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Machine learning identifies the risk of complications after laparoscopic radical gastrectomy for gastric cancer

World Journal of Gastroenterology 2024年第1期30卷 79-90页

作者： Qing-Qi Hong Su Yan Yong-Liang Zhao lin fan Li Yang Wen-Bin Zhang Hao Liu He-Xin lin Jian Zhang Zhi-Jian Ye Xian Shen Li-Sheng Cai Guo-Wei Zhang Jia-Ming Zhu Gang Ji Jin-Ping Chen Wei Wang Zheng-Rong Li Jing-Tao Zhu Guo-Xin Li Jun You Department of Gastrointestinal Oncology Surgery The First Affiliated Hospital of Xiamen UniversitySchool of MedicineXiamen 361001Fujian ProvinceChina Department of Gastrointestinal Surgery Qinghai University Affiliated HospitalXining 810000Qinghai ProvinceChina Department of General Surgery and Center of Minimal Invasive Gastrointestinal Surgery The First Hospital Affiliated to Army Medical UniversityChongqing 400038China Department of General Surgery The First Affiliated Hospital of Xi'an Jiaotong UniversityXi'an 710061Shaanxi ProvinceChina Department of General Surgery The First Affiliated Hospital of Nanjing Medical UniversityNanjing 210029Jiangsu ProvinceChina Department of Gastrointestinal Surgery The First Affiliated Hospital of Xinjiang Medical UniversityUrmuqi 830054Xinjiang Uygur Autonomous RegionChina Department of General Surgery Nanfang HospitalSouthern Medical UniversityGuangzhou 510515Guangdong ProvinceChina Department of Gastrointestinal Surgery Affiliated Hangzhou First People's HospitalZhejiang University School of MedicineHangzhou 310006Zhejiang ProvinceChina Department of Gastrointestinal Surgery Zhongshan Hospital of Xiamen UniversityXiamen 361004Fujian ProvinceChina Department of Surgery The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical UniversityWenzhou 325027Zhejiang ProvinceChina Department of General Surgery Unit 4 Zhangzhou Affiliated Hospital of Fujian Medical UniversityZhangzhou 363000Fujian ProvinceChina Department of Gastrointestinal Surgery The Second Affiliated Hospital of Xiamen Medical CollegeXiamen 361021Fujian ProvinceChina Department of Gastrointestinal Nutrition and Hernia Surgery The Second Hospital of Jilin UniversityChangchun 130041Jilin ProvinceChina Department of Digestive Diseases Xijing HospitalAir Force Military Medical UniversityXi'an 710032Shaanxi ProvinceChina Department of Gastrointestinal Surgery Quanzhou First Hospital Affiliated to Fujian Medical UniversityQuanzhou 362002Fujian Provin

BACKGROUND Laparoscopic radical gastrectomy is widely used,and perioperative complications have become a highly concerned issue.AIM To develop a predictive model for complications in laparoscopic radical gastrectomy for gastric cancer to better predict the likelihood of complications in gastric cancer patients within 30 days after surgery,guide perioperative treatment strategies for gastric cancer patients,and prevent serious complications.METHODS In total,998 patients who underwent laparoscopic radical gastrectomy for gastric cancer at 16 Chinese medical centers were included in the training group for the complication model,and 398 patients were included in the validation group.The clinicopathological data and 30-d postoperative complications of gastric cancer patients were collected.Three machine learning methods,lasso regression,random forest,and artificial neural networks,were used to construct postoperative complication prediction models for laparoscopic distal gastrectomy and laparoscopic total gastrectomy,and their prediction efficacy and accuracy were evaluated.RESULTS The constructed complication model,particularly the random forest model,could better predict serious complications in gastric cancer patients undergoing laparoscopic radical gastrectomy.It exhibited stable performance in external validation and is worthy of further promotion in more centers.CONCLUSION Using the risk factors identified in multicenter datasets,highly sensitive risk prediction models for complications following laparoscopic radical gastrectomy were established.We hope to facilitate the diagnosis and treatment of preoperative and postoperative decision-making by using these models.

关键词： Gastric cancer Laparoscopic radical gastrectomy Postoperative complications Laparoscopic total gastrectomy

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Epileptic brain network mechanisms and neuroimaging techniques for the brain network

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Neural Regeneration Research 2024年第12期19卷 2637-2648页

作者： Yi Guo Zhonghua lin Zhen fan Xin Tian Department of Neurology Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengduSichuan ProvinceChina Sichuan Provincial Center for Mental Health Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengduSichuan ProvinceChina Department of Geriatrics Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengduSichuan ProvinceChina Department of Neurology Chongqing Key Laboratory of NeurologyThe First Affiliated Hospital of Chongqing Medical UniversityChongqingChina

Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.

关键词： electrophysiological techniques epilepsy functional brain network functional magnetic resonance imaging functional near-infrared spectroscopy machine leaning molecular imaging neuroimaging techniques structural brain network virtual epileptic models

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Advancing neuroscience through real-time processing of big data:Transition from open-loop to closed-loop paradigms

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Zoological Research 2024年第3期45卷 518-519页

作者： Yu-fan Wang Jiu-lin Du Institute of Neuroscience State Key Laboratory of NeuroscienceCenter for Excellence in Brain Science and Intelligence TechnologyChinese Academy of SciencesShanghai 200031China University of Chinese Academy of Sciences Beijing 100049China School of Life Science and Technology ShanghaiTech UniversityShanghai 200031China

The brain functions as a closed-loop system that continuously generates behavior in response to the external environment and adjusts actions based on the outcomes.Traditional research methodologies in neuroscience,especially those employed in brain imaging experiments,have mainly adopted an open-loop paradigm(Grosenick et al.,2015).Functional neural circuits are analyzed offline and subsequently tested through manipulation of neuronal activities within specific regions or with genetic markers.By establishing a closed-loop research paradigm,functional ensembles can be detected and tested in real time with temporal sequences.These functional ensembles,rather than brain regions or genetically labeled neural populations,serve as fundamental units of neural networks,offering valuable insights into the dissection of neural circuits.The closed-loop research paradigm also enables the capture of high-dimensional activities of internal brain dynamics and precise elucidation of physiological processes such as learning,decision-making,and sleep.

关键词： neural loop Transition

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MOF-derived porous graphitic carbon with optimized plateau capacity and rate capability for high performance lithium-ion capacitors

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International Journal of Minerals,Metallurgy and Materials 2024年第2期31卷 395-404页

作者： Ge Chu Chaohui Wang Zhewei Yang lin Qin Xin fan College of Materials Science&Engineering Guilin University of TechnologyGuilin 541004China Institute of Energy Innovation College of Materials Science and EngineeringTaiyuan University of TechnologyTaiyuan 030024China

The development of anode materials with high rate capability and long charge-discharge plateau is the key to improve per-formance of lithium-ion capacitors(LICs).Herein,the porous graphitic carbon(PGC-1300)derived from a new triply interpenetrated co-balt metal-organic framework(Co-MOF)was prepared through the facile and robust carbonization at 1300°C and washing by HCl solu-tion.The as-prepared PGC-1300 featured an optimized graphitization degree and porous framework,which not only contributes to high plateau capacity(105.0 mAh·g^(−1)below 0.2 V at 0.05 A·g^(−1)),but also supplies more convenient pathways for ions and increases the rate capability(128.5 mAh·g^(−1)at 3.2 A·g^(−1)).According to the kinetics analyses,it can be found that diffusion regulated surface induced capa-citive process and Li-ions intercalation process are coexisted for lithium-ion storage.Additionally,LIC PGC-1300//AC constructed with pre-lithiated PGC-1300 anode and activated carbon(AC)cathode exhibited an increased energy density of 102.8 Wh·kg^(−1),a power dens-ity of 6017.1 W·kg^(−1),together with the excellent cyclic stability(91.6%retention after 10000 cycles at 1.0 A·g^(−1)).

关键词： metal-organic framework porous graphitic carbon optimized plateau capacity kinetic analysis lithium-ion capacitor

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Machine Learning Analysis of Impact of Western US Fires on Central US Hailstorms

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Advances in Atmospheric Sciences 2024年第7期41卷 1450-1462页

作者： Xinming lin Jiwen fan Yuwei ZHANG ZJason HOU Pacific Northwest National Laboratory RichlandWA 99354USA Argonne National Laboratory LemontIL 60439USA

Fires,including wildfires,harm air quality and essential public services like transportation,communication,and utilities.These fires can also influence atmospheric conditions,including temperature and aerosols,potentially affecting severe convective storms.Here,we investigate the remote impacts of fires in the western United States(WUS)on the occurrence of large hail(size:≥2.54 cm)in the central US(CUS)over the 20-year period of 2001–20 using the machine learning(ML),Random Forest(RF),and Extreme Gradient Boosting(XGB)methods.The developed RF and XGB models demonstrate high accuracy(>90%)and F1 scores of up to 0.78 in predicting large hail occurrences when WUS fires and CUS hailstorms coincide,particularly in four states(Wyoming,South Dakota,Nebraska,and Kansas).The key contributing variables identified from both ML models include the meteorological variables in the fire region(temperature and moisture),the westerly wind over the plume transport path,and the fire features(i.e.,the maximum fire power and burned area).The results confirm a linkage between WUS fires and severe weather in the CUS,corroborating the findings of our previous modeling study conducted on case simulations with a detailed physics model.

关键词： wildfire severe convective storm hailstorm machine learning

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Optimization of Generator Based on Gaussian Process Regression Model with Conditional Likelihood Lower Bound Search

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CES Transactions on Electrical Machines and Systems 2024年第1期8卷 32-42页

作者： Xiao Liu Pingting lin fan Bu Shaoling Zhuang Shoudao Huang CES&IEEE the College of Electrical and Information Engineering Hunan UniversityChangsha 410082China CES

The noise that comes from finite element simulation often causes the model to fall into the local optimal solution and over fitting during optimization of generator.Thus,this paper proposes a Gaussian Process Regression(GPR)model based on Conditional Likelihood Lower Bound Search(CLLBS)to optimize the design of the generator,which can filter the noise in the data and search for global optimization by combining the Conditional Likelihood Lower Bound Search method.Taking the efficiency optimization of 15 kW Permanent Magnet Synchronous Motor as an example.Firstly,this method uses the elementary effect analysis to choose the sensitive variables,combining the evolutionary algorithm to design the super Latin cube sampling plan;Then the generator-converter system is simulated by establishing a co-simulation platform to obtain data.A Gaussian process regression model combing the method of the conditional likelihood lower bound search is established,which combined the chi-square test to optimize the accuracy of the model globally.Secondly,after the model reaches the accuracy,the Pareto frontier is obtained through the NSGA-II algorithm by considering the maximum output torque as a constraint.Last,the constrained optimization is transformed into an unconstrained optimizing problem by introducing maximum constrained improvement expectation(CEI)optimization method based on the re-interpolation model,which cross-validated the optimization results of the Gaussian process regression model.The above method increase the efficiency of generator by 0.76%and 0.5%respectively;And this method can be used for rapid modeling and multi-objective optimization of generator systems.

关键词： Generator optimization Gaussian Process Regression(GPR) Conditional Likelihood Lower Bound Search(CLLBS) Constraint improvement expectation(CEI) Finite element calculation

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Effects of shore-normal coastal structure on medium-to long-term embayed shoreline evolution

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Acta Oceanologica Sinica 2024年第2期43卷 58-66页

作者： Jitao Yu Yuanting Ding Pei Liu Renfu fan lin Zhang Hainan Academy of Ocean and Fisheries Sciences Haikou 571126China Yazhou Bay Innovation Institute Hainan Tropical Ocean UniversitySanya 572025China School of Geography and Environmental Sciences Hainan Normal UniversityHaikou 571158China

Based on high-tide shoreline data extracted from 87 Landsat satellite images from 1986 to 2019 as well as using the linear regression rate and performing a Mann-Kendall(M–K)trend test,this study analyzes the linear characteristics and nonlinear behavior of the medium-to long-term shoreline evolution of Jinghai Bay,eastern Guangdong Province.In particular,shoreline rotation caused by a shore-normal coastal structure is emphasized.The results show that the overall shoreline evolution over the past 30 years is characterized by erosion on the southwest beach,with an average erosion rate of 3.1 m/a,and significant accretion on the northeast beach,with an average accretion rate of 5.6 m/a.Results of the M–K trend test indicate that significant shoreline changes occurred in early 2006,which can be attributed to shore-normal engineering.Prior to that engineering construction,the shorelines are slightly eroded,where the average erosion rate is 0.7 m/a.However,after shore-normal engineering is performed,the shoreline is characterized by significant erosion(3.2 m/a)on the southwest beach and significant accretion(8.5 m/a)on the northeast beach,thus indicating that the shore-normal engineering at the updrift headland contributes to clockwise shoreline rotation.Further analysis shows that the clockwise shoreline rotation is promoted not only by longshore sediment transport processes from southwest to northeast,but also by cross-shore sediment transport processes.These findings are crucial for beach erosion risk management,coastal disaster zoning,regional sediment budget assessments,and further observations and predictions of beach morphodynamics.

关键词： shoreline rotation non-linear behavior longshore sediment transport cross-shore sediment transport embayed beach coastal structure

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Review of Fiber-Optic Localized Surface Plasmon Resonance Sensors:Geometries,Fabrication Technologies,and Bio-Applications

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Photonic Sensors 2024年第2期14卷 31-56页

作者： Mengdi LU Chen WANG Ruizhi fan Ming lin Jianye GUANG Wei PENG Affiliated Cancer Hospital Dalian University of TechnologyShenyang 110042China School of Physics Dalian University of TechnologyDalian 116024China

Localized surface plasmon resonance(LSPR)biosensors,which enable nanoscale confinement and manipulation of light,offer the enhanced sensitivity and electromagnetic energy localization.The integration of LSPR with the fiber-optic technology has led to the development of compact and versatile sensors for miniaturization and remote sensing.This comprehensive review explores various sensor configurations,fiber types,and geometric shapes,highlighting their benefits in terms of sensitivity,integration,and performance improvement.Fabrication techniques such as focused non-chemical bonding strategies and self-assembly of nanoparticles are discussed,providing control over nanostructure morphology and enhancing sensor performance.Bio-applications of fiber-optic LSPR(FOLSPR)sensors are detailed,specifically in biomolecular interactions and analysis of proteins,pathogens and cells,nucleic acids(DNA and RNA),and other small molecules(organic compounds and heavy metal ions).Surface modification and detection schemes are emphasized for their potential for label-free and real-time biosensing.The challenges and prospects of FOLSPR sensors are addressed,including the developments in sensitivity,fabrication techniques,and measurement reliability.Integration with emerging technologies such as nanomaterials is highlighted as a promising direction for future research.Overall,this review provides insights into the advancements and potential applications of FOLSPR sensors,paving the way for sensitive and versatile optical biosensing platforms in various fields.

关键词： Fiber-optic localized surface plasmon resonance biosensor nanoparticles geometric configuration fabrication technology

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Understanding Urban Vitality from the Economic and Human Activities Perspective:A Case Study of Chongqing,China

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Chinese Geographical Science 2024年第1期34卷 52-66页

作者： YANG Fiona fan lin Geng LEI Yubing WANG Ying YI Zheng School of Geography and Planning Sun Yat-sen UniversityGuangzhou510006China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai519100China Chongqing Planning and Design Institute Chongqing401147China

The literature on urban vitality tends to focus on the built environment.This paper argues that some important processes in shaping vitality may be overlooked without examining the intensity and diversity of economic and human activities.Using newly developed spatial big data and adopting the methods of multi-indicator measurement and spatial analysis methods,we analyzed the pattern of urban vitality in Chongqing,a provincial city in western China and,on this basis,evaluated the creation and maintenance of urban vitality from the economic and human activities perspective.Our findings indicate that the impacts of economic and human activities are positive and significant.Among the three intensity and diversity indicators,economic intensity and population density show an effect on urban vitality stronger than that of economic diversity.However,economic diversity has the strongest superposition or interactive effect,and is thus an important foundation dynamic.The positive effect of population density on urban vitality is largely a result of Chongqing’s jobs-housing balance.The case of Chongqing highlights the importance of topographic features,historical inheritance,large-scale migration,and cultural activities in shaping the distinctive vitality pattern of a city.This study contends that the creation and maintenance of urban vitality can not be fully explained without incorporating the impacts of economic and human activities.It contributes to a comprehensive measurement of urban vitality and enriches its connotations.

关键词： urban vitality economic diversity economic intensity population density Chongqing,China

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Deciphering the high-carbonization-temperature triggered enzymatic activity of wool-derived N,S-co-doped carbon nanosheets

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Chinese Chemical Letters 2024年第3期35卷 182-188页

作者： Jiachen Zhao Deshuai Yu Jianmin Chen Shihao lin Yonghua Tang Chaoyu fan Dongfang Zhou Youhui lin Department of Physics Research Institute for Biomimetics and Soft MatterFujian Provincial Key Laboratory for Soft Functional Materials ResearchXiamen UniversityXiamen 361005China School of Pharmacy and Medical Technology Putian UniversityPutian 351100China Key Laboratory of Mental Health of the Ministry of Education NMPA Key Laboratory for Research and Evaluation of Drug Metabolism&Guangdong Provincial Key Laboratory of New Drug ScreeningSchool of Pharmaceutical SciencesSouthern Medical UniversityGuangzhou 510515China Key Laboratory of Pharmaceutical Analysis and Laboratory Medicine(Putian University) Fujian Province UniversityPutian 351100China

It is well-established that high carbonization temperature will trigger the enzyme-like activity of carbon-based materials.However,the catalytic mechanism is still ambiguous,which hinders the further rational design of nanomaterials as enzyme mimics.Hereby,N,S-rich carbonized wool nanosheets(CWs)were synthesized at different pyrolysis temperatures.As expected,only CWs treated with high-temperature possess intrinsic oxidase-and peroxidase-like activities.Meanwhile,density functional theory(DFT)calculations demonstrate that graphitic nitrogen and the co-existence of nitrogen and sulfur in the carbon matrix serve as the active sites for the enzyme-like process.More importantly,combining theoretical calculations and experimental observations,the high-temperature triggered catalytic mechanism can be ascribed to the fact that an appropriate high-temperature maximizes the graphitization degree to a certain extent,at which most of the catalytic active sites are well retained rather than evaporating.Moreover,coupling with excellent photothermal conversion efficiency and catalytic performance,CWs can be applied to photothermal-catalytic cancer therapy under near-infrared region(NIR)light irradiation.We believe this work will contribute to understanding the catalytic mechanism of carbon-based nanozymes and promote the development of new biomedical and pharmaceutical applications.

关键词： Carbon-based nanozyme Catalytic mechanism Density functional theory High-temperature carbonization

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