Rheumatoid arthritis(RA)is a systemic autoimmune condition that leads to chronic arthritis,disability,and reduced lifespan.Current therapies show limited effectiveness and often cause severe side effects,with up to 50...Rheumatoid arthritis(RA)is a systemic autoimmune condition that leads to chronic arthritis,disability,and reduced lifespan.Current therapies show limited effectiveness and often cause severe side effects,with up to 50%of patients discontinuing disease-modifying antirheumatic drugs(DMARDs)due to unsatisfactory outcomes.Natural bioactive compounds(NBCs),such as glycosides,alkaloids,terpenoids,flavonoids,polyphenols,and coumarins,have gained attention for their immunomodulatory and antiinflammatory properties.However,challenges like poor solubility,high dosage requirements,short action duration,and low tissue specificity hinder their clinical use.Nanoparticle(NP)-based delivery systems,including lipid NPs(LNPs),polymer carriers,and inorganic nanocarriers,have been designed to address these challenges through passive,active,and stimuli-responsive strategies.NBC-loaded NPs target immune dysfunction,synovial hyperplasia,bone destruction,angiogenesis,inflammation,and oxidative stress(OS)in RA.This article highlights recent advancements in NBCs for RA treatment,nanoformulation design,and targeted mechanisms,while addressing challenges and future directions in this field.The integration of cutting-edge nanotechnology has demonstrated significant potential to overcome traditional barriers such as low bioavailability and off-target effects through intelligent NPs design.Future research should enhance artificial intelligence(AI)-driven modeling to predict drugnanocarrier interactions,develop biomarker frameworks for precision nanomedicine,and optimize RA management.展开更多
To integrate driver experience and heterogeneous vehicle platform characteristics in a motion-planning algorithm,based on the driver-behavior-based transferable motion primitives(MPs), a general motion-planning framew...To integrate driver experience and heterogeneous vehicle platform characteristics in a motion-planning algorithm,based on the driver-behavior-based transferable motion primitives(MPs), a general motion-planning framework for offline generation and online selection of MPs is proposed. Optimal control theory is applied to solve the boundary value problems in the process of generating MPs, where the driver behaviors and the vehicle motion characteristics are integrated into the optimization in the form of constraints. Moreover, a layered, unequal-weighted MP selection framework is proposed that utilizes a combination of environmental constraints, nonholonomic vehicle constraints,trajectory smoothness, and collision risk as the single-step extension evaluation index. The library of MPs generated offline demonstrates that the proposed generation method realizes the effective expansion of MP types and achieves diverse generation of MPs with various velocity attributes and platform types. We also present how the MP selection algorithm utilizes a unique MP library to achieve online extension of MP sequences. The results show that the proposed motion-planning framework can not only improve the efficiency and rationality of the algorithm based on driving experience but can also transfer between heterogeneous vehicle platforms and highlight the unique motion characteristics of the platform.展开更多
As the outfield load spectrum is so complicated that it cannot be used directly for test study in laboratory.This paper presents a method to determine load spectrum for high and low cycle combined fatigue of turbine m...As the outfield load spectrum is so complicated that it cannot be used directly for test study in laboratory.This paper presents a method to determine load spectrum for high and low cycle combined fatigue of turbine mortise at elevated temperature through experimental and numerical method.First of all,the low cycle load spectrum with duration time is determined through cumulative damage rule.The rain flow counting method is applied to obtain main cycles and sub cycles,and then the stress cycle is converted into pulsation cycle(stress ratio=0)based on the S-N curve and the Goodman curve;Secondly,three groups of different amplitudes tests are established to determine the high cycle amplitude.Finally,another three groups of the high-low combined cycle fatigue(HLCCF)tests for turbine mortise of a certain type engine are carried out.The results show that the macro and micro failure modes are identical with outfield's,which verifies the accuracy of the conversion method.展开更多
The cell membrane is a vital barrier that protects the cell from external damage and is involved in many biochemical processes.Thus,it is of great significance to label the cell membrane to explore its function.Howeve...The cell membrane is a vital barrier that protects the cell from external damage and is involved in many biochemical processes.Thus,it is of great significance to label the cell membrane to explore its function.However,due to its complex and dynamic nature,precise and firm cell membrane labeling simultaneously is still a challenge.Herein,we report the fabrication of a peptide-conjugated aggregationinduced emission fluorogen(AIEgen),RTP,consisting of three main components:(1)An integrin-targeting peptide(RGD,R),which could bind specifically to integrinαvβ3 on cell membranes through ligand–receptor interaction.(2)An AIE-active tetraphenylethene derivative(T-MY,T)for fluorescent imaging.(3)Palmitic acid-modified peptide(Pal-RRRR,P),in which Pal isinserted into the lipid on the cellmembrane by hydrophobic interaction,and RRRR interacted with the negatively charged cell membrane components(proteins and lipids)through electrostatic forces.RTP could precisely label tumor cells with high integrinαvβ3 expression andfirmly trace the cellmembrane for up to 4 h;it also has a strong resistance to photobleaching.Moreover,RTP achieved in vivo tumor-specific imaging via cell membrane labeling.Thereby,utilizing multiple weak interactions between the fluorescent probe and the cell membrane provided a new strategy for precise and firm imaging of the cell membrane simultaneously.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.:U21A20411 and 82074400)the Hunan ProvincialNatural Science Foundation,China(GrantNo.:2024JJ5303)+1 种基金the Scientific Research Project of Hunan University of Chinese Medicine,China(GrantNo.:Z2023XJYB05)the Postgraduate Scientific Research Innovation Project of Hunan,China(Grant No.:CX20220795).
文摘Rheumatoid arthritis(RA)is a systemic autoimmune condition that leads to chronic arthritis,disability,and reduced lifespan.Current therapies show limited effectiveness and often cause severe side effects,with up to 50%of patients discontinuing disease-modifying antirheumatic drugs(DMARDs)due to unsatisfactory outcomes.Natural bioactive compounds(NBCs),such as glycosides,alkaloids,terpenoids,flavonoids,polyphenols,and coumarins,have gained attention for their immunomodulatory and antiinflammatory properties.However,challenges like poor solubility,high dosage requirements,short action duration,and low tissue specificity hinder their clinical use.Nanoparticle(NP)-based delivery systems,including lipid NPs(LNPs),polymer carriers,and inorganic nanocarriers,have been designed to address these challenges through passive,active,and stimuli-responsive strategies.NBC-loaded NPs target immune dysfunction,synovial hyperplasia,bone destruction,angiogenesis,inflammation,and oxidative stress(OS)in RA.This article highlights recent advancements in NBCs for RA treatment,nanoformulation design,and targeted mechanisms,while addressing challenges and future directions in this field.The integration of cutting-edge nanotechnology has demonstrated significant potential to overcome traditional barriers such as low bioavailability and off-target effects through intelligent NPs design.Future research should enhance artificial intelligence(AI)-driven modeling to predict drugnanocarrier interactions,develop biomarker frameworks for precision nanomedicine,and optimize RA management.
基金Supported by National Natural Science Foundation of China (Grant Nos. 91420203 and 61703041)。
文摘To integrate driver experience and heterogeneous vehicle platform characteristics in a motion-planning algorithm,based on the driver-behavior-based transferable motion primitives(MPs), a general motion-planning framework for offline generation and online selection of MPs is proposed. Optimal control theory is applied to solve the boundary value problems in the process of generating MPs, where the driver behaviors and the vehicle motion characteristics are integrated into the optimization in the form of constraints. Moreover, a layered, unequal-weighted MP selection framework is proposed that utilizes a combination of environmental constraints, nonholonomic vehicle constraints,trajectory smoothness, and collision risk as the single-step extension evaluation index. The library of MPs generated offline demonstrates that the proposed generation method realizes the effective expansion of MP types and achieves diverse generation of MPs with various velocity attributes and platform types. We also present how the MP selection algorithm utilizes a unique MP library to achieve online extension of MP sequences. The results show that the proposed motion-planning framework can not only improve the efficiency and rationality of the algorithm based on driving experience but can also transfer between heterogeneous vehicle platforms and highlight the unique motion characteristics of the platform.
基金This work is supported by National Natural Science Foundation of China(51305012)Doctoral Fund of Ministry of Education of China(20111102120011)National Natural Science Foundation of China(51375031).The writers are grateful。
文摘As the outfield load spectrum is so complicated that it cannot be used directly for test study in laboratory.This paper presents a method to determine load spectrum for high and low cycle combined fatigue of turbine mortise at elevated temperature through experimental and numerical method.First of all,the low cycle load spectrum with duration time is determined through cumulative damage rule.The rain flow counting method is applied to obtain main cycles and sub cycles,and then the stress cycle is converted into pulsation cycle(stress ratio=0)based on the S-N curve and the Goodman curve;Secondly,three groups of different amplitudes tests are established to determine the high cycle amplitude.Finally,another three groups of the high-low combined cycle fatigue(HLCCF)tests for turbine mortise of a certain type engine are carried out.The results show that the macro and micro failure modes are identical with outfield's,which verifies the accuracy of the conversion method.
基金support by the National Key R&D Program of China(no.2020YFA0211200)the National Natural Science Foundation of China(nos.22090050,21974128,21874121,and 52003257)the Hubei Provincial Natural Science Foundation of China(nos.2019CFA043 and 2020CFA037).
文摘The cell membrane is a vital barrier that protects the cell from external damage and is involved in many biochemical processes.Thus,it is of great significance to label the cell membrane to explore its function.However,due to its complex and dynamic nature,precise and firm cell membrane labeling simultaneously is still a challenge.Herein,we report the fabrication of a peptide-conjugated aggregationinduced emission fluorogen(AIEgen),RTP,consisting of three main components:(1)An integrin-targeting peptide(RGD,R),which could bind specifically to integrinαvβ3 on cell membranes through ligand–receptor interaction.(2)An AIE-active tetraphenylethene derivative(T-MY,T)for fluorescent imaging.(3)Palmitic acid-modified peptide(Pal-RRRR,P),in which Pal isinserted into the lipid on the cellmembrane by hydrophobic interaction,and RRRR interacted with the negatively charged cell membrane components(proteins and lipids)through electrostatic forces.RTP could precisely label tumor cells with high integrinαvβ3 expression andfirmly trace the cellmembrane for up to 4 h;it also has a strong resistance to photobleaching.Moreover,RTP achieved in vivo tumor-specific imaging via cell membrane labeling.Thereby,utilizing multiple weak interactions between the fluorescent probe and the cell membrane provided a new strategy for precise and firm imaging of the cell membrane simultaneously.
