ming Sun, Pei-Xun Liu, Saijun Fan, Feiyue Fan, Xiao-Dong ZhangTianjin Key Laboratory of Molecular Nuclear Medicine, Institute of Radiation Medicine,Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, People's Republic of ChinaAbstract: Gold nanoparticles have received wide interest in disease diagnosis and therapy, but one of the important issues is their toxicological effects in vivo. Sex differences in the toxicity of gold nanoparticles are not clear. In this work, body weight, organ weight, hematology, and biochemistry were used to evaluate sex differences in immune response and liver and kidney damage. Pathology was used to observe the general toxicity of reproductive organs. The immune response was influenced significantly in female mice, with obvious changes in spleen and thymus index. Hematology results showed that male mice treated with 22.5 nm gold nanoparticles received more significant infection and inflammation than female mice. Meanwhile, the biochemistry results showed that 4.4 and 22.5 nm gold nanoparticles caused more significant liver damage in male mice than female mice, while 22.5, 29.3, and 36.1 nm gold nanoparticles caused more significant kidney damage in female mice than male mice. No significant toxicological response was found in the reproductive system for female or male mice. It was found that gold nanoparticles caused more serious liver toxicity and infection in male mice than female mice. These findings indicated that sex differences may be one of the important elements for in vivo toxicity of gold nanoparticles.Keywords: sex differences, toxicity, gold nanoparticles

Xiao-Dong Zhang, Di Wu, Xiu Shen, Pei-Xun Liu, Na Yang, Bin Zhao, Hao Zhang, Yuan-Ming Sun, Liang-An Zhang, Fei-Yue FanInstitute of Radiation Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin Key Laboratory of Molecular Nuclear Medicine, Tianjin, People’s Republic of ChinaBackground: Gold nanoparticle toxicity research is currently leading towards the in vivo experiment. Most toxicology data show that the surface chemistry and physical dimensions of gold nanoparticles play an important role in toxicity. Here, we present the in vivo toxicity of 5, 10, 30, and 60 nm PEG-coated gold nanoparticles in mice.Methods: Animal survival, weight, hematology, morphology, organ index, and biochemistry were characterized at a concentration of 4000 µg/kg over 28 days.Results: The PEG-coated gold particles did not cause an obvious decrease in body weight or appreciable toxicity even after their breakdown in vivo. Biodistribution results show that 5 nm and 10 nm particles accumulated in the liver and that 30 nm particles accumulated in the spleen, while the 60 nm particles did not accumulate to an appreciable extent in either organ. Transmission electron microscopic observations showed that the 5, 10, 30, and 60 nm particles located in the blood and bone marrow cells, and that the 5 and 60 nm particles aggregated preferentially in the blood cells. The increase in spleen index and thymus index shows that the immune system can be affected by these small nanoparticles. The 10 nm gold particles induced an increase in white blood cells, while the 5 nm and 30 nm particles induced a decrease in white blood cells and red blood cells. The biochemistry results show that the 10 nm and 60 nm PEG-coated gold nanoparticles caused a significant increase in alanine transaminase and aspartate transaminase levels, indicating slight damage to the liver.Conclusion: The toxicity of PEG-coated gold particles is complex, and it cannot be concluded that the smaller particles have greater toxicity. The toxicity of the 10 nm and 60 nm particles was obviously higher than that of the 5 nm and 30 nm particles. The metabolism of these particles and protection of the liver will be more important issues for medical applications of gold-based nanomaterials in future.Keywords: gold nanoparticles, in vivo, toxicity, size

Vision Training is important for basketball players to effectively search for teammates who has wide-open opportunities to shoot, observe the defenders around the wide-open teammates and quickly choose a proper way to pass the ball to the most suitable one. We develop an immersive virtual reality (VR) system called VisionCoach to simulate the player's viewing perspective and generate three designed systematic vision training tasks to benefit the cultivating procedure. By recording the player's eye gazing and dribbling video sequence, the proposed system can analyze the vision-related behavior to understand the training effectiveness. To demonstrate the proposed VR training system can facilitate the cultivation of vision ability, we recruited 14 experienced players to participate in a 6-week between-subject study, and conducted a study by comparing the most frequently used 2D vision training method called Vision Performance Enhancement (VPE) program with the proposed system. Qualitative experiences and quantitative training results are reported to show that the proposed immersive VR training system can effectively improve player's vision ability in terms of gaze behavior and dribbling stability. Furthermore, training in the VR-VisionCoach Condition can transfer the learned abilities to real scenario more easily than training in the 2D-VPE Condition.

Laparoscopic liver surgery is a newly developed minimally invasive technique and represents an inevitable trend in the future development of surgical methods. By using augmented reality (AR) technology to overlay preoperative CT models with intraoperative laparoscopic videos, surgeons can accurately locate blood vessels and tumors, significantly enhancing the safety and precision of surgeries. Point cloud registration technology is key to achieving this effect. However, there are two major challenges in registering the CT model with the point cloud surface reconstructed from intraoperative laparoscopy. First, the surface features of the organ are not prominent. Second, due to the limited field of view of the laparoscope, the reconstructed surface typically represents only a very small portion of the entire organ. To address these issues, this paper proposes the keypoint correspondence registration network (KCR-Net). This network first uses the neighborhood feature fusion module (NFFM) to aggregate and interact features from different regions and structures within a pair of point clouds to obtain comprehensive feature representations. Then, through correspondence generation, it directly generates keypoints and their corresponding weights, with keypoints located in the common structures of the point clouds to be registered, and corresponding weights learned automatically by the network. This approach enables accurate point cloud registration even under conditions of extremely low overlap. Experiments conducted on the ModelNet40, 3Dircadb, DePoLL demonstrate that our method achieves excellent registration accuracy and is capable of meeting the requirements of real-world scenarios.

Background: Bipolar hemostasis electrocoagulation is a fundamental procedure in neurosurgery. A precise electrocoagulation model is essential to enable realistic visual feedback in virtual neurosurgical simulation. However, existing models lack an accurate description of the heat damage and irreversible tissue deformation caused by electrocoagulation, thus diminishing the visual realism. This work focuses on the electrocoagulation model for neurosurgery simulation., Method: In this paper, a position-based dynamics (PBD) model with a bioheat transfer and damage prediction (BHTDP) method is developed for simulating the deformation of brain tissue caused by electrocoagulation. The presented BTHDP method uses the Arrhenius equation to predict thermal damage of brain tissue. A deformation model with energy and thermal damage constraints is developed to characterize soft tissue deformation during heat absorption before and after thermal injury. Visual effect of damaged brain tissue is re-rendered., Result: To evaluate the accuracy of the proposed method, numerical simulations were conducted and compared with commercial finite element software. The maximum normalized error of the proposed model for predicting midpoint temperature is 10.3 % and the maximum error for predicting the thermal damage is 5.4 %. The contraction effects of heat-exposed anisotropic tissues are also simulated. The results indicate that the presented electrocoagulation model provides stable and realistic visual effects, making it applicable for simulating the electrocoagulation process in virtual neurosurgery., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Blood accumulation often occurs during bleeding in surgery. Simulating the blood accumulation in surgical simulation system not only enhances the realism and immersion of surgical training, but also helps researchers better understand the physical properties of blood flow., Methods: To realistically simulate the blood accumulation during the bleeding, this paper proposes a novel kernel function with non-negative second derivatives to improve the SPH method. Meanwhile, a simple form of boundary force equation is constructed to impose the solid boundary condition., Results: We simulate the blood accumulation during liver bleeding and vessel bleeding respectively in the surgical simulation system. The simulation results show that there is no occurrence of blood physically penetrating the boundary., Conclusions: Applying the solid boundary condition to the blood by using the method proposed in this paper is not only convenient but can also eliminate compression instability in the blood accumulation simulation., (© 2024 John Wiley & Sons Ltd.)

The current thyroid ultrasound relies heavily on the experience and skills of the sonographer and the expertise of the radiologist, and the process is physically and cognitively exhausting. In this paper, we report a fully autonomous robotic ultrasound system, which is able to scan thyroid regions without human assistance and identify malignant nod- ules. In this system, human skeleton point recognition, reinforcement learning, and force feedback are used to deal with the difficulties in locating thyroid targets. The orientation of the ultrasound probe is adjusted dynamically via Bayesian optimization. Experimental results on human participants demonstrated that this system can perform high-quality ultrasound scans, close to manual scans obtained by clinicians. Additionally, it has the potential to detect thyroid nodules and provide data on nodule characteristics for American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) calculation., (© 2024. The Author(s).)

Photonic integrated quantum memories are essential for the construction of scalable quantum networks. Spin-wave quantum storage, which can support on-demand retrieval with a long lifetime, is indispensable for practical applications, but has never been demonstrated in an integrated solid-state device. Here, we demonstrate spin-wave quantum storage based on a laser-written waveguide fabricated in a 151 Eu 3+ :Y 2 SiO 5 crystal, using both the atomic frequency comb and noiseless photon-echo protocols. Qubits encoded with single-photon-level inputs are stored and retrieved with a fidelity of [Formula: see text], which is far beyond the maximal fidelity that can be obtained with any classical device. Our results underline the potential of laser-written integrated devices for practical applications in large-scale quantum networks, such as the construction of multiplexed quantum repeaters in an integrated configuration and high-density transportable quantum memories., (© The Author(s) 2024. Published by Oxford University Press on behalf of China Science Publishing & Media Ltd.)

In this article, the adaptive tracking control problem is considered for high-order stochastic nonlinear time-delay systems in fixed-time. Being different from existing results, an improved Lyapunov-Krasovskii function is designed, which can not only compensate for the time-delay term but also remove the obstacle from the high-order term. Due to the introduction of the Lyapunov-Krasovskii function into the total Lyapunov function, it makes it difficult to stabilize the controlled system within a fixed-time interval. L'Hopital's rule is used to determine the boundedness of the Lyapunov-Krasovskii function, and the fixed-time boundedness of the integral functions can be inferred. By utilizing the fixed-time Lyapunov stability theorem, it is proved that the controlled system is semi-globally practical fixed-time stable (SGPFS), all the closed-loop signals (CLSs) are bounded within the fixed-time interval, and the tracking error converges into a small region around zero. The validity of the designed scheme is substantiated via simulation results.

The selective removal of targeted pollutants from complex wastewater is challenging. Herein, a novel persulfate (PS)-based advanced oxidation system equipped with a series of two-dimensional (2D) bimetallic oxide nanosheets (NSs) catalysts is developed to selectively degrade bisphenol A (BPA) within mixed pollutants via initiating nonradical-induced polymerization. Results indicate that the Ni 0.60 Co 0.40 O x NSs demonstrate the highest catalytic efficiency among all Ni-Co NSs catalysts. Specifically, BPA degradation rate is 47.34, 27.26, and 9.72 times higher than that of 4-chlorophenol, phenol, and 2,4-dichlorophenol in the mixed solution, respectively. The lower oxidative potential of BPA in relation to the other pollutants renders it the primary target for oxidation within the PDS activation system. PDS molecules combine on the surface of Ni 0.60 Co 0.40 O x NSs to form the surface-activated complex, triggering the generation of BPA monomer radicals through H-abstraction or electron transfer. These radicals subsequently polymerize on the surface of the catalyst through coupling reactions. Importantly, this polymerization process can occur under typical aquatic environmental conditions and demonstrates resistance to background matrices like Cl - and humic acid due to its inherent nonradical attributes. This study offers valuable insights into the targeted conversion of organic pollutants in wastewater into value-added polymers, contributing to carbon recycle and circular economy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background and Objective: Physiological motions have a significant impact on soft tissue deformation and accuracy of surgical procedures, which is essential for realistic surgical simulation. While existing studies offer accurate simulation of soft tissue deformation, integrating physiological motions into deformation models of soft tissue remains a challenging task., Methods: This paper introduces a novel deformation model, based on complementary dynamics, to animate soft tissue deformation under physiological motion. The finite element method is incorporated to accurately characterize the elastic behavior of the soft tissue. Mathematical models of physiological motion are utilized and the physiological effects are converted into displacements of a predefined set of handles within the soft tissue mesh. Complementary displacements derived from the inherent dynamics of the soft tissue are calculated, enabling the simulation of physiological motions and elastic behaviors in soft tissue deformation., Results: Experiments were conducted to evaluate the performance and effectiveness of the proposed method in simulating soft tissue deformation under physiological motion. The simulation results show that the soft tissues exhibit physiological motion that corresponds to the rhythm of arterial pressure fluctuations, heartbeat or respiratory. Furthermore, the presented method exhibits stable performance compared with existing force-based methods., Conclusions: Both elastic behaviors and physiological motions of soft tissue deformation can be governed by the proposed method. A high degree of realistic visualization is achieved for virtual surgery simulation., Competing Interests: Declaration of Competing Interest We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome., (Copyright © 2023 Elsevier B.V. All rights reserved.)

This paper studies the exponential synchronization problem for a class of delayed coupled neural networks with delay-compensatory impulsive control. A Razumikhin-type inequality involving some destabilizing delayed impulse gains and a new idea of delay-compensatory that shows two critical roles for system stability are presented, respectively. Based on the constructed inequality and the presented delay-compensatory idea, sufficient stability and synchronization criteria for globally exponential synchronization (GES) of coupled neural networks (CNNs) are presented. Compared with existing results, the uniqueness of the presented results lies in that impulse delays can be fetched and integrated to compensate for instantaneous unstable impulse dynamics caused by destabilizing gains. Moreover, constraints between system delay and impulsive delay are relaxed, and the interval of impulses no longer constrains the system delay. Comparisons and a practical application are given to demonstrate the superior performance of the presented novel control methods., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 ISA. Published by Elsevier Ltd. All rights reserved.)

BACKGROUND : Selective biliary cannulation is the most challenging step in endoscopic retrograde cholangiopancreatography (ERCP) because only indirect radiographic images can be obtained. Therefore, we developed a novel endoscopic retrograde direct cholangioscopy (ERDC) technology to facilitate visible biliary cannulation. METHODS : In this case series, we used ERDC to treat 21 patients with common bile duct stones who were enrolled consecutively between July 2022 and December 2022. The procedure details and complications were recorded, and all patients were followed up for 3 months after the procedure. The learning curve effect was analyzed by comparing the early and later cases. RESULTS : Biliary cannulation was successful in all patients, and the stones were removed completely. The median (interquartile range [IQR]) time for cholangioscopy-guided biliary cannulation was 240.0 (10.0-430.0) seconds, and the median (IQR) number of cannulation procedures was 2 (1-5). Despite there being one episode of post-ERCP pancreatitis, one of cholangitis, and three patients developing asymptomatic hyperamylasemia, all of the patients recovered after symptomatic treatment, being discharged and with no serious adverse events occurring during the 3-month follow-up period. Compared with the early cases, the number of intubations and the use of guidewire guidance decreased in later cases. CONCLUSION : Our research confirms that ERDC is a feasible technology for biliary cannulation under direct vision., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

A new two-step, one-pot synthesis of benzo[ f ][1,2]thiazepine 1,1-dioxides was developed, which contains a visible-light mediated aza Paternò-Büchi reaction of benzo[ d ]isothiazole 1,1-dioxides with alkenes and a Lewis acid catalyzed ring-expansion of azetidine. In this work, the mechanism of the aza Paternò-Büchi reaction was also investigated.

Existing driving fatigue detection methods rarely consider how to effectively fuse the advantages of the electroencephalogram (EEG) and electrocardiogram (ECG) signals to enhance detection performance under noise conditions. To address the issues, this article proposes a new type of the deep learning (DL) framework based on EEG and ECG called the product fuzzy convolutional network (PFCN). It should be noted that this article first investigates how to fuse EEG and ECG signals to deal with driving fatigue detection under noise conditions in both simulated and real-field driving environments. Specifically, the PFCN includes three subnetworks. The first uses a fuzzy neural network (FNN) with feedback and a product layer, effectively capturing the particularity and temporal variation of high-dimensional EEG signals and reducing the time-space complexity. The second subnetwork uses a 1-D convolution to convert the ECG data into feature sequences, providing high accuracy and low computational complexity in ECG data classification. The third subnetwork proposes a fusion-separation mechanism to effectively fuse the extracted ECG and EEG features, suppressing the noise interference and ensuring higher detection accuracy. To evaluate the performance of PFCN, a series of experiments has been set up in both simulated and real-field driving environments. The results indicate that the proposed PFCN model has better robustness and detection accuracy compared with several mainstream fatigue detection models.

Background and Aim: A pyogenic liver abscess (PLA) is an infectious disease with high in-hospital mortality. It has no specific symptoms and is difficult to be diagnosed early in the emergency department. Ultrasound is commonly used to detect PLA lesions of PLA, but its sensitivity can be affected by lesion size, location, and clinician experience. Therefore, early diagnosis and prompt treatment (especially abscess drainage) are crucial for better patient outcomes and should be prioritized by clinical physicians., Methods: We conducted a retrospective study to compare the effect of early and late (i.e., receiving CT scanning within 48 h and >48 h after admission) adoption of nonenhanced computed tomography (CT) scanning regarding the hospitalization days and interval between admission and drainage of patients with PLA., Results: This study included 76 hospitalized patients with PLA in the Department of Digestive Disease of Xiamen Chang Gung Hospital in China who underwent CT examinations from 2014 to 2021. We conducted CT scans on 56 patients within 48 h of admission and on 20 patients more than 48 h after admission. The early CT group had a significantly shorter hospitalization length compared with the late CT group (15.0 days vs. 20.5 days; P  = 0.035). Besides, the median time to initiate drainage after admission was also significantly shorter in the early CT group than in the late CT group (1.0 days vs. 4.5 days; P  < 0.001)., Conclusion: Early CT scanning within 48 h of admission may aid in early PLA diagnosis and benefit disease recovery, as revealed by our findings., (© 2023 The Authors. JGH Open published by Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.)

A novel wearable upper arm tactile display device, which can simultaneously provide three types of tactile stimuli (i.e., squeezing, stretching, and vibration) is presented. The squeezing and stretching stimulation of the skin is generated by two motors simultaneously driving the nylon belt in the opposite and the same direction, respectively. In addition, four evenly spaced vibration motors are fixed around the user's arm by an elastic nylon band. There is also a unique structural design for assembling the control module and actuator, powered by two lithium batteries, making it portable and wearable. Psychophysical experiments are conducted to investigate the effect of interference on the perception of squeezing and stretching stimulation by this device. Results show that (1) different tactile stimuli actually interfere with the user's perception compared to the case where only one stimulus is applied to the user; (2) the squeezing has a considerable impact on the stretch just noticeable difference (JND) values when both stimuli are exerted on the user, and when the squeezing is strong, while the impact of stretch on the squeezing JND values is negligible.

This research addresses the finite-time control problem for nonaffine stochastic nonlinear systems with actuator faults and input saturation. Specifically, a new finite-time control scheme is constructed based on the adaptive backstepping framework, with the usage of a state observer and taking advantage of the universal approximation capability of the fuzzy-logic system (FLS). The novelty of this work is that it considers the output feedback problem of a completely nonaffine stochastic system and incorporates the idea of the dynamic surface control (DSC) design. By using the Lyapunov stability theory, all the signals of the controlled system can be semiglobal finite-time stable in probability (SGFSP) while the system is imposed with multiple actuator constraints. In the meantime, the problem of "complexity explosion" is avoided. Two simulation examples are given to demonstrate the validity of the presented strategy.

Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer, accounting for 75%-85% of cases. Although treatments are given to cure early-stage HCC, up to 50%-70% of individuals may experience a relapse of the illness in the liver after 5 years. Research on the fundamental treatment modalities for recurrent HCC is moving significantly further. The precise selection of individuals for therapy strategies with established survival advantages is crucial to ensuring better outcomes. These strategies aim to minimize substantial morbidity, support good life quality, and enhance survival for patients with recurrent HCC. For individuals with recurring HCC after curative treatment, no approved therapeutic regimen is currently available. A recent study presented novel approaches, like immunotherapy and antiviral medication, to improve the prognosis of patients with recurring HCC with the apparent lack of data to guide the clinical treatment. The data supporting several neoadjuvant and adjuvant therapies for patients with recurring HCC are outlined in this review. We also discuss the potential for future clinical and translational investigations., Competing Interests: Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article., (©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.)

In this article, the problem of decentralized fuzzy adaptive control is addressed for a class of stochastic interconnected nonlinear large-scale systems including saturation and unknown disturbance. Fuzzy logic systems (FLSs) are used to estimate packaged nonlinear uncertainties. The command filter technique is presented to eliminate the "explosion of complexity" obstacle associated with the backstepping procedures and the corresponding error compensation mechanism is constructed to alleviate the effect of the errors generated by command filters. The influence of input saturation is compensated by introducing an auxiliary system. Meanwhile, an improved adaptive fuzzy decentralized controller is developed and it is able to minimize calculation time since there is no need for repeated differentiation for the virtual control laws. The presented control scheme not only assures the semi-global boundedness of all the signals in the closed-loop system, but also makes the output tracking errors reach a small neighborhood around the origin. Finally, both numerical and practical examples are provided to illustrate the efficiency and effectiveness of our theoretic result., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 ISA. Published by Elsevier Ltd. All rights reserved.)

Background and Objective: Realistic modeling the dissection of brain tissue is of key importance for simulation of brain tumor removal in virtual neurosurgery systems. However, existing methods are unable to characterize inelastic behaviors of brain tissue, such as plastic deformation and dissection evolution, making it ineffective in simulating brain tumor removal procedures., Methods: In this paper, a model of fibrous soft tissue dissection for the simulation of brain tumor removal is proposed. A dissection variable of representative volume element is used to characterize the dissection state of the fibrous soft tissue. The evolution of dissection with elastic-plastic deformation under the effects of external loads is presented., Results: Simulation results show that the proposed model provides realistic, stable and intuitive results in the simulation of fracture in fibrous soft tissues. As the external load increases, the fibrous soft tissue begins to crack, with the cracks growing and multiplying until they eventually merge to form a fracture. The proposed model is incorporated into the simulation of brain tumor removal., Conclusions: The experimental results demonstrate the feasibility of modeling fibrous soft tissue dissection with elastic-plastic deformation. A relative high degree of realistic visual feedback is achieved., Competing Interests: Declaration of Competing Interest Authors declare that they have no conflict of interest., (Copyright © 2023 Elsevier B.V. All rights reserved.)

A class of heterogeneous second-order multi-agent consensus problems is studied, in which an event-triggered method is used to improve the feasibility of the control protocol. The sliding mode control method is used to achieve the robustness of the system. A special type of general radial basis function neural network is applied to estimate the uncertainties. The event-triggered mechanism is introduced to reduce the update frequency of the controller and the communication frequency among the agents. Zeno behavior is avoided by ensuring a lower bound between two adjacent trigger instants. Finally, the simulation results are provided to demonstrate that the time evolution of consensus errors eventually approaches zero. The consensus of multi-agent systems is achieved.

Cordycepin (3 '-deoxyadenosine) is the main active component of Cordyceps militaris , which is a chemical marker for quality detection of Cordyceps militaris and has important medicinal development value. Existing methods for obtaining cordycepin are complex and costly. In this study, an economical and simple method for separation and purification of cordycepin from Cordyceps militaris fermentation liquid through physical crystallization was explored. First, lyophilized powdered fermentation liquid (LPFL) and pure methanol (1 g/100 mL, w/v) were mixed, and then repeatedly dissolved and crystallized until the precipitation was white. Purified product was obtained by freeze-drying the precipitate. The substance was determined to be cordycepin by high performance liquid chromatography, mass spectrometry and infrared spectroscopy, and the purity was 94.26%. Compared with the existing methods, this method is simple and low cost. In addition, the functional activity of cordycepin was determined by in vitro test. The results exhibited that cordycepin caused death and morphological changes in human colon cancer Caco-2 cells, and significantly inhibited the proliferation of Caco-2 cells, with a half-maximal inhibitory concentration (IC 50 ) of 107.2 μg/mL. Cordycepin could induce early apoptosis of Caco-2 and caused cell cycle arrest in the G2 phase. Caco-2 cell apoptosis and cell cycle arrest showed dose dependence to cordycepin over a certain range. These results improved cordycepin purification method, provided insights into the mechanism of cordycepin in cancer inhibition, and would provide important reference for further development and clinical application of cordycepin., Competing Interests: The authors declare no conflict of interest., (© 2023 The Authors.)

In this article, we consider the input-to-state stability (ISS) problem for a class of time-delay systems with intermittent large delays, which may cause the invalidation of traditional delay-dependent stability criteria. The topic of this article features that it proposes a novel kind of stability criterion for time-delay systems, which is delay dependent if the time delay is smaller than a prescribed allowable size. While if the time delay is larger than the allowable size, the ISS can be preserved as well provided that the large-delay periods satisfy the kind of duration condition. Different from existing results on similar topics, we present the main result based on a unified Lyapunov-Krasovskii function (LKF). In this way, the frequency restriction can be removed and the analysis complexity can be simplified. A numerical example is provided to verify the proposed results.

Background: In colonoscopy screening for colorectal cancer, human vision limitations may lead to higher miss rate of lesions; artificial intelligence (AI) assistance has been demonstrated to improve polyp detection. However, there still lacks direct evidence to demonstrate whether AI is superior to trainees or experienced nurses as a second observer to increase adenoma detection during colonoscopy. In this study, we aimed to compare the effectiveness of assistance from AI and human observer during colonoscopy., Methods: A prospective multicenter randomized study was conducted from 2 September 2019 to 29 May 2020 at four endoscopy centers in China. Eligible patients were randomized to either computer-aided detection (CADe)-assisted group or observer-assisted group. The primary outcome was adenoma per colonoscopy (APC). Secondary outcomes included polyp per colonoscopy (PPC), adenoma detection rate (ADR), and polyp detection rate (PDR). We compared continuous variables and categorical variables by using R studio (version 3.4.4)., Results: A total of 1,261 (636 in the CADe-assisted group and 625 in the observer-assisted group) eligible patients were analysed. APC (0.42 vs 0.35, P  =   0.034), PPC (1.13 vs 0.81, P  <   0.001), PDR (47.5% vs 37.4%, P  <   0.001), ADR (25.8% vs 24.0%, P  =   0.464), the number of detected sessile polyps (683 vs 464, P  <   0.001), and sessile adenomas (244 vs 182, P  =   0.005) were significantly higher in the CADe-assisted group than in the observer-assisted group. False detections of the CADe system were lower than those of the human observer (122 vs 191, P  <   0.001)., Conclusions: Compared with the human observer, the CADe system may improve the clinical outcome of colonoscopy and reduce disturbance to routine practice (Chictr.org.cn No.: ChiCTR1900025235)., (© The Author(s) 2023. Published by Oxford University Press and Sixth Affiliated Hospital of Sun Yat-sen University.)

Aims: The aim of this study was to develop a novel approach using lateral flow recombinase polymerase amplification (RPA-LF) combined with immunomagnetic separation (IMS) for the rapid detection of Staphylococcus aureus in milk., Methods and Results: Under optimum conditions, the average capture efficiency values for S. aureus strains (10 4  colony-forming units [CFU] per ml) was above 95.0% in PBST and ~80% in milk within 45 min with 0.7 mg immunomagnetic beads. The RPA-LF assay, which comprised DNA amplification via RPA at 39°C for 10 min and visualization of the amplicons through LF strips for 5 min, detected S. aureus within 15 min. The method only detected S. aureus and did not show cross-reaction with other bacteria, exhibiting a high level of specificity. Sensitivity experiments confirmed a detection limit of RPA-LF assay as low as 600 fg per reaction for the S. aureus genome (corresponding to approximately 36 CFU of S. aureus), which was about 16.7-fold more sensitive than that of the conventional polymerase chain reaction method. When RPA-LF was used in combination with IMS to detect S. aureus inoculated into artificially contaminated milk, it exhibited a detection limit of approximately 40 CFU per reaction., Conclusions: The newly developed IMS-RPA-LF method enabled detection of S. aureus at levels as low as 40 CFU per reaction in milk samples without culture enrichment for an overall testing time of only 70 min., Significance and Impact of the Study: The newly developed IMS-lateral flow RPA-LF assay effectively combines sample preparation, amplification and detection into a single platform. Because of its high sensitivity, specificity and speed, the IMS-RPA-LF assay will have important implications for the rapid detection of S. aureus in contaminated food., (© 2022 Society for Applied Microbiology.)

Background and Objective: Modeling of glioma growth and evolution is of key importance for cancer diagnosis, predicting clinical progression and improving treatment outcomes of neurosurgery. However, existing models are unable to characterize spatial variations of the proliferation and infiltration of tumor cells, making it difficult to achieve accurate prediction of tumor growth., Methods: In this paper, a new growth model of brain tumor using a reaction-diffusion equation on brain magnetic resonance images is proposed. Both the heterogeneity of brain tissue and the density of tumor cells are used to estimate the proliferation and diffusion coefficients of brain tumor cells. The diffusion coefficient that characterizes tumor diffusion and infiltration is calculated based on the ratio of tissues (white and gray matter), while the proliferation coefficient is evaluated using the spatial gradient of tumor cells. In addition, a parameter space is constructed using inverse distance weighted interpolation to describe the spatial distribution of proliferation coefficient., Results: The glioma growth predicted by the proposed model were tested by comparing with the real magnetic resonance images of the patients. Experiments and simulation results show that the proposed method achieves accurate modeling of glioma growth. The interpolation-based growth model has higher average dice score of 0.0647 and 0.0545, and higher average Jaccard index of 0.0673 and 0.0573, respectively, compared to the uniform- and gradient-based growth models., Conclusions: The experimental results demonstrate the feasibility of calculating the proliferation and diffusion coefficients of the growth model based on patient-specific anatomy. The parameter space that characterizes spatial distribution of proliferation and diffusion coefficients is established and incorporated into the simulation of glioma growth. It enables to obtain patient-specific models about glioma growth by estimating and calibrating only a few model parameters., (Copyright © 2022. Published by Elsevier B.V.)

Background: Wear particles-induced osteolysis is a major long-term complication after total joint arthroplasty. Up to now, there is no effective treatment for wear particles-induced osteolysis except for the revision surgery, which is a heavy psychological and economic burden to patients. A metabolite of gut microbiota, short chain fatty acids (SCFAs), has been reported to be beneficial for many chronic inflammatory diseases. This study aimed to investigate the therapeutic effect of SCFAs on osteolysis., Methods: A model of inflammatory osteolysis was established by applying CoCrMo alloy particles to mouse calvarium. After two weeks of intervention, the anti-inflammatory effects of SCFAs on wear particle-induced osteolysis were evaluated by Micro-CT analysis and immunohistochemistry staining. In vitro study, lipopolysaccharide (LPS) primed bone marrow-derived macrophages (BMDMs) and Tohoku Hospital Pediatrics-1 (THP-1) macrophages were stimulated with CoCrMo particles to activate inflammasome in the presence of acetate (C2), propionate (C3), and butyrate (C4). Western blotting, Enzyme-linked immunosorbent assay, and immunofluorescence were used to detect the activation of NLRP3 inflammasome. The effects of SCFAs on osteoclasts were evaluate by qRT-PCR, Western blotting, immunofluorescence, and tartrate-resistant acid phosphatase (TRAP) staining. Additionally, histone deacetylase (HDAC) inhibitors, agonists of GPR41, GPR43, and GPR109A were applied to confirm the underlying mechanism of SCFAs on the inflammasome activation of macrophages and osteoclastogenesis., Results: C3 and C4 but not C2 could alleviate wear particles-induced osteolysis with fewer bone erosion pits (P < 0.001), higher level of bone volume to tissue volume (BV/TV, P < 0.001), bone mineral density (BMD, P < 0.001), and a lower total porosity (P < 0.001). C3 and C4 prevented CoCrMo alloy particles-induced ASC speck formation and nucleation-induced oligomerization, suppressing the cleavage of caspase-1 (P < 0.05) and IL-1β (P < 0.05) stimulated by CoCrMo alloy particles. C3 and C4 also inhibited the generation of Gasdermin D-N-terminal fragment (GSDMD-NT) to regulate pyroptosis. Besides, C3 and C4 have a negative impact on osteoclast differentiation (P < 0.05) and its function (P < 0.05), affecting the podosome arrangement and morphologically normal podosome belts formation., Conclusion: Our work showed that C3 and C4 are qualified candidates for the treatment of wear particle-induced osteolysis., (© 2022. The Author(s).)

Vibrio parahaemolyticus is a marine pathogen thought to be the leading cause of seafood-borne gastroenteritis globally, urgently requiring efficient management methods. V. parahaemolyticus encodes 12 resistance/nodulation/division (RND) efflux systems. However, research on these systems is still in its infancy. In this study, we discovered that the inactivation of VmeL, a membrane fusion protein within the RND efflux systems, led to reduction of the ability of biofilm formation. Further results displayed that the decreased capacity of Congo red binding and the colony of Δ vmeL is more translucent compared with wild type strains, suggested reduced biofilm formation due to decreased production of biofilm exopolysaccharide upon vmeL deletion. In addition, the deletion of vmeL abolished surface swarming and swimming motility of V. parahaemolyticus . Additionally, deletion of vmeL weakened the cytotoxicity of V. parahaemolyticus towards HeLa cells, and impaired its virulence in a murine intraperitoneal infection assay. Finally, through RNA-sequencing, we ascertained that there were 716 upregulated genes and 247 downregulated genes in Δ vmeL strain. KEGG enrichment analysis revealed that quorum sensing, bacterial secretion systems, ATP-binding cassette transporters, and various amino acid metabolism pathways were altered due to the inactivation of vmeL . qRT-PCR further confirmed that genes accountable to the type III secretion system (T3SS1) and lateral flagella were negatively affected by vmeL deletion. Taken together, our results suggest that VmeL plays an important role in pathogenicity, making it a good target for managing infection with V. parahaemolyticus., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Zhang, Wang, Li, Sun, Qi, Zhou, Han, Chen, Fang and Jiang.)

In this article, finite-time-prescribed performance-based adaptive fuzzy control is considered for a class of strict-feedback systems in the presence of actuator faults and dynamic disturbances. To deal with the difficulties associated with the actuator faults and external disturbance, an adaptive fuzzy fault-tolerant control strategy is introduced. Different from the existing controller design methods, a modified performance function, which is called the finite-time performance function (FTPF), is presented. It is proved that the presented controller can ensure all the signals of the closed-loop system are bounded and the tracking error converges to a predetermined region in finite time. The effectiveness of the presented control scheme is verified through the simulation results.

An adaptive finite-time approach to the feedback control of stochastic nonlinear systems is presented. The fuzzy logic system (FLS) and a state observer are used to estimate the uncertain function and unmeasured state of the controlled system, respectively. A dynamic surface control (DSC) scheme is employed to deal with the "computational explosion" problem, which is inherent in traditional backstepping methods since the repetitive calculation of the derivatives of virtual control signals is avoided. A new output feedback controller is developed to guarantee that all the signals of the controlled system are bounded within a finite time range and the tracking deviation can converge to an arbitrarily small residual set within finite time. Simulations confirm the analytical and theoretical results of the presented algorithm., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 ISA. Published by Elsevier Ltd. All rights reserved.)

In this research, the adaptive neural network consensus control problem is addressed for a class of non-affine multiagent systems (MASs) with actuator faults and stochastic disturbances. To overcome difficulties associated with actuator faults and uncertain functions of the designed MAS, a neural network fault-tolerant control scheme is developed. Moreover, an adaptive backstepping controller is developed to solve the non-affine appearance in multiagent stochastic non-affine systems using the mean value theorem. Being different from the existing control methods, the developed adaptive fixed-time control approach can ensure that the outputs of all followers track the reference signal synchronously in the fixed time, and all signals of the controlled system are semi-globally uniformly fixed-time stable. The simulation results confirm that the presented control strategy is effective in achieving control goals.

A Gram-stain-negative, cocci-to-oval-shaped bacterial strain, designated XZZS9 T , was isolated from the rhizosphere soil of Pinus sylvestris var. mongolica and characterized taxonomically using a polyphasic approach. Growth occurred at 20-35 °C (optimum, 28 °C), pH 6.0-11.0 (optimum, pH 7.0), and in 0-1% NaCl (optimum, 0%). Phylogenetic analysis based on 16S rRNA gene sequencing indicated that strain XZZS9 T was related to members of the genus Roseococcus, with the highest sequence identity to Roseococcus microcysteis NIBR12 T (96.9%). The major cellular fatty acids (> 5% of the total) were C 18:1 ω7c and C 19:0 cyclo ω8c. The major isoprenoid quinone was Q-9 and the polar lipid profile contained diphosphatidylglycerol, phosphatidylglycerol, phosphatidylcholine, phosphatidylethanolamine, an unidentified glycophospholipid, and an unidentified phospholipid. Genome sequencing revealed that had a genome size of 4.79 Mbp with a G + C content of 69.5%. Comparative genomic analyses clearly separated strain XZZS9 T from the known species of the genus Roseococcus based on average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values below the thresholds for species delineation. Genome annotations did not find pufL and pufM genes in strain XZZS9 T , suggesting a possible lack of photosynthetic reaction. Based on genotypic and phenotypic characteristics, strain XZZS9 T represents a novel species of the genus Roseococcus, for which we propose the name Roseococcus pinisoli sp. nov. The type strain is XZZS9 T (= KCTC 82435 T  = JCM 34402 T  = GDMCC 1.2158 T )., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background and Objectives: For neurological simulation, an accurate deformation model of brain tissue is of key importance for faithful visual feedback. Existing models, however, do not take into account intracranial pulsation, which degrades significantly the realism of visual feedback., Methods: In this paper, a finite element model incorporating intracranial pressure is proposed for simulating brain tissue deformation with pulsation. An implicit Euler method is developed to calculate the deformation of brain tissue. A circuit model of intracranial pressure dynamics is established based on cerebral blood and cerebrospinal fluid circulations. The intracranial pulsation of pressure is introduced into the deformation model, so that the simulated brain tissues pulsate with a rhythm in accord with the changes of intracranial pressure, which resembles real-life neurosurgery., Results and Conclusions: The experimental implementation of the proposed deformation model and the calculation method shows that it provides realistic simulation of brain tissue pulsation and real-time performance is achieved on an ordinary computer for certain procedures of neurosurgery., Competing Interests: Declaration of Competing Interest We confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Hepatocellular carcinoma (HCC) is one of the most prevalent and lethal cancers. Dysregulation of S100A2 has recently been found in many cancers including HCC. However, its regulatory mechanism in HCC remains poorly understood, especially in hypoxia. In this study, we found that S100A2 is upregulated and correlated with the clinicopathological features of HCC patients. Moreover, the elevated S100A2 showed worse overall survival. Functionally, S100A2 inhibition decreased the proliferation and migration of HepG2 cells. Interestingly, we found that HIF-1α directly binds to hypoxia response elements (HREs) of the S100A2 promoter region. S100A2 expression could be induced in an HIF-1α-dependent manner under hypoxia. Furthermore, S100A2 silencing significantly suppressed HCC cell proliferation and invasion under hypoxia. Mechanistically, pyrosequencing results showed that the hypomethylation status of CpG located in the HRE at the S100A2 promoter was correlated with S100A2 induction. Additionally, HIF-1α- mediated S100A2 activation was associated with TET2-related epigenetic inactivation. TET2 was enriched in the HRE of the S100A2 promoter in HepG2 cells. Finally, S100A2 methylation-related genes and pathways were analyzed. We found that the methylation of S100A2 is correlated with ANXA2, PPP1R15A, and FOS, which include in a hypoxia-related gene set from the GSEA database. Moreover, some EMT-related genes are associated with the methylation of S100A2 in HCC. Conclusively, our study thus uncovered a novel mechanism showing that hypoxia/HIF-1α signaling associated with DNA methylation enhances S100A2 expression in HCC. S100A2 may be useful as a target for facilitating novel diagnostic and therapeutic strategies in liver cancer., (© 2022 Wiley Periodicals LLC.)

S100B has been found to be dysregulated in many cancers including hepatocellular carcinoma (HCC). However, the functions of S100B and its underlying mechanisms in HCC remain poorly understood, especially in the tumor microenvironment. In this study, functions enrichment analysis indicated that S100B expression was correlated with hypoxia and immune responses. We found that hypoxia could induce S100B expression in an HIF-1α-dependent manner in HepG2 cells. Luciferase reporter and ChIP-qRCR assays demonstrated that HIF-1α regulates S100B transcription by directly binding to hypoxia-response elements (HREs) of the S100B promoter. Functionally, knockdown of S100B reduces hypoxia-induced HepG2 cell invasion and migration. Furthermore, GSVA enrichment results displayed that S100B and its co-expressed genes were positively correlated with EMT pathway in HCC. Additionally, GO/KEGG cluster analysis results indicated that co-expressed genes of S100B were involved in biological processes of immune response and multiple tumor immune-related signaling pathways in HCC. S100B expression was positively correlated with multiple immune cells tumor infiltration and associated with chemokines/chemokine receptors and immune checkpoint genes. Moreover, S100B is predominantly expressed in immune cells, especially NK (Natural Killer) cell. In addition, the hub genes of S100B co-expression and hypoxia response in HepG2 cell were also associated with immune cells infiltration in HCC. Taken together, these findings provide a new insight into the complex networks between hypoxia response and immune cells infiltration in tumor microenvironment of liver cancer. S100B maybe serve as a novel target for future HCC therapies., Competing Interests: The authors declare that they have no competing interests., (© 2022 Yan et al.)

Background and Objective: In the application of wearable heart-monitors, it is of great significance to analyze electrocardiogram (ECG) signals for anomaly detection. ECG arrhythmia classification remains an open problem in that it cannot easily recognize data from minority classes due to the imbalanced dataset and particular characteristic of the time series signal. In this study, a novel method is presented as a possible solution to imbalanced classification problems., Methods: An improved data augmentation method based on variational auto-encoder (VAE) and auxiliary classifier generative adversarial network (ACGAN) is implemented to address the difficulties resulting from the imbalanced dataset. Based on the augmented dataset, convolutional neural network (CNN) classifiers are employed to automatically recognize arrhythmias using two-dimensional ECG images., Results: In experimental studies conducted with the MIT-BIH arrhythmia database, the proposed method achieves 98.45% accuracy and 97.03% sensitivity. The sensitivities of two minority classes achieve 95.83% and 97.37%, respectively., Conclusion: In imbalanced classification, the sensitivity of minority class is a key evaluation indicator. One of the significant contributions of this study is that the proposed method can obtain higher sensitivity of minority class. The experimental results demonstrate that the proposed method for ECG arrhythmia calssification under imbalanced data has better performance compared with traditional cropping augmentation methods and traditional classifiers., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021. Published by Elsevier B.V.)

Hepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors with high mortality worldwide. Spermatogenesis-associated serine-rich 2 (SPATS2) could be a novel diagnostic and prognostic biomarker in HCC. However, the regulatory mechanism of SPATS2 in HCC requires further elucidation. Therefore, the study's objective was to investigate this process in HCC. In this study, we found that SPATS2 is significantly upregulated in HepG2 cells to promote cell growth and migration. SPATS2 is the target transcript of lncRNA SNHG5. SPATS2 positively affects the proliferation and migration of HepG2 cells caused by the higher expression of SNHG5. Mechanistically, we identified that the elevated of SPATS2 was attributed to SNHG5 related hypomethylation of SPATS2. SNHG5 reduced the expression of DNMT3a to suppress the methylation level of SPATS2. Taken together, our results uncover a novel epigenetic regulatory mechanism of lncRNA SNHG5-DNMT3a axis-related SPATS2 expression underlying HCC progression. This may serve as a novel prognostic marker and a promising therapeutic target for the treatment of HCC., Competing Interests: The authors declare that they have no financial conflicts of interest.

This article investigates the stabilization control and stabilizing data-rate condition problems for networked control systems, which transmit signals from the sensor to the controller over the communication network with denial-of-service (DoS) attacks. Considering a class of DoS attacks that only constrain its frequency and duration, we aim to explore the constraint condition for stabilization and minimum stabilizing data rate of the networked control systems. The framework consists of two main parts. The first part considers the stabilizing control by the state-feedback approach under ideal bandwidth capacity. While the second part characterizes the average stabilizing data rate in terms of the eigenvalues of system matrix and DoS constraint functions to explicitly reveal the relationship between the attacks and the network bandwidth capacity. The stabilizing result is novel in the sense that the DoS-attack intensity, which is characterized by its frequency and duration, can vary for different time intervals. With this feature, the minimum average data-rate condition can vary for different time intervals according to the intensity of DoS attacks.

Strain XQZ8 T , isolated from the rhizosphere soil of a Populus popularis plant in China, was characterized using a polyphasic taxonomic approach. Cells were Gram-negative, aerobic, non-spore-forming, and rod-shaped. Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain XQZ8 T was related to members of the genus Rhizobium and had the highest 16S rRNA gene sequence similarity to Rhizobium smilacinae PTYR-5 T (96.6%). The average nucleotide identity and digital DNA-DNA hybridization value between strain XQZ8 T and R. smilacinae PTYR-5 T were 77.5% and 21.4%, respectively. TYGS whole-genome-based taxonomic and multi-locus sequence analyses of three concatenated housekeeping genes (atpD-recA-glnII) further indicated that strain XQZ8 T was a new member of the genus Rhizobium. The major cellular fatty acids included summed feature 8 (C 18:1 ω7c/C 18:1 ω6c), summed feature 2 (C 12:0 aldehyde/unknown 10.928), C 16:0 , and C 19:0 cyclo ω8c. The major respiratory quinones were Q-9 and Q-10. The polar lipids were phosphatidylglycerol, phosphatidylcholine, phosphatidylethanolamine, phosphatidyldimethylethanolamine, phosphatidylmonomethylethanolamine, an unidentified glycophospholipid, and three unidentified lipids. The genomic DNA G + C content of the strain was 60.1 mol%. Based on the phylogenetic, phenotypic, and genotypic characteristics, strain XQZ8 T represents a novel species of the genus Rhizobium, for which the name Rhizobium populisoli sp. nov. is proposed. The type strain is XQZ8 T (= JCM 34442 T  = GDMCC 1.2201 T )., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Coking wastewater is typically refractory, mainly due to its biological toxicity and complex composition. In this study, a novel integrated biological-electrocatalytic process consisting of two three-dimensional electrochemical reactors (3DERs), two biological aerated filters (BAFs), and a three-dimensional biofilm electrode reactor (3DBER) is developed for the advanced treatment of coking wastewater. 73.21% of chemical oxygen demand (COD), 38.02% of ammonium nitrogen (NH 4 + -N) and 91.46% of nitrate nitrogen (NO 3 - -N) are removed by 3DERs. BAFs mainly convert NH 4 + -N to NO 3 - -N through microbial nitrification. The 3DBER removes the residual NO 3 - -N by bio-electrochemical denitrification. The integrated system can eliminate 74.72-83.27% of COD, 99.38-99.74% of NH 4 + -N, and 69.64-99.83% of total nitrogen from coking wastewater during the continuous operation, as well as significantly reducing the toxicity of the wastewater. The superiorities of the integrated 3DERs/BAFs/3DBER system recommend the application of such biological-electrocatalytic technology in the treatment of highly toxic wastewater., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background and Objective: Medical image segmentation plays an important role in clinic. Recently, with the development of deep learning, many convolutional neural network (CNN)-based medical image segmentation algorithms have been proposed. Among them, U-Net is one of the most famous networks. However, the standard convolutional layers used by U-Net limit its capability to capture abundant features. Additionally, the consecutive maximum pooling operations in U-Net cause certain features to be lost. This paper aims to improve the feature extraction capability of U-Net and reduce the feature loss during the segmentation process. Meanwhile, the paper also focuses on improving the versatility of the proposed segmentation model., Methods: Firstly, in order to enable the model to capture richer features, we have proposed a novel multiscale convolutional block (MCB). MCB adopts a wider and deeper structure, which can be applied to different types of segmentation tasks. Secondly, a hybrid down-sampling block (HDSB) has been proposed to reduce the feature loss via replacing the maximum pooling layer. Thirdly, we have proposed a context module (CIF) based on atrous convolution and SKNet to extract sufficient context information. Finally, we combined the CIF module with Skip Connection of U-Net, and further proposed the Skip Connection+ structure., Results: We name the proposed network MHSU-Net. MHSU-Net has been evaluated on three different datasets, including lung, cell contour, and pancreas. Experimental results demonstrate that MHSU-Net outperforms U-Net and other state-of-the-art models under various evaluation metrics, and owns greater potential in clinical applications., Conclusions: The proposed modules can greatly improve the feature extraction capability of the segmentation model and effectively reduce the feature loss during the segmentation process. MHSU-Net can also be applied to different types of medical image segmentation tasks., Competing Interests: Declaration of Competing Interest Authors declare that they have no conflict of interest., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Accurate segmentation of medical images plays an essential role in their analysis and has a wide range of research and application values in fields of practice such as medical research, disease diagnosis, disease analysis, and auxiliary surgery. In recent years, deep convolutional neural networks have been developed that show strong performance in medical image segmentation. However, because of the inherent challenges of medical images, such as irregularities of the dataset and the existence of outliers, segmentation approaches have not demonstrated sufficiently accurate and reliable results for clinical employment. Our method is based on three key ideas: (1) integrating the BConvLSTM block and the Attention block to reduce the semantic gap between the encoder and decoder feature maps to make the two feature maps more homogeneous, (2) factorizing convolutions with a large filter size by Redesigned Inception, which uses a multiscale feature fusion method to significantly increase the effective receptive field, and (3) devising a deep convolutional neural network with multiscale feature fusion and a Attentive BConvLSTM mechanism, which integrates the Attentive BConvLSTM block and the Redesigned Inception block into an encoder-decoder model called Attentive BConvLSTM U-Net with Redesigned Inception (IBA-U-Net). Our proposed architecture, IBA-U-Net, has been compared with the U-Net and state-of-the-art segmentation methods on three publicly available datasets, the lung image segmentation dataset, skin lesion image dataset, and retinal blood vessel image segmentation dataset, each with their unique challenges, and it has improved the prediction performance even with slightly less calculation expense and fewer network parameters. By devising a deep convolutional neural network with a multiscale feature fusion and Attentive BConvLSTM mechanism, medical image segmentation of different tasks can be completed effectively and accurately with only 45% of U-Net parameters., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Medical image segmentation is a typical task in medical image processing and critical foundation in medical image analysis. U-Net is well-liked in medical image segmentation, but it doesn't fully explore useful features of the channel and capitalize on the contextual information. Therefore, we present an improved U-Net with residual connections, adding a plug-and-play, very portable channel attention (CA) block and a hybrid dilated attention convolutional (HDAC) layer to perform medical image segmentation for different tasks accurately and effectively, and call it HDA-ResUNet, in which we fully utilize advantages of U-Net, attention mechanism and dilated convolution. In contrast to the simple copy splicing of U-Net in the skip connection, the channel attention block is inserted into the extracted feature map of the encoding path before decoding operation. Since this block is lightweight, we can apply it to multiple layers in the backbone network to optimize the channel effect of this layer's coding operation. In addition, the convolutional layer at the bottom of the "U"-shaped network is replaced by a hybrid dilated attention convolutional (HDAC) layer to fuse information from different sizes of receptive fields. The proposed HDA-ResUNet is evaluated on four datasets: liver and tumor segmentation (LiTS 2017), lung segmentation (Lung dataset), nuclear segmentation in microscope images (DSB 2018) and neuron structure segmentation (ISBI 2012). The dice global scores of liver and tumor segmentation (LiTS 2017) reach 0.949 and 0.799. The dice coefficients of lung segmentation and nuclear segmentation are 0.9797 and 0.9081 respectively, and the information theoretic score for the last one is 0.9703. The segmentation results are all more accurate than U-Net with fewer parameters, and the problem of slow convergence speed of U-Net on DBS 2018 is solved., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

A versatile microporous metal-organic framework (MOF), {[Cu(TIA)]·1.5CH 3 OH} n ( Cu-1 ), was successfully obtained via the solvothermal reaction of cuprous(II) salt with the bifunctional ligand 3-(1 H -1,2,4-triazol-1-yl)isophthalic acid. Single-crystal X-ray diffraction studies indicate that Cu-1 contains an apo three-dimensional skeleton and two types of one-dimensional channels. The framework of Cu-1 has excellent acid-alkali resistance and thermal stability, which is stable in a pH = 2-13 aqueous solution and an 260 °C air environment. In addition, the microporous copper MOF shows very high uptakes of CO 2 (180 cm 3 ·g -1 ) and C 2 H 2 (113 cm 3 ·g -1 ) at 273 K and displays excellent adsorption selectivity for small molecular gases. The ideal adsorbed solution theory selectivity values for C 2 H 2 /C 2 H 4 , CO 2 /CH 4 , and CO 2 /N 2 are 2, 9, and 22 at 298 K, respectively. At the same time, breakthrough experiments for CO 2 /CH 4 , CO 2 /N 2 , and C 2 H 2 /C 2 H 4 were further conducted to verify the efficient separation performances.

This paper addresses the synchronization control problem of leader-follower multiagent systems with each follower described by a class of high-order nonlinear multiple-input-multiple-output (MIMO) dynamics in the presence of time delays and actuator faults. A distributed synchronization scheme with guaranteed synchronization performance based on the radial basis function neural network (RBF NN) is introduced. We propose an augmented quadratic Lyapunov function by incorporating the lower bounds of control gain matrices and the actuator healthy indicator, and the problems caused by the unknown time-varying control gain matrices, actuator faults, and coupling terms among agents are solved. Meanwhile, the output of followers can track that of the leader and the steady state, and the transient performance of synchronization can be guaranteed, while all the other signals in the closed-loop system are guaranteed to be bounded. Finally, numerical analysis has been carried out to verify the effectiveness of the proposed controller.

Background and Objective: A realistic virtual surgery simulation needs to simulate smoke as electrical cutting causes thermal tissue damage. The vortex particle method of simulating smoke can realistically present the vortex details and motion trajectory of the smoke, but there is high computational cost., Methods: To address this problem, we propose the 3D Vortex Particles in Cube Algorithm (3D-VPICA). 3D-VPICA can realistically show the visual effect of smoke and reduce the computational cost. In addition, in order to enhance the reality of the smoke, we propose the Auxiliary Particles Algorithm (APA) method to deal with the collision problem of smoke., Results: The 3D-VPICA can calculate the velocity of the vortex particles speedily with the help of cube grids and with the complexity decreasing from O(N 2 ) to O(N) + O(Mlog  2 M). The APA can ensure that boundary conditions are satisfied when the smoke collides with irregular surfaces. Experimental results show that 3D-VPICA is faster than traditional methods of smoke simulation and that APA is successful in simulating smoke colliding with moving objects with irregular surfaces., Conclusions: The proposed 3D smoke simulation method was applied to a virtual surgery system using a high frequency electric knife. The cutting and coagulate operations were fluent and the smoke flowed with fidelity., Competing Interests: Declaration of competing interest We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted., (Copyright © 2020. Published by Elsevier B.V.)

Background and Objective: In the virtual surgery simulation system, the reconstruction of a highly precise soft tissue 3D model is an effective method to improve the user's visual telepresence. However, the traditional point cloud generation method based on subdivision and filling is unsatisfactory due to its low accuracy and slow speed., Methods: To address this problem, we present a novel 3D point cloud reconstructing model based on Morphing. The 3D surface model of soft tissue (live) is obtained from a series of 2D CT images using Mimics. The 3D voxel model of soft tissue is reconstructed through a sequential change of the 3D surface model by utilizing Morphing. A nonlinear interpolation method is used to fit the irregular shape of the model and improve simulation accuracy., Results: The point cloud model builds from discrete points, avoiding the problems of instability and computational complexity, which are inherent in both the surface and volume models for soft tissue. Compared with the volumetric subdividing and voxel filling method, the simulation results show that the 3D cloud model reconstructed based on Morphing is more fast, accurate and consistent with the real soft tissue., Conclusions: The simulating experiment of soft tissue deformation using 3D point cloud model which reconstructed using moprhing proved our method is effective and correct., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020. Published by Elsevier B.V.)