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Early systemic anticoagulation reduces hospital readmission in acute necrotizing pancreatitis patients:A retrospective cohort study

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Hepatobiliary & Pancreatic Diseases International 2024年第1期23卷 77-82页

作者： Wen-Jian Mao Jing Zhou Guo-Fu Zhang Fa-Xi Chen Jing-Zhu Zhang Bai-Qiang Li Lu Ke Wei-Qin Li Department of Critical Care Medicine Jinling HospitalNanjing Medical UniversityNanjing 210002China Department of Critical Care Medicine Jinling HospitalMedical School of Nanjing UniversityNanjing 210002China national institute of healthcare data science Nanjing UniversityNanjing 210010China

Background:Early systemic anticoagulation(SAC)is a common practice in acute necrotizing pancreatitis(ANP),and its impact on in-hospital clinical outcomes had been assessed.However,whether it affects long-term outcomes is unknown.This study aimed to evaluate the effect of SAC on 90-day readmission and other long-term outcomes in ANP patients.Methods:During January 2013 and December 2018,ANP patients admitted within 7 days from the onset of abdominal pain were screened.The primary outcome was 90-day readmission after discharge.Cox proportional-hazards regression model and mediation analysis were used to define the relationship between early SAC and 90-day readmission.Results:A total of 241 ANP patients were enrolled,of whom 143 received early SAC during their hospitalization and 98 did not.Patients who received early SAC experienced a lower incidence of splanchnic venous thrombosis(SVT)[risk ratio(RR)=0.40,95%CI:0.26-0.60,P<0.01]and lower 90-day readmission with an RR of 0.61(95%CI:0.41-0.91,P=0.02)than those who did not.For the quality of life,patients who received early SAC had a significantly higher score in the subscale of vitality(P=0.03)while the other subscales were all comparable between the two groups.Multivariable Cox regression model showed that early SAC was an independent protective factor for 90-day readmission after adjusting for potential confounders with a hazard ratio of 0.57(95%CI:0.34-0.96,P=0.04).Mediation analysis showed that SVT mediated 37.0%of the early SAC-90-day readmission causality.Conclusions:The application of early SAC may reduce the risk of 90-day readmission in the survivors of ANP patients,and reduced SVT incidence might be the primary contributor.

关键词： Anticoagulation Splanchnic venous thrombosis Acute necrotizing pancreatitis Readmission Long-term outcomes

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Long-term functional maintenance of primary hepatocytes in vitro using macroporous hydrogels engineered through liquid-liquid phase separation

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Nano Research 2024年第3期17卷 1725-1736页

作者： Yang Sun Sheng Yin Jian Cui Zhongxia Wang Yueying Han Ding Ma Shuo Wang Junhua Wu Yi Cao Chunping Jiang Xiaosong Gu Jinan Microecological Biomedicine Shandong Laboratory Jinan 250021China Collaborative Innovation Center of Advanced Microstructures National Laboratory of Solid State MicrostructureKey Laboratory of Intelligent Optical Sensing and ManipulationMinistry of EducationDepartment of PhysicsNanjing UniversityNanjing 210093China Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital of Nanjing University Medical SchoolNanjing 210093China national institute of healthcare data science at nanjing university Nanjing UniversityNanjing 210093China

Preserving the functionality of hepatocytes in vitro poses a significant challenge in liver tissue engineering and bioartificial liver,as these cells rapidly lose their metabolic and functional characteristics after isolation.Inspired by the macroporous structures found in native liver tissues,here we develop synthetic hydrogel scaffolds that closely mimic the liver’s structural organization through the phase separation between polyethylene glycol(PEG)and polysaccharides.Our hydrogels exhibit interconnected macroporous structures and appropriate mechanical properties,providing an optimal microenvironment conducive to hepatocyte adhesion and the formation of sizable aggregates.Compared to two-dimensional hepatocyte cultures,enhanced functionalities of hepatocytes cultured in our macroporous hydrogels were observed for 14 days,as evidenced by quantitative reverse-transcription–polymerase chain reactions(qRT-PCR),immunofluorescence,and enzyme linked immunosorbent assay(ELISA)analyses.Protein sequencing data further confirmed the establishment of cell–cell interactions among hepatocytes when cultured in our hydrogels.Notably,these hepatocytes maintained a protein expression lineage that closely resembled freshly isolated hepatocytes,particularly in the Notch and tumor necrosis factor(TNF)signaling pathways.These results suggest that the macroporous hydrogels are attractive scaffolds for liver tissue engineering.

关键词： liver tissue engineering phase separation hepatocytes macroporous hydrogel

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A compact multi-pixel superconducting nanowire single-photon detector array supporting gigabit space-to-ground communications

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Light(science & Applications) 2024年第2期13卷 254-266页

作者： Hao Hao Qing-Yuan Zhao Yang-Hui Huang Jie Deng Fan Yang Sai-Ying Ru Zhen Liu Chao Wan Hao Liu Zhi-Jian Li Hua-Bing Wang Xue-Cou Tu La-Bao Zhang Xiao-Qing Jia Xing-Long Wu Jian Chen Lin Kang Pei-Heng Wu Research institute of Superconductor Electronics(RISE) School of Electronic Science and EngineeringNanjing UniversityNanjingJiangsu 210023China Purple Mountain Laboratories NanjingJiangsu 211111China Hefei national Laboratory HefeiAnhui 230088China national Laboratory of Solid State Microstructures and Department of Physics Nanjing UniversityNanjing 210023China

Classical and quantum space-to-ground communications necessitate highly sensitive receivers capable of extracting information from modulated photons to extend the communication distance from near-earth orbits to deep space explorations.To achieve gigabit data rates while mitigating strong background noise photons and beam drift in a highly attenuated free-space channel,a comprehensive design of a multi-functional detector is indispensable.In this study,we present an innovative compact multi-pixel superconducting nanowire single-photon detector array that integrates near-unity detection efficiency(91.6%),high photon counting rate(1.61 Gcps),large dynamic range for resolving different photon numbers(1-24),and four-quadrant position sensing function all within one device.Furthermore,we have constructed a communication testbed to validate the advantages offered by such an architecture.Through 8-PPM(pulse position modulation)format communication experiments,we have achieved an impressive maximum data rate of 1.5 Gbps,demonstrating sensitivities surpassing previous benchmarks at respective speeds.By incorporating photon number information into error correction codes,the receiver can tolerate maximum background noise levels equivalent to 0.8 photons/slot at a data rate of 120 Mbps—showcasing a great potential for daylight operation scenarios.Additionally,preliminary beam tracking tests were conducted through open-loop scanning techniques,which revealed clear quantitative dependence indicating sensitivity variations based on beam location.Based on the device characterizations and communication results,we anticipate that this device architecture,along with its corresponding signal processing and coding techniques,will be applicable in future space-to-ground communication tasks.

关键词： photon supporting correction

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Deep-learning-assisted online surface roughness monitoring in ultraprecision fly cutting

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science China(Technological sciences) 2024年第5期67卷 1482-1497页

作者： SHEHZAD Adeel RUI XiaoTing DING YuanYuan ZHANG JianShu CHANG Yu LU HanJing CHEN YiHeng institute of Launch Dynamics Nanjing University of Science and TechnologyNanjing210094China national Key Laboratory of Complex Multibody System Dynamics Nanjing210094China Automotive Engineering Centre University of Engineering and TechnologyLahore54890Pakistan School of science Nanjing University of Science and TechnologyNanjing210094China College of Engineering Peking UniversityBeijing100871China

Surface roughness is one of the most critical attributes of machined components,especially those used in high-performance systems.Online surface roughness monitoring offers advancements comparable to post-process inspection methods,reducing inspection time and costs and concurrently reducing the likelihood of defects.Currently,online monitoring approaches for surface roughness are constrained by several limitations,including the reliance on handcrafted feature extraction,which necessitates the involvement of human experts and entails time-consuming processes.Moreover,the prediction models trained under one set of cutting conditions exhibit poor performance when applied to different experimental settings.To address these challenges,this work presents a novel deep-learning-assisted online surface roughness monitoring method for ultraprecision fly cutting of copper workpieces under different cutting conditions.Tooltip acceleration signals were acquired during each cutting experiment to develop two datasets,and no handcrafted features were extracted.Five deep learning models were developed and evaluated using standard performance metrics.A convolutional neural network stacked on a long short-term memory network outperformed all other network models,yielding exceptional results,including a mean absolute percentage error as low as 1.51%and an R2value of 96.6%.Furthermore,the robustness of the proposed model was assessed via a validation cohort analysis using experimental data obtained using cutting parameters different from those previously employed.The performance of the model remained consistent and commendable under varied conditions,asserting its applicability in real-world scenarios.

关键词： online surface roughness monitoring UPFC deep learning CNN-LSTM vibration signal

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Research on simulation of gun muzzle flow field empowered by artificial intelligence

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Defence Technology（防务技术） 2024年第2期32卷 196-208页

作者： Mengdi Zhou Linfang Qian Congyong Cao Guangsong Chen Jin Kong Ming-hao Tong School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing210094China Northwest institute of Mechanical and Electrical Engineering Xianyang712099ShaanxiChina School of Automation Nanjing University of Science and TechnologyNanjing210094China

Artificial intelligence technology is introduced into the simulation of muzzle flow field to improve its simulation efficiency in this paper.A data-physical fusion driven framework is proposed.First,the known flow field data is used to initialize the model parameters,so that the parameters to be trained are close to the optimal value.Then physical prior knowledge is introduced into the training process so that the prediction results not only meet the known flow field information but also meet the physical conservation laws.Through two examples,it is proved that the model under the fusion driven framework can solve the strongly nonlinear flow field problems,and has stronger generalization and expansion.The proposed model is used to solve a muzzle flow field,and the safety clearance behind the barrel side is divided.It is pointed out that the shape of the safety clearance under different launch speeds is roughly the same,and the pressure disturbance in the area within 9.2 m behind the muzzle section exceeds the safety threshold,which is a dangerous area.Comparison with the CFD results shows that the calculation efficiency of the proposed model is greatly improved under the condition of the same calculation accuracy.The proposed model can quickly and accurately simulate the muzzle flow field under various launch conditions.

关键词： Muzzle flow field Artificial intelligence Deep learning data-physical fusion driven Shock wave

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Security and Privacy in Solar Insecticidal Lamps Internet of Things:Requirements and Challenges

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 58-73页

作者： Qingsong Zhao Lei Shu Kailiang Li Mohamed Amine Ferrag Ximeng Liu Yanbin Li the College of Artificial Intelligence Nanjing Agricultural UniversityNanjing 210031 the State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210023 the State Key Laboratory of Cryptology Beijing 100878China IEEE the School of Engineering University of LincolnLincoln LN67TSUK the Artificial Intelligence and Digital science Research Center Technology Innovation InstituteMasdar City 9639UAE the College of Computer and data science Fuzhou UniversityFuzhou 350108China

Solar insecticidal lamps(SIL) can effectively control pests and reduce the use of pesticides. Combining SIL and Internet of Things(IoT) has formed a new type of agricultural IoT,known as SIL-IoT, which can improve the effectiveness of migratory phototropic pest control. However, since the SIL is connected to the Internet, it is vulnerable to various security issues.These issues can lead to serious consequences, such as tampering with the parameters of SIL, illegally starting and stopping SIL,etc. In this paper, we describe the overall security requirements of SIL-IoT and present an extensive survey of security and privacy solutions for SIL-IoT. We investigate the background and logical architecture of SIL-IoT, discuss SIL-IoT security scenarios, and analyze potential attacks. Starting from the security requirements of SIL-IoT we divide them into six categories, namely privacy, authentication, confidentiality, access control, availability,and integrity. Next, we describe the SIL-IoT privacy and security solutions, as well as the blockchain-based solutions. Based on the current survey, we finally discuss the challenges and future research directions of SIL-IoT.

关键词： Challenges Internet of Things(IoT) privacy and security security requirements solar insecticidal lamps(SIL)

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Design,preparation,and characterization of a novel ZnO/CuO/Al energetic diode with dual functionality:Logic and destruction

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Defence Technology（防务技术） 2024年第4期34卷 57-68页

作者： Jialu Yang Jiaheng Hu Yinghua Ye Jianbing Xu Yan Hu Ruiqi Shen School of Chemistry and Chemical Engineering Nanjing University of Science and TechnologyNanjing 210094China Micro-Nano Energetic Devices Key Laboratory of MIIT Nanjing 210094China institute of Space Propulsion Nanjing University of Science and TechnologyNanjing 210094China

Self-destructing chips have promising applications for securing data.This paper proposes a new concept of energetic diodes for the first time,which can be used for self-destructive chips.A simple two-step electrochemical deposition method is used to prepare ZnO/CuO/Al energetic diode,in which N-type ZnO and P-type CuO are constricted to a PN junction.This paper comprehensively discusses the material properties,morphology,semiconductor characteristics,and exploding performances of the energetic diode.Experimental results show that the energetic diode has typical rectification with a turn-on voltage of about 1.78 V and a reverse leakage current of about 3×10^(-4)A.When a constant voltage of 70 V loads to the energetic diode in the forward direction for about 0.14 s or 55 V loads in the reverse direction for about 0.17 s,the loaded power can excite the energetic diode exploding and the current rises to about100 A.Due to the unique performance of the energetic diode,it has a double function of rectification and explosion.The energetic diode can be used as a logic element in the normal chip to complete the regular operation,and it can release energy to destroy the chip accurately.

关键词： Energetic diode ZnO—CuO—Al thermite ZnO/CuO PN junction Electrical explosion performance Self-destructing chips

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The relationship between compartment models and their stochastic counterparts:A comparative study with examples of the COVID-19 epidemic modeling

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Journal of Biomedical Research 2024年第2期38卷 175-188,I0016-I0018页

作者： Ziyu Zhao Yi Zhou Jinxing Guan Yan Yan Jing Zhao Zhihang Peng Feng Chen Yang Zhao Fang Shao Department of Biostatistics School of Public HealthNanjing Medical UniversityNanjingJiangsu 211166China nanjing Hanwei Public Health Research institute Co. LtdNanjingJiangsu 210005China China International Cooperation Center for Environment and Human Health Center for Global HealthNanjing Medical UniversityNanjingJiangsu 211166China The Center of Biomedical Big data and the Laboratory of Biomedical Big data Nanjing Medical UniversityNanjingJiangsu 211166China Jiangsu Key Lab of Cancer Biomarkers Prevention and TreatmentCollaborative Innovation Center for Cancer Personalized MedicineNanjing Medical UniversityNanjingJiangsu 211166China

Deterministic compartment models(CMs)and stochastic models,including stochastic CMs and agent-based models,are widely utilized in epidemic modeling.However,the relationship between CMs and their corresponding stochastic models is not well understood.The present study aimed to address this gap by conducting a comparative study using the susceptible,exposed,infectious,and recovered(SEIR)model and its extended CMs from the coronavirus disease 2019 modeling literature.We demonstrated the equivalence of the numerical solution of CMs using the Euler scheme and their stochastic counterparts through theoretical analysis and simulations.Based on this equivalence,we proposed an efficient model calibration method that could replicate the exact solution of CMs in the corresponding stochastic models through parameter adjustment.The advancement in calibration techniques enhanced the accuracy of stochastic modeling in capturing the dynamics of epidemics.However,it should be noted that discrete-time stochastic models cannot perfectly reproduce the exact solution of continuous-time CMs.Additionally,we proposed a new stochastic compartment and agent mixed model as an alternative to agent-based models for large-scale population simulations with a limited number of agents.This model offered a balance between computational efficiency and accuracy.The results of this research contributed to the comparison and unification of deterministic CMs and stochastic models in epidemic modeling.Furthermore,the results had implications for the development of hybrid models that integrated the strengths of both frameworks.Overall,the present study has provided valuable epidemic modeling techniques and their practical applications for understanding and controlling the spread of infectious diseases.

关键词： compartment models agent-based models compartment-agent mixed models comparative study COVID-19

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Generation of orbital angular momentum hologram using a modified U-net

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Chinese Physics B 2024年第3期33卷 401-407页

作者：郑志刚韩菲菲王乐赵生妹 institute of Signal Processing and Transmission Nanjing University of Posts and TelecommunicationsNanjing 210003China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology (Ministry of Education) Nanjing University of Posts and TelecommunicationsNanjing 210003China national Laboratory of Solid State Microstructures Nanjing UniversityNanjing 210093China

Orbital angular momentum(OAM)holography has become a promising technique in information encryption,data storage and opto-electronic computing,owing to the infinite topological charge of one single OAM mode and the orthogonality of different OAM modes.In this paper,we propose a novel OAM hologram generation method based on a densely connected U-net(DCU),where the densely connected convolution blocks(DCB)replace the convolution blocks of the U-net.Importantly,the reconstruction process of the OAM hologram is integrated into DCU as its output layer,so as to eliminate the requirement to prepare training data for the OAM hologram,which is required by conventional neural networks through an iterative algorithm.The experimental and simulation results show that the OAM hologram can rapidly be generated with the well-trained DCU,and the reconstructed image's quality from the generated OAM hologram is significantly improved in comparison with those from the Gerchberg-Saxton generation method,the Gerchberg-Saxton based generation method and the U-net method.In addition,a 10-bit OAM multiplexing hologram scheme is numerically demonstrated to have a high capacity with OAM hologram.

关键词： orbital angular momentum(OAM) holography OAM holography deep learning

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Phosphorylated protein chip combined with artificial intelligence tools for precise drug screening

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Journal of Biomedical Research 2024年第3期38卷 195-205页

作者： Katsuhisa Horimoto Yuki Suyama Tadamasa Sasaki Kazuhiko Fukui Lili Feng Meiling Sun Yamin Tang Yixuan Zhang Dongyin Chen Feng Han SOCIUM Inc. Tokyo 1350064Japan International Medical Center Saitama Medical UniversitySaitama 350-1298Japan Artificial Intelligence Research Center National Institute of Advanced Industrial Science and TechnologyTokyo 1350064Japan Department of Informatics and data science Sanyo-Onoda City UniversityYamaguchi 7560884Japan International Joint Laboratory for Drug Target of Critical Illnesses School of PharmacyNanjing Medical UniversityNanjingJiangsu 211166China Department of Physiology School of Basic Medical SciencesNanjing Medical UniversityNanjingJiangsu 211166China Gusu School Nanjing Medical UniversitySuzhouJiangsu 215001China national Vaccine Innovation Platform Nanjing Medical UniversityNanjingJiangsu 211166China

We have developed a protein array system,named"Phospho-Totum",which reproduces the phosphorylation state of a sample on the array.The protein array contains 1471 proteins from 273 known signaling pathways.According to the activation degrees of tyrosine kinases in the sample,the corresponding groups of substrate proteins on the array are phosphorylated under the same conditions.In addition to measuring the phosphorylation levels of the 1471 substrates,we have developed and performed the artificial intelligence-assisted tools to further characterize the phosphorylation state and estimate pathway activation,tyrosine kinase activation,and a list of kinase inhibitors that produce phosphorylation states similar to that of the sample.The Phospho-Totum system,which seamlessly links and interrogates the measurements and analyses,has the potential to not only elucidate pathophysiological mechanisms in diseases by reproducing the phosphorylation state of samples,but also be useful for drug discovery,particularly for screening targeted kinases for potential drug kinase inhibitors.

关键词： Phospho-Totum protein array signal transduction pathways artificial intelligence tools drug screening

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