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Chinese Journal of Natural Medicines 2024年第2期22卷 112-126页

作者： REN Boxue LI Yang DI Lei CHENG Ranran LIU Lijuan LI Hongmei LI Yi TANG Zhangrui YAN Yongming lu tao FU Rong CHENG Yongxian WU Zhaoqiu State Key Laboratory of Natural Medicines Department of PharmacologySchool of PharmacyChina Pharmaceutical UniversityNanjing 211198China Institute for Inheritance-Based Innovation of Chinese Medicine School of Pharmaceutical SciencesShenzhen University Health Science CenterShenzhen 518060China

The tumor suppressor protein p53 is central to cancer biology,with its pathway reactivation emerging as a promising therapeutic strategy in oncology.This study introduced LZ22,a novel compound that selectively inhibits the growth,migration,and metastasis of tumor cells expressing wild-type p53,demonstrating ineffectiveness in cells devoid of p53 or those expressing mutant p53.LZ22’s mechanism of action involves a high-affinity interaction with the histidine-96 pocket of the MDM2 protein.This interaction disrupted the MDM2-p53 binding,consequently stabilizing p53 by shielding it from proteasomal degradation.LZ22 impeded cell cycle progression and diminished cell proliferation by reinstating the p53-dependent suppression of the CDK2/Rb signaling pathway.Moreover,LZ22 alleviated the p53-dependent repression of Snail transcription factor expression and its consequent EMT,effectively reducing tumor cell migration and distal metastasis.Importantly,LZ22 administration in tumor-bearing mice did not manifest notable side effects.The findings position LZ22 as a structurally unique reactivator of p53,offering therapeutic promise for the management of human cancers with wild-type TP53.

关键词： LZ22 Wild-type p53 p53 Reactivator Snail-driven EMT Tumor growth and metastasis

Material flow analysis and global warming potential assessment of an industrial insect-based bioconversion plant using housefly larvae

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Journal of Environmental Sciences 2024年第5期139卷 483-495页

作者： tao lu Fan Lü Nanlin Liao Honghui Chai Hua Zhang Pinjing He Institute of Waste Treatment and Reclamation Tongji UniversityShanghai 200092China State Key Laboratory of Pollution Control and Source Reuse Tongji UniversityShanghai 200092China Zhejiang Qihe Ecological Technology Co. Ltd.Hangzhou 310052China

The significant increase in the demand for biomass waste treatment after garbage classification has led to housefly larvae treatment becoming an attractive treatment option.It can provide a source of protein while treating biomass waste,which means that nutrients can be returned to the natural food chain.However,the performance of this technology in terms of its environmental impacts is still unclear,particularly with regards to global warming potential(GWP).This study used a life cycle assessment(LCA)approach to assess a housefly larvae treatment plant with a treatment capacity of 50 tons of biomass waste per day.The LCA results showed that the 95% confidence intervals for the GWP in summer and winter were determined to be 24.46-32.81 kg CO_(2) equivalent(CO_(2)-eq)/ton biomass waste and5.37-10.08 kg CO_(2)-eq/ton biomass waste,respectively.The greater GWP value in summer is due to the longer ventilation time and higher ventilation intensity in summer,which consumes more power.The main GWP contributions are from(1)electricity needs(accounting for 78.6% of emissions in summer and 70.2%in winter)and(2)product substitution by mature housefly larvae and compost(both summer and winter accounting for 96.8% of carbon reduction).

关键词： Biomass waste Musca domestica Housefly larvae Life cycle assessment Global warming potential

A global perspective on microbial risk factors in effluents of wastewater treatment plants

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Journal of Environmental Sciences 2024年第4期138卷 227-235页

作者： Kejing Chen Jinsong Liang Yuhan Wang Yechen tao Yun lu Aijie Wang School of Civil and Environmental Engineering Harbin Institute of TechnologyShenzhen 518055China Shenzhen Guohuan Environmental Protection Technology Development Co. LTD.Shenzhen 518055China State Key Joint Laboratory of Environmental Simulation and Pollution Control State Environmental Protection Key Laboratory of Microorganism Application and Risk ControlSchool of EnvironmentTsinghua UniversityBeijing 100084China

Effective monitoring and management of microbial risk factors in wastewater treatment plants(WWTPs)effluents require a comprehensive investigation of these risks.A global survey on microbial risk factors in WWTP effluents could reveal important insights into their risk features.This study aims to explore the abundance and types of antibiotic resistance genes(ARGs),virulence factor genes(VFGs),the vector of ARG/VFG,and dominant pathogens in global WWTP effluents.We collected 113 metagenomes of WWTP effluents from the Sequence Read Archive of the National Center for Biotechnology Information and characterized the microbial risk factors.Our results showed that multidrug resistance was the dominant ARG type,while offensive virulence factors were the most abundant type of VFGs.The most dominant types of ARGs in the vector of plasmid and phage were both aminoglycoside resistance,which is concerning as aminoglycosides are often a last resort for treating multi-resistant infections.Acinetobacter baumannii was the most dominant pathogen,rather than Escherichia coli,and a weak negative correlation between Escherichia coli and two other dominant pathogens(Acinetobacter baumannii and Bacteroides uniformis)suggests that using Escherichia coli as a biological indicator for all pathogens in WWTP effluents may not be appropriate.The Getah virus was the most dominant virus found in global WWTP effluents.Our study presents a comprehensive global-scale investigation of microbial risk factors in WWTP effluents,providing valuable insights into the potential risks associated with WWTP effluents and contributing to the monitoring and control of these risks.

关键词： Wastewater treatment plant Microbial risk factor Effluent Pathogen Antibiotic resistance gene Virulence factor gene

The joint knowledge reasoning model based on knowledge representation learning for aviation assembly domain

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Science China(Technological Sciences) 2024年第1期67卷 143-156页

作者： LIU PeiFeng QIAN lu lu Hu XUE Lei ZHAO XingWei tao Bo State Key Laboratory of Digital Manufacturing Equipment and Technology Department of MechanicalHuazhong University of Science and TechnologyWuhan 430074China School of Transportation and Logistics Engineering Wuhan University of Technology(WHUT)Wuhan 430063China Shanghai Aircraft Manufacturing Co. Ltd.Shanghai 201324China

Knowledge graph technology is widely applied in the domain of general knowledge reasoning with an excellent performance.For fine-grained professional fields,professional knowledge graphs can provide more accurate information in practical industrial scenarios.Based on an aviation assembly domain-specific knowledge graph,the article constructs a joint knowledge reasoning model,which combines a named entity recognition model and a subgraph embedding learning model.When performing knowledge reasoning tasks,the two models vectorize entities,relationships and entity attributes in the same space,so as to share parameters and optimize learning efficiency.The knowledge reasoning model,which provides intelligent question answering services,is able to reduce the assembly error rate and improve the assembly efficiency.The system can accurately solve general knowledge reasoning problems in the assembly process in actual industrial scenarios of general assembly and component assembly under interference-free conditions.Finally,this paper compares the proposed knowledge reasoning model based on knowledge representation learning and the question-answering system based on large-scale pre-trained models.In the application scenario of system functional testing in general assembly,the joint model attains an accuracy rate of 95%,outperforming GPT with 78%accuracy and enhanced representation through knowledge integration with 71%accuracy.

关键词： intelligent manufacturing knowledge graph aviation assembly knowledge representation knowledge-based question an-swering

Immediate implantation of ultrafine fiber slow-release system based on cell electrospinning to induce osteogenesis of mesenchymal stem cells

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Regenerative Biomaterials 2024年第2期3卷 76-87页

作者： tao lu Long Yang Zhuoyang Li Yin Liu Shun'en Xu Chuan Ye Department of Orthopaedics The Affliated Hospital of Guizhou Medical UniversityGuiyang 550004China Department of Orthopaedics The First People's Hospital of GuiyangGuiyang 550004China Center for Tissue Engineering and Stem Cell Research Guizhou Medical UniversityGuiyang 550004China Department of Otolaryngology Head and Neck Surgery Xinqiao HospitalArmy Medical University(Third Military Medical University)Chongqing 400037China Department of Dental implant Stomatological Hospital of GuiyangGuiyang 550000China

This study presents the development and evaluation of a poly(3-hydroxybutyrate-co-4-hydroxybutyrate)(P34HB)ultrafine fiber slow-release system for in vivo osteogenic induction of human umbilical cord mesenchymal stem cells(HUCMSCs).Utilizing dual-nozzle and cell electrospinning techniques,the system encapsulates L-ascorbic acid-2-phosphate magnesium(AsP),βB-glycerophosphate sodium and dexamethasone(DEX)within the'fbers,ensuring sustained osteogenic differentiation.The scaffold's morphology,characterization,hydrophilicity,mechanical properties and cellular behavior were examined.Immediate subcutaneous implantation in rabbits was con-ducted to observe its ectopic osteogenic induction effect.Successfully fabricated P34HB ultrafine fiber slow-release sys-tem.Charact ization med.theuniform distribution of HUCMSCs and inducing components within the scaffold,with no chemical reactions affecting the active components.In vitro tests showcased a prolonged release of DEX and ASP,while biocompatibility assays highlighted the scaffold's suitability for cellular growth.Alizarin Red,type I collagen,and osteopontin(OPN)staining verifed the scaffold's potent osteogenic induction effect on HUCMsCs.Notably,immediate implantation into New Zealand White rabbits led to significant new bone formation within 8 weeks.These findings underscore the system's potential for immediate in vivo implantation without prior in vitro induction,marking a promising advancement in bone tissue engineering.

关键词： bone tissue engineering cell electrospinning in vivo induction immediate implantation biomaterials

A projected Newton algorithm based on chemically allowed interval for chemical equilibrium computations

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Frontiers of Chemical Science and Engineering 2024年第3期18卷 25-37页

作者： Hongbin lu Shaohui tao Xiaoyan Sun Li Xia Shuguang Xiang Institute of Process Systems Engineering College of Chemical EngineeringQingdao University of Science and TechnologyQingdao266042China

The chemical equilibrium equations utilized in reactive transport modeling are complex and nonlinear,and are typically solved using the Newton-Raphson method.Although this algorithm is known for its quadratic convergence near the solution,it is less effective far from the solution,especially for ill-conditioned problems.In such cases,the algorithm may fail to converge or require excessive iterations.To address these limitations,a projected Newton method is introduced to incorporate the concept of projection.This method constrains the Newton step by utilizing a chemically allowed interval that generates feasible descending iterations.Moreover,we utilize the positive continuous fraction method as a preconditioning technique,providing reliable initial values for solving the algorithms.The numerical results are compared with those derived using the regular Newton-Raphson method,the Newton-Raphson method based on chemically allowed interval updating rules,and the bounded variable least squares method in six different test cases.The numerical results highlight the robustness and efficacy of the proposed algorithm.

关键词： chemical equilibrium reactive transport modeling numerical methods projected Newton method

Predictive value of machine learning models for lymph node metastasis in gastric cancer: A two-center study

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World Journal of Gastrointestinal Surgery 2024年第1期16卷 85-94页

作者： Tong lu Miao lu Dong Wu Yuan-Yuan Ding Hao-Nan Liu tao-tao Li Da-Qing Song Department of Emergency Medicine Jining No.1 People’s HospitalJining 272000Shandong ProvinceChina Wuxi Mental Health Center Wuxi 214000Jiangsu ProvinceChina Department of Gastroenterology Jining No.1 People’s HospitalJining 272000Shandong ProvinceChina Department of Oncology The Affiliated Hospital of Xuzhou Medical UniversityXuzhou 221002Jiangsu ProvinceChina

BACKGROUND Gastric cancer is one of the most common malignant tumors in the digestive system,ranking sixth in incidence and fourth in mortality worldwide.Since 42.5%of metastatic lymph nodes in gastric cancer belong to nodule type and peripheral type,the application of imaging diagnosis is restricted.AIM To establish models for predicting the risk of lymph node metastasis in gastric cancer patients using machine learning(ML)algorithms and to evaluate their pre-dictive performance in clinical practice.METHODS Data of a total of 369 patients who underwent radical gastrectomy at the Depart-ment of General Surgery of Affiliated Hospital of Xuzhou Medical University(Xuzhou,China)from March 2016 to November 2019 were collected and retro-spectively analyzed as the training group.In addition,data of 123 patients who underwent radical gastrectomy at the Department of General Surgery of Jining First People’s Hospital(Jining,China)were collected and analyzed as the verifi-cation group.Seven ML models,including decision tree,random forest,support vector machine(SVM),gradient boosting machine,naive Bayes,neural network,and logistic regression,were developed to evaluate the occurrence of lymph node metastasis in patients with gastric cancer.The ML models were established fo-llowing ten cross-validation iterations using the training dataset,and subsequently,each model was assessed using the test dataset.The models’performance was evaluated by comparing the area under the receiver operating characteristic curve of each model.RESULTS Among the seven ML models,except for SVM,the other ones exhibited higher accuracy and reliability,and the influences of various risk factors on the models are intuitive.CONCluSION The ML models developed exhibit strong predictive capabilities for lymph node metastasis in gastric cancer,which can aid in personalized clinical diagnosis and treatment.

关键词： Machine learning Prediction model Gastric cancer Lymph node metastasis

A Blockchain and CP-ABE Based Access Control Scheme with Fine-Grained Revocation of Attributes in Cloud Health

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Computers, Materials & Continua 2024年第2期78卷 2787-2811页

作者： Ye lu tao Feng Chunyan Liu Wenbo Zhang School of Computer&Communication Lanzhou University of TechnologyLanzhou730000China School of Economics&Management Lanzhou University of TechnologyLanzhou730000China School of Computer Science Baoji University of Arts and ScienceBaoji721000China

The Access control scheme is an effective method to protect user data privacy.The access control scheme based on blockchain and ciphertext policy attribute encryption(CP–ABE)can solve the problems of single—point of failure and lack of trust in the centralized system.However,it also brings new problems to the health information in the cloud storage environment,such as attribute leakage,low consensus efficiency,complex permission updates,and so on.This paper proposes an access control scheme with fine-grained attribute revocation,keyword search,and traceability of the attribute private key distribution process.Blockchain technology tracks the authorization of attribute private keys.The credit scoring method improves the Raft protocol in consensus efficiency.Besides,the interplanetary file system(IPFS)addresses the capacity deficit of blockchain.Under the premise of hiding policy,the research proposes a fine-grained access control method based on users,user attributes,and file structure.It optimizes the data-sharing mode.At the same time,Proxy Re-Encryption(PRE)technology is used to update the access rights.The proposed scheme proved to be secure.Comparative analysis and experimental results show that the proposed scheme has higher efficiency and more functions.It can meet the needs of medical institutions.

关键词： Blockchain access-control CP-ABE cloud health

Selective control of secondary alcohols upgrading using Ir-catalyzed cross-coupling strategy

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Science China Chemistry 2024年第3期67卷 914-921页

作者： Siqi Yang Zeye lu Jiale Ji Qingshu Zheng tao Tu Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials Department of ChemistryFudan UniversityShanghai 200438China Frontiers Science Center for Transformative Molecules School of Chemistry and Chemical EngineeringShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Organometallic Chemistry Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghai 200032China

The selective coupling of alcohols is a fascinating yet challenging approach for upgrading alcohols. Herein, we accomplished the controlled production of β-disubstituted ketones or upgraded secondary alcohols via the Ir-catalyzed cross-coupling of secondary alcohols in excellent yields with broad substrate scopes. This selective control was achieved by using an in-situ generated monoNHC-Ir or a tris-NHC-Ir complex as the catalysts, respectively. Mechanistic studies revealed that the delicate balance between dehydrogenation and hydrogenation abilities of these bifunctional catalysts is crucial for achieving different selectivity. The tris-NHC-Ir complex effectively facilitated dehydrogenation of alcohols and hydrogenation of intermediates, leading to the desired upgraded secondary alcohols. Conversely, the high dehydrogenation ability of the mono-NHC-Ir complex promoted the conversion of formed secondary alcohols back to ketones.

关键词： cross-coupling hydrogen-borrowing NHC-Ir complexes selectivity control upgrading of alcohols

Exploring the impacts of major events on the systemic risk of the international energy market

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Petroleum Science 2024年第2期21卷 1444-1457页

作者： Ming-tao Zhao Su-Wan lu Lian-Biao Cui School of Statistics and Applied Mathematics Anhui University of Finance and EconomicsBengbu233030AnhuiChina Anhui Province Key Laboratory of Philosophy and Social Science of Low-Carbon Development and Carbon Finance Anhui University of Finance and EconomicsBengbu233030AnhuiChina

This study examines the systemic risk caused by major events in the international energy market(IEM)and proposes a management strategy to mitigate it. Using the tail-event driven network(TENET)method, this study constructed a tail-risk spillover network(TRSN) of IEM and simulated the dynamic spillover tail-risk process through the cascading failure mechanism. The study found that renewable energy markets contributed more to systemic risk during the Paris Agreement and the COVID-19pandemic, while fossil energy markets played a larger role during the Russia-Ukraine conflict. This study identifies systemically important markets(SM) and critical tail-risk spillover paths as potential sources of systemic risk. The research confirms that cutting off the IEM risk spillover path can greatly reduce systemic risk and the influence of SM. This study offers insights into the management of systemic risk in IEM and provides policy recommendations to reduce the impact of shock events.

关键词： International energy market Tail-risk spillover Cascading failure mechanism Systemic risk management