Facilitated transport membranes for post-combustion carbon capture are one of the technologies to achieve efficient and large-scale capture.The central principle is to utilize the affinity of CO_(2) for the carrier to...Facilitated transport membranes for post-combustion carbon capture are one of the technologies to achieve efficient and large-scale capture.The central principle is to utilize the affinity of CO_(2) for the carrier to achieve efficient separation and to break the Robson upper bound.This paper reviews the progress of facilitated transport membranes research regarding polymer materials,principles,and problems faced at this stage.Firstly,we briefly introduce the transport mechanism of the facilitated transport membranes.Then the research progress of several major polymers used for facilitated transport membranes for CO_(2)/N_(2) separation was presented in the past five years.Additionally,we analyze the primary challenges of facilitated transport membranes,including the influence of water,the effect of temperature,the saturation effect of the carrier,and the process configuration.Finally,we also delve into the challenges and competitiveness of facilitated transport membranes.展开更多
With the deepening of epigenetic research,studies have shown that N6-methyladenosine(m^(6)A)is closely related to the development of rheumatoid arthritis(RA),but the mechanism is still unclear.In the study,we collecte...With the deepening of epigenetic research,studies have shown that N6-methyladenosine(m^(6)A)is closely related to the development of rheumatoid arthritis(RA),but the mechanism is still unclear.In the study,we collected synovial tissues from normal controls and patients with osteoarthritis(OA)or RA.The levels of m^(6)A and inflammation were analyzed by immunofluorescence staining and western blotting.The roles of IGF2BP3 in cell proliferation and inflammatory activation were explored using transfection and RNA immunoprecipitation assays.IGF2BP3^(−/−)mice were generated and used to establish an arthritis mouse model by transferring serum from adult arthritis K/BxN mice.We found m^(6)A levels were markedly increased in RA patients and mouse models,and the expression of IGF2BP3 was upregulated in individuals with RA and related to the levels of inflammatory markers.IGF2BP3 played an important part in RA-fibroblast-like synoviocytes(FLS)by promoting cell proliferation,migration,invasion,inflammatory cytokine release and inhibiting autophagy.In addition,IGF2BP3 inhibited autophagy to reduce ROS production,thereby decreasing the inflammatory activation of macrophages.More importantly,RASGRF1-mediated mTORC1 activation played a crucial role in the ability of IGF2BP3 to promote cell proliferation and inflammatory activation.In an arthritis model of IGF2BP3^(−/−)mice,IGF2BP3 knockout inhibited RA-FLS proliferation and inflammatory infiltration,and further ameliorated RA joint injury.Our study revealed an important role for IGF2BP3 in RA progression.The targeted inhibition of IGF2BP3 reduced cell proliferation and inflammatory activation and limited RA development,providing a potential strategy for RA therapy.展开更多
Rheumatoid arthritis(RA)is a progressive autoimmune disease characterized by bone destruction that is primarily caused by the overactivation of osteoclasts(OCs),which are critical therapeutic targets.Triptolide(TP)has...Rheumatoid arthritis(RA)is a progressive autoimmune disease characterized by bone destruction that is primarily caused by the overactivation of osteoclasts(OCs),which are critical therapeutic targets.Triptolide(TP)has strong anti-RA effects but is limited by its narrow therapeutic window and associated toxicity,necessitating combination therapy to increase its efficacy and reduce side effects.Medicarpin(Med),a flavonoid with anti-inflammatory and anti-bone destruction properties,has shown potential in reducing osteoclastogenesis.However,the mechanisms underlying the synergistic effects of TP and Med on RA treatment remain unclear.We addressed this issue by evaluating the effects of TP,Med,and their combination on a collagen-induced arthritis(CIA)rat model,with a focus on bone erosion as the primary research endpoint.We subsequently performed experimental validation in an in vitro OC dif-ferentiation model to assess the impacts of these treatments on OC formation and function.Based on polymerase chain reaction(PCR)microarray data from RA patients,further investigations focused on N^(6)-methyladenosine(m^(6)A)methylation and its regulatory factors,methyltransferase-like 3(METTL3)and YT521-B homology domain family protein 1(YTHDF1),which have been identified as potential tar-gets of TP and Med.Key findings revealed that the TP and Med combination significantly alleviated bone destruction and inhibited OC differentiation,exerting stronger effects at lower doses than either drug alone.Mechanistically,TP and Med synergistically modulated METTL3 and YTHDF1 to suppress osteo-clastogenesis through distinct m6 A methylation pathways,contributing to the mitigation of RA-associated bone destruction.Overall,our data highlight the potential of the m^(6)A modification as a ther-apeutic mechanism for the combined use of TP and Med for RA treatment,providing a theoretical basis for the clinical application of herbal active ingredient combinations.展开更多
Background Reproductive efficiency in goats is closely linked to the healthy development of follicles,with the proliferation of ovarian granulosa cells(GCs)playing a crucial role in this process.Sirtuin 3(SIRT3),an en...Background Reproductive efficiency in goats is closely linked to the healthy development of follicles,with the proliferation of ovarian granulosa cells(GCs)playing a crucial role in this process.Sirtuin 3(SIRT3),an enzyme that catalyzes post-translational modifications(PTMs)of proteins,is known to regulate a variety of mitochondrial metabolic pathways,thereby affecting cell fate.However,the specific effect of SIRT3 on the follicular development process remains unclear.Therefore,this study aimed to investigate the regulatory role of SIRT3 in the mitochondrial function and proliferation of goat GCs,as well as the underlying mechanisms involved.Results In this study,GCs from small follicles in goat ovaries presented increased proliferative potential and elevated SIRT3 expression levels compared with those from large follicles.In vitro,SIRT3 overexpression enhanced mitochondrial function,promoted proliferation and inhibited apoptosis in GCs.Correspondingly,the inhibition of SIRT3 led to the opposite effects.Notably,SIRT3 interacted with carnitine palmitoyl transferase 2(CPT2)and stabilized the CPT2 protein by mediating delactylation,which prolonged the half-life of CPT2 and prevented its degradation.Further investigation revealed that CPT2 overexpression enhanced fatty acidβ-oxidation and mitochondrial function in GCs.Additionally,CPT2 promoted the proliferation of GCs by increasing the protein levels ofβ-catenin and its downstream target,cyclin D1(CCND1).However,this effect was reversed by 3-TYP(a SIRT3 inhibitor).Conclusions SIRT3 stabilizes CPT2 protein expression through delactylation,thereby enhancing mitochondrial function and the proliferative capacity of GCs in goats.This study provides novel insights into the molecular mechanisms and regulatory pathways involved in mammalian follicular development.展开更多
Osteosarcoma is the most common primary bone tumor with high malignancy.It is particularly necessary to achieve rapid and accurate diagnosis in its intraoperative examination and early diagnosis.Accordingly,the multim...Osteosarcoma is the most common primary bone tumor with high malignancy.It is particularly necessary to achieve rapid and accurate diagnosis in its intraoperative examination and early diagnosis.Accordingly,the multimodal microscopic imaging diagnosis system constructed by bright field,spontaneous fluorescence and polarized light microscopic imaging was used to study the pathological mechanism of osteosarcoma from the tissue microenvironment level and achieve rapid and accurate diagnosis.First,the multimodal microscopic images of normal and osteosarcoma tissue slices were collected to characterize the overall morphology of the tissue microenvironment of the samples,the arrangement structure of collagen fibers and the content and distribution of endogenous fluorescent substances.Second,based on the correlation and complementarity of the feature information contained in the three single-mode images,combined with convolutional neural network(CNN)and image fusion methods,a multimodal intelligent diagnosis model was constructed to effectively improve the information utilization and diagnosis accuracy.The accuracy and true positivity of the multimodal diagnostic model were significantly improved to 0.8495 and 0.9412,respectively,compared to those of the single-modal models.Besides,the difference of tissue microenvironments before and after cancerization can be used as a basis for cancer diagnosis,and the information extraction and intelligent diagnosis of osteosarcoma tissue can be achieved by using multimodal microscopic imaging technology combined with deep learning,which significantly promoted the application of tissue microenvironment in pathological examination.This diagnostic system relies on its advantages of simple operation,high efficiency and accuracy and high cost-effectiveness,and has enormous clinical application potential and research significance.展开更多
Cropland nitrate leaching is the major nitrogen(N) loss pathway, and it contributes significantly to water pollution. However, cropland nitrate leaching estimates show great uncertainty due to variations in input data...Cropland nitrate leaching is the major nitrogen(N) loss pathway, and it contributes significantly to water pollution. However, cropland nitrate leaching estimates show great uncertainty due to variations in input datasets and estimation methods. Here, we presented a re-evaluation of Chinese cropland nitrate leaching, and identified and quantified the sources of uncertainty by integrating three cropland area datasets, three N input datasets, and three estimation methods. The results revealed that nitrate leaching from Chinese cropland averaged 6.7±0.6 Tg N yr^(-1)in 2010, ranging from 2.9 to 15.8 Tg N yr^(-1)across 27 different estimates. The primary contributor to the uncertainty was the estimation method, accounting for 45.1%, followed by the interaction of N input dataset and estimation method at 24.4%. The results of this study emphasize the need for adopting a robust estimation method and improving the compatibility between the estimation method and N input dataset to effectively reduce uncertainty. This analysis provides valuable insights for accurately estimating cropland nitrate leaching and contributes to ongoing efforts that address water pollution concerns.展开更多
Platinum-based(Pt)catalysts are notoriously susceptible to deactivation in industrial chemical processes due to carbon monoxide(CO)poisoning.Overcoming this poisoning deactivation of Pt-based catalysts while enhancing...Platinum-based(Pt)catalysts are notoriously susceptible to deactivation in industrial chemical processes due to carbon monoxide(CO)poisoning.Overcoming this poisoning deactivation of Pt-based catalysts while enhancing their catalytic activity,selectivity,and durability remains a major challenge.Herein,we propose a strategy to enhance the CO tolerance of Pt clusters(Pt_n)by introducing neighboring functionalized vip single atoms(such as Fe,Co,Ni,Cu,Sb,and Bi).Among them,antimony(Sb)single atoms(SAs)exhibit significant performance enhancement,achieving 99%CO selectivity and 33.6%CO_(2)conversion at 450℃,Experimental results and density functional theory(DFT)calculations indicate the optimization arises from the electronic interaction between neighboring functionalized Sb SAs and Pt clusters,leading to optimal 5d electron redistribution in Pt clusters compared to other functionalized vip single atoms.The redistribution of 5d electrons weaken both theσdonation andπbackdonation interactions,resulting in a weakened bond strength with CO and enhancing catalyst activity and selectivity.In situ environmental transmission electron microscopy(ETEM)further demonstrates the exception thermal stability of the catalyst,even under H_(2)at 700℃.Notably,the functionalized Sb SAs also improve CO tolerance in various heterogenous catalysts,including Co/CeO_(2),Ni/CeO_(2),Pt/Al_(2)O_(3),and Pt/CeO_(2)-C.This finding provides an effective approach to overcome the primary challenge of CO poisoning in Pt-based catalysts,making their broader applications in various industrial catalysts.展开更多
Bimodal pressure sensors capable of simultaneously detecting static and dynamic forces are essential to medical detection and bio-robotics.However,conventional pressure sensors typically integrate multiple operating m...Bimodal pressure sensors capable of simultaneously detecting static and dynamic forces are essential to medical detection and bio-robotics.However,conventional pressure sensors typically integrate multiple operating mechanisms to achieve bimodal detection,leading to complex device architectures and challenges in signal decoupling.In this work,we address these limitations by leveraging the unique piezotronic effect of Y-ion-doped ZnO to develop a bimodal piezotronic sensor(BPS)with a simplified structure and enhanced sensitivity.Through a combination of finite element simulations and experimental validation,we demonstrate that the BPS can effectively monitor both dynamic and static forces,achieving an on/off ratio of 1029,a gauge factor of 23,439 and a static force response duration of up to 600 s,significantly outperforming the performance of conventional piezoelectric sensors.As a proof-of-concept,the BPS demonstrates the continuous monitoring of Achilles tendon behavior under mixed dynamic and static loading conditions.Aided by deep learning algorithms,the system achieves 96%accuracy in identifying Achilles tendon movement patterns,thus enabling warnings for dangerous movements.This work provides a viable strategy for bimodal force monitoring,highlighting its potential in wearable electronics.展开更多
The swinging-loading process is essential for automatic artillery loading systems.This study focuses on the problems of reliability analysis that affect swinging-loading positioning accuracy.A dynamic model for a mult...The swinging-loading process is essential for automatic artillery loading systems.This study focuses on the problems of reliability analysis that affect swinging-loading positioning accuracy.A dynamic model for a multi degree-of-freedom swinging-loading-integrated rigid-flexible coupling system is established.This model is based on the identification of key parameters and platform experiments.Based on the spatial geometric relationship between the breech and loader during modular charge transfer and the possible maximum interference depth of the modular charge,a new failure criterion for estimating the reliability of swinging-loading positioning accuracy is proposed.Considering the uncertainties in the operation of the pendulum loader,the direct probability integration method is introduced to analyze the reliability of the swinging-loading positioning accuracy under three different charge numbers.The results indicate that under two and four charges,the swinging-loading process shows outstanding reliability.However,an unstable stage appears when the swinging motion occurred under six charges,with a maximum positioning failure probability of 0.0712.A comparison between the results obtained under the conventional and proposed criteria further reveals the effectiveness and necessity of the proposed criterion.展开更多
The emerging interfacial polarization strategy exhibits applicative potential in piezoelectric enhancement.However,there is an ongoing effort to address the inherent limitations arising from charge bridging phenomena ...The emerging interfacial polarization strategy exhibits applicative potential in piezoelectric enhancement.However,there is an ongoing effort to address the inherent limitations arising from charge bridging phenomena and stochastic interface disorder that plague the improvement of piezoelectric performance.Here,we report a dual structure reinforced MXene/PVDF-TrFE piezoelectric composite,whose piezoelectricity is enhanced under the coupling effect of interfacial polarization and structural design.Synergistically,molecular dynamics simulations,density functional theory calculations and experimental validation revealed the details of interfacial interactions,which promotes the net spontaneous polarization of PVDF-TrFE from the 0.56 to 31.41 Debye.The oriented MXene distribution and porous structure not only tripled the piezoelectric response but also achieved an eightfold increase in sensitivity within the low-pressure region,along with demonstrating cyclic stability exceeding 20,000 cycles.The properties reinforcement originating from dual structure is elucidated through the finite element simulation and experimental validation.Attributed to the excellent piezoelectric response and deep learning algorithm,the sensor can effectively recognize the signals of artery pulse and finger flexion.Finally,a 3×3 sensor array is fabricated to monitor the pressure distribution wirelessly.This study provides an innovative methodology for reinforcing interfacial polarized piezoelectric materials and insight into structural designs.展开更多
The embodied artificial intelligence(EAI)is driving a significant transformation in robotics,enhancing their autonomy,efficiency and evolution ability.In this rapidly evolving technological landscape,robots need numer...The embodied artificial intelligence(EAI)is driving a significant transformation in robotics,enhancing their autonomy,efficiency and evolution ability.In this rapidly evolving technological landscape,robots need numerous sensors to realize high levels of perception,precision,safety,adaptability,and intelligence.Triboelectric and piezoelectric sensors address these needs by providing high sensitivity,flexibility,and the capability of self-powered sensing,leveraging the revolutionary nature of nanogenerators to convert mechanical energy into electrical energy on basis of Maxwell’s displacement current.These sensors surpass externally powered passive sensors by offering continuous operation,reduced maintenance,and the capability to function in remote or harsh environments.The integration of EAI with advanced nanogenerators sensors could position robotics to perform autonomously,efficiently,and safely,paving the way for innovative applications in various domains such as industrial automation,environmental monitoring,healthcare,and smart homes.In this paper,the fundamental theories,design,manufacturing,and applications of nanogenerators are comprehensively reviewed as afoundation of the advanced sensors for intelligent robotics in the new era,with three major application fields:sensing(including human–robot interaction,exteroceptive sensing and proprioceptive sensing),computing and actuating.Perspectives are addressed for nanogenerators systems in future development.展开更多
The integration of deep learning into smart grid operations addresses critical challenges in dynamic load forecasting and optimal dispatch amid increasing renewable energy penetration.This study proposes a hybrid LSTM...The integration of deep learning into smart grid operations addresses critical challenges in dynamic load forecasting and optimal dispatch amid increasing renewable energy penetration.This study proposes a hybrid LSTM-Transformer architecture for multi-scale temporal-spatial load prediction,achieving 28%RMSE reduction on real-world datasets(CAISO,PJM),coupled with a deep reinforcement learning framework for multi-objective dispatch optimization that lowers operational costs by 12.4%while ensuring stability constraints.The synergy between adaptive forecasting models and scenario-based stochastic optimization demonstrates superior performance in handling renewable intermittency and demand volatility,validated through grid-scale case studies.Methodological innovations in federated feature extraction and carbon-aware scheduling further enhance scalability for distributed energy systems.These advancements provide actionable insights for grid operators transitioning to low-carbon paradigms,emphasizing computational efficiency and interoperability with legacy infrastructure.展开更多
Correction to:Nano-Micro Lett.(2023)15:233 https://doi.org/10.1007/s40820-023-01201-7 Following publication of the original article[1],the authors reported that the first two lines of the introduction were accidentall...Correction to:Nano-Micro Lett.(2023)15:233 https://doi.org/10.1007/s40820-023-01201-7 Following publication of the original article[1],the authors reported that the first two lines of the introduction were accidentally placed in the right-hand column of the page in the PDF,which affects the readability.展开更多
3D printing technology is a new type of precision forming technology and the core technology of the third industrial revolution.The powder-based 3D printing technology of titanium and its alloys have received great at...3D printing technology is a new type of precision forming technology and the core technology of the third industrial revolution.The powder-based 3D printing technology of titanium and its alloys have received great attention in biomedical applications since its advantages of custom manufacturing,costsaving,time-saving,and resource-saving potential.In particular,the personalized customization of 3D printing can meet specific needs and achieve precise control of micro-organization and structural design.The purpose of this review is to present the most advanced multi-material 3D printing methods for titanium-based biomaterials.We first reviewed the bone tissue engineering,the application of titanium alloy as bone substitutes and the development of manufacturing technology,which emphasized the advantages of 3D printing technology over traditional manufacturing methods.What is more,the optimization design of the hierarchical structure was analyzed to achieve the best mechanical properties,and the biocompatibility and osseointegration ability of the porous titanium alloy after implantation in living bodies was analyzed.Finally,we emphasized the development of digital tools such as artificial intelligence,which provides new ideas for the rational selection of processing parameters.The 3D printing titanium-based alloys will meet the huge market demand in the biomedical field,but there are still many challenges,such as the trade-off between high strength and low modulus,optimization of process parameters and structural design.We believe that the combination of mechanical models,machine learning,and metallurgical knowledge may shape the future of metal printing.展开更多
With the development of artificial intelligence,stiffness sensors are extensively utilized in various fields,and their integration with robots for automated palpation has gained significant attention.This study presen...With the development of artificial intelligence,stiffness sensors are extensively utilized in various fields,and their integration with robots for automated palpation has gained significant attention.This study presents a broad range self-powered stiffness sensor based on the triboelectric nanogenerator(Stiff-TENG)for variable inclusions in soft objects detection.The Stiff-TENG employs a stacked structure comprising an indium tin oxide film,an elastic sponge,a fluorinated ethylene propylene film with a conductive ink electrode,and two acrylic pieces with a shielding layer.Through the decoupling method,the Stiff-TENG achieves stiffness detection of objects within 1.0 s.The output performance and characteristics of the TENG for different stiffness objects under 4 mm displacement are analyzed.The Stiff-TENG is successfully used to detect the heterogeneous stiffness structures,enabling effective recognition of variable inclusions in soft object,reaching a recognition accuracy of 99.7%.Furthermore,its adaptability makes it well-suited for the detection of pathological conditions within the human body,as pathological tissues often exhibit changes in the stiffness of internal organs.This research highlights the innovative applications of TENG and thereby showcases its immense potential in healthcare applications such as palpation which assesses pathological conditions based on organ stiffness.展开更多
The function-led design of porous hydrochar from mineral-rich biowaste for environmental applications inevitably suffers from carbon-ash recalcitrance.However,a method to alter the original carbon skeleton with ash re...The function-led design of porous hydrochar from mineral-rich biowaste for environmental applications inevitably suffers from carbon-ash recalcitrance.However,a method to alter the original carbon skeleton with ash remains elusive and hinders the availability of hydrochar.Herein,we propose a facile strategy for breaking the rigid structure of carbon-ash coupled hydrochar using phase-tunable molten carbonates.A case system was designed in which livestock manure and NaHCO3 were used to prepare the activated hydrochar,and NH3 served as the target contaminant.Due to the redox effect,we found that organic fractions significantly advanced the melting temperature of Na2CO3 below 800℃.The Na species steadily broke the carbon-ash interaction as the thermal intensity increased and transformed inorganic constituents to facilitate ash dissolution,rebuilding the hydrochar skeleton with abundant hierarchical channels and active defect edges.The surface polarity and mesopore distribution collectively governed the five cycles NH3 adsorption attenuation process.Manure hydrochar delivered favorable potential for application with a maximum overall adsorption capacity of 100.49 mg·g^(-1).Integrated spectroscopic characterization and theoretical computations revealed that incorporating NH3 on the carbon surface could transfer electrons to chemisorbed oxygen,which promoted the oxidation of pyridine-N during adsorption.This work offers deep insight into the structure function correlation of hydrochar and inspires a more rational design of engineered hydrochar from high-ash biowaste.展开更多
In urban Vehicular Ad hoc Networks(VANETs),high mobility of vehicular environment and frequently changed network topology call for a low delay end-to-end routing algorithm.In this paper,we propose a Multi-Agent Reinfo...In urban Vehicular Ad hoc Networks(VANETs),high mobility of vehicular environment and frequently changed network topology call for a low delay end-to-end routing algorithm.In this paper,we propose a Multi-Agent Reinforcement Learning(MARL)based decentralized routing scheme,where the inherent similarity between the routing problem in VANET and the MARL problem is exploited.The proposed routing scheme models the interaction between vehicles and the environment as a multi-agent problem in which each vehicle autonomously establishes the communication channel with a neighbor device regardless of the global information.Simulation performed in the 3GPP Manhattan mobility model demonstrates that our proposed decentralized routing algorithm achieves less than 45.8 ms average latency and high stability of 0.05%averaging failure rate with varying vehicle capacities.展开更多
As renewable energy resources increasingly penetrate the electric grid,the inertia capability of power systems has become a developmental bottleneck.Nevertheless,the importance of primary frequency response(PFR)when m...As renewable energy resources increasingly penetrate the electric grid,the inertia capability of power systems has become a developmental bottleneck.Nevertheless,the importance of primary frequency response(PFR)when making generation-expansion plans has been largely ignored.In this paper,we propose an optimal generation-expansion planning framework for wind and thermal power plants that takes PFR into account.The model is based on the frequency equivalent model.It includes investment,startup/shutdown,and typical operating costs for both thermal and renewable generators.The linearization constraints of PFR are derived theoretically.Case studies based on the modified IEEE 39-bus system demonstrate the efficiency and effectiveness of the proposed method.Compared with methods that ignore PFR,the method proposed in this paper can effectively reduce the cost of the entire planning and operation cycle,improving the accommodation rate of renewable energy.展开更多
文摘Facilitated transport membranes for post-combustion carbon capture are one of the technologies to achieve efficient and large-scale capture.The central principle is to utilize the affinity of CO_(2) for the carrier to achieve efficient separation and to break the Robson upper bound.This paper reviews the progress of facilitated transport membranes research regarding polymer materials,principles,and problems faced at this stage.Firstly,we briefly introduce the transport mechanism of the facilitated transport membranes.Then the research progress of several major polymers used for facilitated transport membranes for CO_(2)/N_(2) separation was presented in the past five years.Additionally,we analyze the primary challenges of facilitated transport membranes,including the influence of water,the effect of temperature,the saturation effect of the carrier,and the process configuration.Finally,we also delve into the challenges and competitiveness of facilitated transport membranes.
基金supported by the National Natural Science Foundation of China(U22A20374,52373273)National High Level Hospital Clinical Research Funding of China-Japan Friendship Hospital(Grant number:2024-NHLHCRF-JBGSWZ-02).
文摘With the deepening of epigenetic research,studies have shown that N6-methyladenosine(m^(6)A)is closely related to the development of rheumatoid arthritis(RA),but the mechanism is still unclear.In the study,we collected synovial tissues from normal controls and patients with osteoarthritis(OA)or RA.The levels of m^(6)A and inflammation were analyzed by immunofluorescence staining and western blotting.The roles of IGF2BP3 in cell proliferation and inflammatory activation were explored using transfection and RNA immunoprecipitation assays.IGF2BP3^(−/−)mice were generated and used to establish an arthritis mouse model by transferring serum from adult arthritis K/BxN mice.We found m^(6)A levels were markedly increased in RA patients and mouse models,and the expression of IGF2BP3 was upregulated in individuals with RA and related to the levels of inflammatory markers.IGF2BP3 played an important part in RA-fibroblast-like synoviocytes(FLS)by promoting cell proliferation,migration,invasion,inflammatory cytokine release and inhibiting autophagy.In addition,IGF2BP3 inhibited autophagy to reduce ROS production,thereby decreasing the inflammatory activation of macrophages.More importantly,RASGRF1-mediated mTORC1 activation played a crucial role in the ability of IGF2BP3 to promote cell proliferation and inflammatory activation.In an arthritis model of IGF2BP3^(−/−)mice,IGF2BP3 knockout inhibited RA-FLS proliferation and inflammatory infiltration,and further ameliorated RA joint injury.Our study revealed an important role for IGF2BP3 in RA progression.The targeted inhibition of IGF2BP3 reduced cell proliferation and inflammatory activation and limited RA development,providing a potential strategy for RA therapy.
基金supported by the National Natural Science Foundation of China(U22A20374).
文摘Rheumatoid arthritis(RA)is a progressive autoimmune disease characterized by bone destruction that is primarily caused by the overactivation of osteoclasts(OCs),which are critical therapeutic targets.Triptolide(TP)has strong anti-RA effects but is limited by its narrow therapeutic window and associated toxicity,necessitating combination therapy to increase its efficacy and reduce side effects.Medicarpin(Med),a flavonoid with anti-inflammatory and anti-bone destruction properties,has shown potential in reducing osteoclastogenesis.However,the mechanisms underlying the synergistic effects of TP and Med on RA treatment remain unclear.We addressed this issue by evaluating the effects of TP,Med,and their combination on a collagen-induced arthritis(CIA)rat model,with a focus on bone erosion as the primary research endpoint.We subsequently performed experimental validation in an in vitro OC dif-ferentiation model to assess the impacts of these treatments on OC formation and function.Based on polymerase chain reaction(PCR)microarray data from RA patients,further investigations focused on N^(6)-methyladenosine(m^(6)A)methylation and its regulatory factors,methyltransferase-like 3(METTL3)and YT521-B homology domain family protein 1(YTHDF1),which have been identified as potential tar-gets of TP and Med.Key findings revealed that the TP and Med combination significantly alleviated bone destruction and inhibited OC differentiation,exerting stronger effects at lower doses than either drug alone.Mechanistically,TP and Med synergistically modulated METTL3 and YTHDF1 to suppress osteo-clastogenesis through distinct m6 A methylation pathways,contributing to the mitigation of RA-associated bone destruction.Overall,our data highlight the potential of the m^(6)A modification as a ther-apeutic mechanism for the combined use of TP and Med for RA treatment,providing a theoretical basis for the clinical application of herbal active ingredient combinations.
基金supported by the National Key Research and Development Program of China(2022YFD1300202)the Technology Innovation and Application Development Special Project of Chongqing(cstc2021jscx-gksbX0008).
文摘Background Reproductive efficiency in goats is closely linked to the healthy development of follicles,with the proliferation of ovarian granulosa cells(GCs)playing a crucial role in this process.Sirtuin 3(SIRT3),an enzyme that catalyzes post-translational modifications(PTMs)of proteins,is known to regulate a variety of mitochondrial metabolic pathways,thereby affecting cell fate.However,the specific effect of SIRT3 on the follicular development process remains unclear.Therefore,this study aimed to investigate the regulatory role of SIRT3 in the mitochondrial function and proliferation of goat GCs,as well as the underlying mechanisms involved.Results In this study,GCs from small follicles in goat ovaries presented increased proliferative potential and elevated SIRT3 expression levels compared with those from large follicles.In vitro,SIRT3 overexpression enhanced mitochondrial function,promoted proliferation and inhibited apoptosis in GCs.Correspondingly,the inhibition of SIRT3 led to the opposite effects.Notably,SIRT3 interacted with carnitine palmitoyl transferase 2(CPT2)and stabilized the CPT2 protein by mediating delactylation,which prolonged the half-life of CPT2 and prevented its degradation.Further investigation revealed that CPT2 overexpression enhanced fatty acidβ-oxidation and mitochondrial function in GCs.Additionally,CPT2 promoted the proliferation of GCs by increasing the protein levels ofβ-catenin and its downstream target,cyclin D1(CCND1).However,this effect was reversed by 3-TYP(a SIRT3 inhibitor).Conclusions SIRT3 stabilizes CPT2 protein expression through delactylation,thereby enhancing mitochondrial function and the proliferative capacity of GCs in goats.This study provides novel insights into the molecular mechanisms and regulatory pathways involved in mammalian follicular development.
基金the National Natural Science Foundation of China(62375127,82272664)Hunan Provincial Natural Science Foundation of China(2022JJ30843)+5 种基金the Science and Technology Development Fund Guided by Central Govern-ment(2021Szvup169)the Scientic Research Program of Hunan Provincial Health Commission(B202304077077)the Fundamental Research Funds for the Central Universities(NS2022035)Prospective Layout Special Fund of Nanjing University of Aero-nautics and Astronautics(ILA-22022)Graduate Research and Innovation Program of Nanjing University of Aeronautics and Astronautics(xcxjh20220328)Experimental Technology Research and Development Project of NUAA(No.SYJS202303Z)for the grant。
文摘Osteosarcoma is the most common primary bone tumor with high malignancy.It is particularly necessary to achieve rapid and accurate diagnosis in its intraoperative examination and early diagnosis.Accordingly,the multimodal microscopic imaging diagnosis system constructed by bright field,spontaneous fluorescence and polarized light microscopic imaging was used to study the pathological mechanism of osteosarcoma from the tissue microenvironment level and achieve rapid and accurate diagnosis.First,the multimodal microscopic images of normal and osteosarcoma tissue slices were collected to characterize the overall morphology of the tissue microenvironment of the samples,the arrangement structure of collagen fibers and the content and distribution of endogenous fluorescent substances.Second,based on the correlation and complementarity of the feature information contained in the three single-mode images,combined with convolutional neural network(CNN)and image fusion methods,a multimodal intelligent diagnosis model was constructed to effectively improve the information utilization and diagnosis accuracy.The accuracy and true positivity of the multimodal diagnostic model were significantly improved to 0.8495 and 0.9412,respectively,compared to those of the single-modal models.Besides,the difference of tissue microenvironments before and after cancerization can be used as a basis for cancer diagnosis,and the information extraction and intelligent diagnosis of osteosarcoma tissue can be achieved by using multimodal microscopic imaging technology combined with deep learning,which significantly promoted the application of tissue microenvironment in pathological examination.This diagnostic system relies on its advantages of simple operation,high efficiency and accuracy and high cost-effectiveness,and has enormous clinical application potential and research significance.
基金supported by the National Key Research and Development Program of China (2023YFD1902703)the National Natural Science Foundation of China (Key Program) (U23A20158)。
文摘Cropland nitrate leaching is the major nitrogen(N) loss pathway, and it contributes significantly to water pollution. However, cropland nitrate leaching estimates show great uncertainty due to variations in input datasets and estimation methods. Here, we presented a re-evaluation of Chinese cropland nitrate leaching, and identified and quantified the sources of uncertainty by integrating three cropland area datasets, three N input datasets, and three estimation methods. The results revealed that nitrate leaching from Chinese cropland averaged 6.7±0.6 Tg N yr^(-1)in 2010, ranging from 2.9 to 15.8 Tg N yr^(-1)across 27 different estimates. The primary contributor to the uncertainty was the estimation method, accounting for 45.1%, followed by the interaction of N input dataset and estimation method at 24.4%. The results of this study emphasize the need for adopting a robust estimation method and improving the compatibility between the estimation method and N input dataset to effectively reduce uncertainty. This analysis provides valuable insights for accurately estimating cropland nitrate leaching and contributes to ongoing efforts that address water pollution concerns.
基金financially supported by the Shanghai RisingStar Program(No.23QA1403700)the National Natural Science Foundation of China(NSFC,Grant No.U2230102)+1 种基金the sponsored by National Key Research and Development Program of China(No.2021YFB3502200)the Shanghai Technical Service Center of Science and Engineering Computing,Shanghai University.
文摘Platinum-based(Pt)catalysts are notoriously susceptible to deactivation in industrial chemical processes due to carbon monoxide(CO)poisoning.Overcoming this poisoning deactivation of Pt-based catalysts while enhancing their catalytic activity,selectivity,and durability remains a major challenge.Herein,we propose a strategy to enhance the CO tolerance of Pt clusters(Pt_n)by introducing neighboring functionalized vip single atoms(such as Fe,Co,Ni,Cu,Sb,and Bi).Among them,antimony(Sb)single atoms(SAs)exhibit significant performance enhancement,achieving 99%CO selectivity and 33.6%CO_(2)conversion at 450℃,Experimental results and density functional theory(DFT)calculations indicate the optimization arises from the electronic interaction between neighboring functionalized Sb SAs and Pt clusters,leading to optimal 5d electron redistribution in Pt clusters compared to other functionalized vip single atoms.The redistribution of 5d electrons weaken both theσdonation andπbackdonation interactions,resulting in a weakened bond strength with CO and enhancing catalyst activity and selectivity.In situ environmental transmission electron microscopy(ETEM)further demonstrates the exception thermal stability of the catalyst,even under H_(2)at 700℃.Notably,the functionalized Sb SAs also improve CO tolerance in various heterogenous catalysts,including Co/CeO_(2),Ni/CeO_(2),Pt/Al_(2)O_(3),and Pt/CeO_(2)-C.This finding provides an effective approach to overcome the primary challenge of CO poisoning in Pt-based catalysts,making their broader applications in various industrial catalysts.
基金financially supported by the National Natural Science Foundation of China(No.U2330120)the Natural Science Foundation of Sichuan Province of China(No.2023NSFSC0313)the Basic Research Cultivation Project of Southwest Jiaotong University(No.2682023KJ024)。
文摘Bimodal pressure sensors capable of simultaneously detecting static and dynamic forces are essential to medical detection and bio-robotics.However,conventional pressure sensors typically integrate multiple operating mechanisms to achieve bimodal detection,leading to complex device architectures and challenges in signal decoupling.In this work,we address these limitations by leveraging the unique piezotronic effect of Y-ion-doped ZnO to develop a bimodal piezotronic sensor(BPS)with a simplified structure and enhanced sensitivity.Through a combination of finite element simulations and experimental validation,we demonstrate that the BPS can effectively monitor both dynamic and static forces,achieving an on/off ratio of 1029,a gauge factor of 23,439 and a static force response duration of up to 600 s,significantly outperforming the performance of conventional piezoelectric sensors.As a proof-of-concept,the BPS demonstrates the continuous monitoring of Achilles tendon behavior under mixed dynamic and static loading conditions.Aided by deep learning algorithms,the system achieves 96%accuracy in identifying Achilles tendon movement patterns,thus enabling warnings for dangerous movements.This work provides a viable strategy for bimodal force monitoring,highlighting its potential in wearable electronics.
文摘The swinging-loading process is essential for automatic artillery loading systems.This study focuses on the problems of reliability analysis that affect swinging-loading positioning accuracy.A dynamic model for a multi degree-of-freedom swinging-loading-integrated rigid-flexible coupling system is established.This model is based on the identification of key parameters and platform experiments.Based on the spatial geometric relationship between the breech and loader during modular charge transfer and the possible maximum interference depth of the modular charge,a new failure criterion for estimating the reliability of swinging-loading positioning accuracy is proposed.Considering the uncertainties in the operation of the pendulum loader,the direct probability integration method is introduced to analyze the reliability of the swinging-loading positioning accuracy under three different charge numbers.The results indicate that under two and four charges,the swinging-loading process shows outstanding reliability.However,an unstable stage appears when the swinging motion occurred under six charges,with a maximum positioning failure probability of 0.0712.A comparison between the results obtained under the conventional and proposed criteria further reveals the effectiveness and necessity of the proposed criterion.
基金supported by the National Natural Science Foundation of China(No.52303328)the Postdoctoral Innovation Talents Support Program(No.BX20220257)the Sichuan Science and Technology Program(No.2023NSFSC0313).
文摘The emerging interfacial polarization strategy exhibits applicative potential in piezoelectric enhancement.However,there is an ongoing effort to address the inherent limitations arising from charge bridging phenomena and stochastic interface disorder that plague the improvement of piezoelectric performance.Here,we report a dual structure reinforced MXene/PVDF-TrFE piezoelectric composite,whose piezoelectricity is enhanced under the coupling effect of interfacial polarization and structural design.Synergistically,molecular dynamics simulations,density functional theory calculations and experimental validation revealed the details of interfacial interactions,which promotes the net spontaneous polarization of PVDF-TrFE from the 0.56 to 31.41 Debye.The oriented MXene distribution and porous structure not only tripled the piezoelectric response but also achieved an eightfold increase in sensitivity within the low-pressure region,along with demonstrating cyclic stability exceeding 20,000 cycles.The properties reinforcement originating from dual structure is elucidated through the finite element simulation and experimental validation.Attributed to the excellent piezoelectric response and deep learning algorithm,the sensor can effectively recognize the signals of artery pulse and finger flexion.Finally,a 3×3 sensor array is fabricated to monitor the pressure distribution wirelessly.This study provides an innovative methodology for reinforcing interfacial polarized piezoelectric materials and insight into structural designs.
基金supported by the National Natural Science Foundation of China(Grants Nos.62104125and 62311530102)Shenzhen Science and Technology Program(Grant Nos.JCYJ20220530143013030 and JCYJ20240813111910014)+1 种基金Guangdong Innovative and Entrepreneurial Research Team Program(Grant No.2021ZT09L197)Tsinghua Shenzhen International Graduate School-Shenzhen Pengrui Young Faculty Program of Shenzhen Pengrui Foundation(Grant No.SZPR2023005)。
文摘The embodied artificial intelligence(EAI)is driving a significant transformation in robotics,enhancing their autonomy,efficiency and evolution ability.In this rapidly evolving technological landscape,robots need numerous sensors to realize high levels of perception,precision,safety,adaptability,and intelligence.Triboelectric and piezoelectric sensors address these needs by providing high sensitivity,flexibility,and the capability of self-powered sensing,leveraging the revolutionary nature of nanogenerators to convert mechanical energy into electrical energy on basis of Maxwell’s displacement current.These sensors surpass externally powered passive sensors by offering continuous operation,reduced maintenance,and the capability to function in remote or harsh environments.The integration of EAI with advanced nanogenerators sensors could position robotics to perform autonomously,efficiently,and safely,paving the way for innovative applications in various domains such as industrial automation,environmental monitoring,healthcare,and smart homes.In this paper,the fundamental theories,design,manufacturing,and applications of nanogenerators are comprehensively reviewed as afoundation of the advanced sensors for intelligent robotics in the new era,with three major application fields:sensing(including human–robot interaction,exteroceptive sensing and proprioceptive sensing),computing and actuating.Perspectives are addressed for nanogenerators systems in future development.
文摘The integration of deep learning into smart grid operations addresses critical challenges in dynamic load forecasting and optimal dispatch amid increasing renewable energy penetration.This study proposes a hybrid LSTM-Transformer architecture for multi-scale temporal-spatial load prediction,achieving 28%RMSE reduction on real-world datasets(CAISO,PJM),coupled with a deep reinforcement learning framework for multi-objective dispatch optimization that lowers operational costs by 12.4%while ensuring stability constraints.The synergy between adaptive forecasting models and scenario-based stochastic optimization demonstrates superior performance in handling renewable intermittency and demand volatility,validated through grid-scale case studies.Methodological innovations in federated feature extraction and carbon-aware scheduling further enhance scalability for distributed energy systems.These advancements provide actionable insights for grid operators transitioning to low-carbon paradigms,emphasizing computational efficiency and interoperability with legacy infrastructure.
文摘Correction to:Nano-Micro Lett.(2023)15:233 https://doi.org/10.1007/s40820-023-01201-7 Following publication of the original article[1],the authors reported that the first two lines of the introduction were accidentally placed in the right-hand column of the page in the PDF,which affects the readability.
基金financial support provided by the National Key Research and Development Program of China(Grant No.2017YFB0701600)Key Program of Science and Technology of Yunnan Province(Grant No.202002AB080001-2)。
文摘3D printing technology is a new type of precision forming technology and the core technology of the third industrial revolution.The powder-based 3D printing technology of titanium and its alloys have received great attention in biomedical applications since its advantages of custom manufacturing,costsaving,time-saving,and resource-saving potential.In particular,the personalized customization of 3D printing can meet specific needs and achieve precise control of micro-organization and structural design.The purpose of this review is to present the most advanced multi-material 3D printing methods for titanium-based biomaterials.We first reviewed the bone tissue engineering,the application of titanium alloy as bone substitutes and the development of manufacturing technology,which emphasized the advantages of 3D printing technology over traditional manufacturing methods.What is more,the optimization design of the hierarchical structure was analyzed to achieve the best mechanical properties,and the biocompatibility and osseointegration ability of the porous titanium alloy after implantation in living bodies was analyzed.Finally,we emphasized the development of digital tools such as artificial intelligence,which provides new ideas for the rational selection of processing parameters.The 3D printing titanium-based alloys will meet the huge market demand in the biomedical field,but there are still many challenges,such as the trade-off between high strength and low modulus,optimization of process parameters and structural design.We believe that the combination of mechanical models,machine learning,and metallurgical knowledge may shape the future of metal printing.
基金This work is supported by the grant from the National Natural Science Foundation of China under Grants 62104125 and 62311530102,Guangdong Innovative and Entrepreneurial Research Team Program(2021ZT09L197)Guangdong Basic and Applied Basic Research Foundation(2020A1515110887)+1 种基金Tsinghua Shenzhen International Graduate School-Shenzhen Pengrui Young Faculty Program of Shenzhen Pengrui Foundation(No.SZPR2023005)Shenzhen Science and Technology Program(JCYJ20220530143013030).
文摘With the development of artificial intelligence,stiffness sensors are extensively utilized in various fields,and their integration with robots for automated palpation has gained significant attention.This study presents a broad range self-powered stiffness sensor based on the triboelectric nanogenerator(Stiff-TENG)for variable inclusions in soft objects detection.The Stiff-TENG employs a stacked structure comprising an indium tin oxide film,an elastic sponge,a fluorinated ethylene propylene film with a conductive ink electrode,and two acrylic pieces with a shielding layer.Through the decoupling method,the Stiff-TENG achieves stiffness detection of objects within 1.0 s.The output performance and characteristics of the TENG for different stiffness objects under 4 mm displacement are analyzed.The Stiff-TENG is successfully used to detect the heterogeneous stiffness structures,enabling effective recognition of variable inclusions in soft object,reaching a recognition accuracy of 99.7%.Furthermore,its adaptability makes it well-suited for the detection of pathological conditions within the human body,as pathological tissues often exhibit changes in the stiffness of internal organs.This research highlights the innovative applications of TENG and thereby showcases its immense potential in healthcare applications such as palpation which assesses pathological conditions based on organ stiffness.
基金supported by the National Natural Science Foundation of China(52261145701 and U21A20162)the 2115 Talent Development Program of China Agricultural University.
文摘The function-led design of porous hydrochar from mineral-rich biowaste for environmental applications inevitably suffers from carbon-ash recalcitrance.However,a method to alter the original carbon skeleton with ash remains elusive and hinders the availability of hydrochar.Herein,we propose a facile strategy for breaking the rigid structure of carbon-ash coupled hydrochar using phase-tunable molten carbonates.A case system was designed in which livestock manure and NaHCO3 were used to prepare the activated hydrochar,and NH3 served as the target contaminant.Due to the redox effect,we found that organic fractions significantly advanced the melting temperature of Na2CO3 below 800℃.The Na species steadily broke the carbon-ash interaction as the thermal intensity increased and transformed inorganic constituents to facilitate ash dissolution,rebuilding the hydrochar skeleton with abundant hierarchical channels and active defect edges.The surface polarity and mesopore distribution collectively governed the five cycles NH3 adsorption attenuation process.Manure hydrochar delivered favorable potential for application with a maximum overall adsorption capacity of 100.49 mg·g^(-1).Integrated spectroscopic characterization and theoretical computations revealed that incorporating NH3 on the carbon surface could transfer electrons to chemisorbed oxygen,which promoted the oxidation of pyridine-N during adsorption.This work offers deep insight into the structure function correlation of hydrochar and inspires a more rational design of engineered hydrochar from high-ash biowaste.
基金This work is supported by the National Science Foundation of China under grant No.61901403,61790551,and 61925106,Youth Innovation Fund of Xiamen No.3502Z20206039 and Tsinghua-Foshan Innovation Special Fund(TFISF)No.2020THFS0109.
文摘In urban Vehicular Ad hoc Networks(VANETs),high mobility of vehicular environment and frequently changed network topology call for a low delay end-to-end routing algorithm.In this paper,we propose a Multi-Agent Reinforcement Learning(MARL)based decentralized routing scheme,where the inherent similarity between the routing problem in VANET and the MARL problem is exploited.The proposed routing scheme models the interaction between vehicles and the environment as a multi-agent problem in which each vehicle autonomously establishes the communication channel with a neighbor device regardless of the global information.Simulation performed in the 3GPP Manhattan mobility model demonstrates that our proposed decentralized routing algorithm achieves less than 45.8 ms average latency and high stability of 0.05%averaging failure rate with varying vehicle capacities.
基金supported in part by the National Natural Science Foundation of China(No.U1966204,51907064).
文摘As renewable energy resources increasingly penetrate the electric grid,the inertia capability of power systems has become a developmental bottleneck.Nevertheless,the importance of primary frequency response(PFR)when making generation-expansion plans has been largely ignored.In this paper,we propose an optimal generation-expansion planning framework for wind and thermal power plants that takes PFR into account.The model is based on the frequency equivalent model.It includes investment,startup/shutdown,and typical operating costs for both thermal and renewable generators.The linearization constraints of PFR are derived theoretically.Case studies based on the modified IEEE 39-bus system demonstrate the efficiency and effectiveness of the proposed method.Compared with methods that ignore PFR,the method proposed in this paper can effectively reduce the cost of the entire planning and operation cycle,improving the accommodation rate of renewable energy.
