Luminescent metal-organic frameworks(MOFs)have garnered significant attention due to their structural tunability and potential applications in solid-state lighting,bioimaging,sensing,anticounterfeiting,and other field...Luminescent metal-organic frameworks(MOFs)have garnered significant attention due to their structural tunability and potential applications in solid-state lighting,bioimaging,sensing,anticounterfeiting,and other fields.Nevertheless,due to the tendency of1,4-benzenedicarboxylic acid(BDC)to rotate within the framework,MOFs composed of it exhibit significant non-radiative energy dissipation and thus impair the emissive properties.In this study,efficient luminescence of MIL-140A nanocrystals(NCs)with BDC rotors as ligands is achieved by pressure treatment strategy.Pressure treatment effectively modulates the pore structure of the framework,enhancing the interactions between the N,N-dimethylformamide vip molecules and the BDC ligands.The enhanced host-vip interaction contributes to the structural rigidity of the MOF,thereby suppressing the rotation-induced excited-state energy loss.As a result,the pressure-treated MIL-140A NCs displayed bright blue-light emission,with the photoluminescence quantum yield increasing from an initial 6.8%to 69.2%.This study developed an effective strategy to improve the luminescence performance of rotor ligand MOFs,offers a new avenue for the rational design and synthesis of MOFs with superior luminescent properties.展开更多
The primary mechanism of secondary injury after cerebral ischemia may be the brain inflammation that emerges after an ischemic stroke,which promotes neuronal death and inhibits nerve tissue regeneration.As the first i...The primary mechanism of secondary injury after cerebral ischemia may be the brain inflammation that emerges after an ischemic stroke,which promotes neuronal death and inhibits nerve tissue regeneration.As the first immune cells to be activated after an ischemic stroke,microglia play an important immunomodulatory role in the progression of the condition.After an ischemic stroke,peripheral blood immune cells(mainly T cells)are recruited to the central nervous system by chemokines secreted by immune cells in the brain,where they interact with central nervous system cells(mainly microglia)to trigger a secondary neuroimmune response.This review summarizes the interactions between T cells and microglia in the immune-inflammatory processes of ischemic stroke.We found that,during ischemic stroke,T cells and microglia demonstrate a more pronounced synergistic effect.Th1,Th17,and M1 microglia can co-secrete proinflammatory factors,such as interferon-γ,tumor necrosis factor-α,and interleukin-1β,to promote neuroinflammation and exacerbate brain injury.Th2,Treg,and M2 microglia jointly secrete anti-inflammatory factors,such as interleukin-4,interleukin-10,and transforming growth factor-β,to inhibit the progression of neuroinflammation,as well as growth factors such as brain-derived neurotrophic factor to promote nerve regeneration and repair brain injury.Immune interactions between microglia and T cells influence the direction of the subsequent neuroinflammation,which in turn determines the prognosis of ischemic stroke patients.Clinical trials have been conducted on the ways to modulate the interactions between T cells and microglia toward anti-inflammatory communication using the immunosuppressant fingolimod or overdosing with Treg cells to promote neural tissue repair and reduce the damage caused by ischemic stroke.However,such studies have been relatively infrequent,and clinical experience is still insufficient.In summary,in ischemic stroke,T cell subsets and activated microglia act synergistically to regulate inflammatory progression,mainly by secreting inflammatory factors.In the future,a key research direction for ischemic stroke treatment could be rooted in the enhancement of anti-inflammatory factor secretion by promoting the generation of Th2 and Treg cells,along with the activation of M2-type microglia.These approaches may alleviate neuroinflammation and facilitate the repair of neural tissues.展开更多
Deficiency or restriction of Zn absorption in soils is one of the most common micronutrients deficient in cereal plants. To investigate critical micronutrient interaction in zinc deficiency and zinc sufficient in soil...Deficiency or restriction of Zn absorption in soils is one of the most common micronutrients deficient in cereal plants. To investigate critical micronutrient interaction in zinc deficiency and zinc sufficient in soil, a factorial experiment based on completely randomized design (CRD) with three replications was conducted in 2023. Six wheat cultivars with different Zn efficiency were used. The cultivars were grown under Zn deficiency and adequate conditions. Results showed that in Zn deficiency conditions, with increasing Zn concentration in the roots, Fe concentrations were increased too, while the Cu and Mn concentrations decreased. In the same condition and with increasing Zn concentration in shoots, the concentrations of Fe and Mn decreased, while Cu were increased. However, by increasing Zn concentration, Fe, Cu, and Mn concentrations were increased in Zn deficiency condition in grains, as well as Zn sufficient conditions. RST (root to shoot micronutrient translocation) comparison of cultivars showed that in lack of Zn, the ability of translocation of Zn, Fe, and Mn in Zn-inefficient cultivar from root to shoot was higher than inefficient cultivar. In the same conditions, the capability of Zn-inefficient cultivar in Cu translocation from root to shoot was lower than other cultivars. In general, it seems that in Zn deficiency conditions, there are antagonistic effects among Zn, Cu and Mn and synergistic effects between Zn and Fe in the root. Also, in Zn sufficient conditions, there were synergistic effects among all studies micronutrients which include Zn, Fe, Cu, and Mn.展开更多
Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air poll...Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air pollution is crucial for mitigating climate change,improving air quality,and promoting the sustainable development of food systems.However,the literature lacks a comprehensive review of these interactions,particularly in the current phase of rapid development in the field.To address this gap,this study systematically reviews recent research on the impacts of climate change and air pollution on food systems,as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution.In addition,this study summarizes various strategies for mitigation and adaptation,including adjustments in agricultural practices and food supply chains.Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions.This review offers a critical overview of current research on the interactions among food systems,climate change,and air pollution and highlights future research directions to support the transition to sustainable food systems.展开更多
Lithium-ion batteries are widely recognized as prime candidates for energy storage devices.Ethylene carbonate(EC)has become a critical component in conventional commercial electrolytes due to its exceptional film-form...Lithium-ion batteries are widely recognized as prime candidates for energy storage devices.Ethylene carbonate(EC)has become a critical component in conventional commercial electrolytes due to its exceptional film-forming properties and high dielectric constant.However,the elevated freezing point,high viscosity,and strong solvation energy of EC significantly hinder the transport rate of Li^(+)and the desolvation process at low temperatures.This leads to substantial capacity loss and even lithium plating on graphite anodes.Herein,we have developed an efficient electrolyte system specifically designed for lowtemperature conditions,which consists of 1.0 M lithium bis(fluorosulfonyl)imide(LiFSI)in isoxazole(IZ)with fluorobenzene(FB)as an uncoordinated solvent and fluoroethylene carbonate(FEC)as a filmforming co-solvent.This system effectively lowers the desolvation energy of Li^(+)through dipole-dipole interactions.The weak solvation capability allows more anions to enter the solvation sheath,promoting the formation of contact ion pairs(CIPs)and aggregates(AGGs)that enhance the transport rate of Li^(+)while maintaining high ionic conductivity across a broad temperature range.Moreover,the formation of inorganic-dominant interfacial phases on the graphite anode,induced by fluoroethylene carbonate,significantly enhances the kinetics of Li^(+)transport.At a low temperature of-20℃,this electrolyte system achieves an impressive reversible capacity of 200.9 mAh g^(-1)in graphite half-cell,which is nearly three times that observed with conventional EC-based electrolytes,demonstrating excellent stability throughout its operation.展开更多
Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from...Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from the obstacles of low sensitivity,narrow bandwidth,and asymmetric Fano resonance perturbations.Here,we demonstrated an overcoupled resonator with a high plasmon-molecule coupling coefficient(μ)(OC-Hμresonator)by precisely controlling the radiation loss channel,the resonator-oscillator coupling channel,and the frequency detuning channel.We observed a strong dependence of the sensing performance on the coupling state,and demonstrated that OC-Hμresonator has excellent sensing properties of ultra-sensitive(7.25%nm^(−1)),ultra-broadband(3–10μm),and immune asymmetric Fano lineshapes.These characteristics represent a breakthrough in SEIRA technology and lay the foundation for specific recognition of biomolecules,trace detection,and protein secondary structure analysis using a single array(array size is 100×100μm^(2)).In addition,with the assistance of machine learning,mixture classification,concentration prediction and spectral reconstruction were achieved with the highest accuracy of 100%.Finally,we demonstrated the potential of OC-Hμresonator for SARS-CoV-2 detection.These findings will promote the wider application of SEIRA technology,while providing new ideas for other enhanced spectroscopy technologies,quantum photonics and studying light–matter interactions.展开更多
Drug development remains a critical issue in the field of biomedicine.With the rapid advancement of information technologies such as artificial intelligence(AI)and the advent of the big data era,AI-assisted drug devel...Drug development remains a critical issue in the field of biomedicine.With the rapid advancement of information technologies such as artificial intelligence(AI)and the advent of the big data era,AI-assisted drug development has become a new trend,particularly in predicting drug-target associations.To address the challenge of drug-target prediction,AI-driven models have emerged as powerful tools,offering innovative solutions by effectively extracting features from complex biological data,accurately modeling molecular interactions,and precisely predicting potential drug-target outcomes.Traditional machine learning(ML),network-based,and advanced deep learning architectures such as convolutional neural networks(CNNs),graph convolutional networks(GCNs),and transformers play a pivotal role.This review systematically compiles and evaluates AI algorithms for drug-and drug combination-target predictions,highlighting their theoretical frameworks,strengths,and limitations.CNNs effectively identify spatial patterns and molecular features critical for drug-target interactions.GCNs provide deep insights into molecular interactions via relational data,whereas transformers increase prediction accuracy by capturing complex dependencies within biological sequences.Network-based models offer a systematic perspective by integrating diverse data sources,and traditional ML efficiently handles large datasets to improve overall predictive accuracy.Collectively,these AI-driven methods are transforming drug-target predictions and advancing the development of personalized therapy.This review summarizes the application of AI in drug development,particularly in drug-target prediction,and offers recommendations on models and algorithms for researchers engaged in biomedical research.It also provides typical cases to better illustrate how AI can further accelerate development in the fields of biomedicine and drug discovery.展开更多
The stability of supersonic inlets faces challenges due to various changes in flight conditions,and flow control methods that address shock wave/boundary layer interactions under only one set of conditions cannot meet...The stability of supersonic inlets faces challenges due to various changes in flight conditions,and flow control methods that address shock wave/boundary layer interactions under only one set of conditions cannot meet developmental requirements.This paper proposes an adaptive bump control scheme and employs dynamic mesh technology for numerical simulation to investigate the unsteady control effects of adaptive bumps.The obtained results indicate that the use of moving bumps to control shock wave/boundary layer interactions is feasible.The adaptive control effects of five different bump speeds are evaluated.Within the range of bump speeds studied,the analysis of the flow field structure reveals the patterns of change in the separation zone area during the control process,as well as the relationship between the bump motion speed and the control effect on the separation zone.It is concluded that the moving bump endows the boundary layer with additional energy.展开更多
Accurate prediction of drug-target interactions(DTIs)plays a pivotal role in drug discovery,facilitating optimization of lead compounds,drug repurposing and elucidation of drug side effects.However,traditional DTI pre...Accurate prediction of drug-target interactions(DTIs)plays a pivotal role in drug discovery,facilitating optimization of lead compounds,drug repurposing and elucidation of drug side effects.However,traditional DTI prediction methods are often limited by incomplete biological data and insufficient representation of protein features.In this study,we proposed KG-CNNDTI,a novel knowledge graph-enhanced framework for DTI prediction,which integrates heterogeneous biological information to improve model generalizability and predictive performance.The proposed model utilized protein embeddings derived from a biomedical knowledge graph via the Node2Vec algorithm,which were further enriched with contextualized sequence representations obtained from ProteinBERT.For compound representation,multiple molecular fingerprint schemes alongside the Uni-Mol pre-trained model were evaluated.The fused representations served as inputs to both classical machine learning models and a convolutional neural network-based predictor.Experimental evaluations across benchmark datasets demonstrated that KG-CNNDTI achieved superior performance compared to state-of-the-art methods,particularly in terms of Precision,Recall,F1-Score and area under the precision-recall curve(AUPR).Ablation analysis highlighted the substantial contribution of knowledge graph-derived features.Moreover,KG-CNNDTI was employed for virtual screening of natural products against Alzheimer's disease,resulting in 40 candidate compounds.5 were supported by literature evidence,among which 3 were further validated in vitro assays.展开更多
This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The partici...This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The participants were a 17-year-old young lady with ASD and intellectual deficit, and a control participant: a preadolescent with ASD but no intellectual deficit (Asperger syndrome). The game is comprised of four phases: greetings, pairing, imitation, and closing. Field educators were involved, playing specific roles: visual or physical inciter. The use of a robot allows for catching the participants’ attention, playing the imitation game for a longer period of time than with a human partner, and preventing the game partner’s negative facial expressions resulting from tiredness, impatience, or boredom. The participants’ behavior was observed in terms of initial approach towards the robot, positioning relative to the robot in terms of distance and orientation, reactions to the robot’s voice or moves, signs of happiness, and imitation attempts. Results suggest a more and more natural approach towards the robot during the sessions, as well as a higher level of social interaction, based on the variations of the parameters listed above. We use these preliminary results to draw the next steps of our research work as well as identify further perspectives, with this aim in mind: improving social interactions with adolescents with ASD and intellectual deficit, allowing for better integration of these people into our societies.展开更多
Aromatic nitro compounds present substantial health and environmental concerns due to their toxic nature and potential explosive properties.Consequently,the development of host–vip molecular recognition systems for...Aromatic nitro compounds present substantial health and environmental concerns due to their toxic nature and potential explosive properties.Consequently,the development of host–vip molecular recognition systems for these compounds serves a dual-purpose:enabling the fabrication of high-performance sensors for detection and guiding the design of efficient adsorbents for environmental remediation.This study investigated the host–vip recognition behavior of perethylated pillar[n]arenes toward two aromatic nitro molecules,1-chloro-2,4-dinitrobenzene and picric acid.Various techniques including^(1)H NMR,2D NOESY NMR,and UV-vis spectroscopy were employed to explore the binding behavior between pillararenes and aromatic nitro vips in solution.Moreover,valuable single crystal structures were obtained to elucidate the distinct solid-state assembly behaviors of these vips with different pillararenes.The assembled solid-state supramolecular structures observed encompassed a 1:1 host–vip inclusion complex,an external binding complex,and an exo-wall tessellation complex.Furthermore,based on the findings from these systems,a pillararene-based test paper was developed for efficient picric acid detection,and the removal of picric acid from solution was also achieved using pillararenes powder.This research provides novel insights into the development of diverse host–vip systems toward hazardous compounds,offering potential applications in environmental protection and explosive detection domains.展开更多
This study investigates the establishment of scientific links between the People's Republic of China(PRC)and the United Kingdom(UK)in the mid-2Oth century,focusing on the early development of China's nuclear i...This study investigates the establishment of scientific links between the People's Republic of China(PRC)and the United Kingdom(UK)in the mid-2Oth century,focusing on the early development of China's nuclear industry.Sino-British scientific interactions took place across multiple dimensions,involving various institutions and individuals.Around 1949,UK-trained Chinese nuclear scientists returned to China,bringing advanced technological knowledge and extensive practical experience.The PRC regarded the UK as a crucial gateway to overcoming the technological blockade imposed by the United States(and later the Soviet Union)and sought to establish scientific relations with the UK through semi-official and unofficial channels.Specifically,these connections manifested in the interactions between the Chinese Academy of Sciences(CAS)and the Royal Society of London,the guiding role of the Chinese Charge d'Affaires Office in London in facilitating scientific and technological exchanges,and the technology investigations led by the Ministry of Foreign Trade in the name of trade.Additionally,the Sino-British scientific network extended to the international arena,allowing China to engage in nuclear-related global organizations and events.This study highlights the significant British influence on the early development of China's nuclear industry,revealing the extent of its British influence.It argues that China's urgent need for nuclear science and industrial advancement was a key driver of its scientific engagement withthe UK.展开更多
The concept of neuroimmune interactions has shown significant advancements over the years. Modern research has revealed many areas of connection between fields, which were previously viewed as distinct disciplines. Fo...The concept of neuroimmune interactions has shown significant advancements over the years. Modern research has revealed many areas of connection between fields, which were previously viewed as distinct disciplines. For example, the nervous system can sense changes in the external environment and convey these changes through molecules and mediators with receptors in the immune system to modulate immune responses. Neuromediators can act on different receptors in the same group of cells, producing antipodal effects. Identification of the anti-inflammatory role of glucocorticoids highlighted that the body functions properly in an integrated manner. These interactions and crosstalk are not unidirectional, as the immune system can also influence various aspects of the nervous system, such as synaptic plasticity and fever. Strict integration of neuro-immuno-endocrine circuits is indispensable for homeostasis. Understanding these circuits and molecules can lead to advances in the understanding of various immune diseases, which will offer promising therapeutic options.展开更多
By simplifying catalyst-product separation and reducing phosphorus waste,heterogeneous hydroformylation offers a more sustainable alternative to homogeneous processes.However,heterogeneous hydroformylation catalysts d...By simplifying catalyst-product separation and reducing phosphorus waste,heterogeneous hydroformylation offers a more sustainable alternative to homogeneous processes.However,heterogeneous hydroformylation catalysts developed thus far still suffer from the issues of much lower activity and metal leaching,which severely hinder their practical application.Here,we demonstrate that incorporating phosphorus(P)atoms into graphitic carbon nitride(PCN)supports facilitates charge transfer from Rh to the PCN support,thus largely enhancing electronic metal-support interactions(EMSIs).In the styrene hydroformylation reaction,the activity of Rh_(1)/PCN single-atom catalysts(SACs)with varying P contents exhibited a volcano-shaped relationship with P doping,where the Rh_(1)/PCN SAC with optimal P doping showed exceptional activity,approximately 5.8-and 3.3-fold greater than that of the Rh_(1)/g-C_(3)N_(4)SAC without P doping and the industrial homogeneous catalyst HRh(CO)(PPh_(3))_(3),respectively.In addition,the optimal Rh_(1)/PCN SAC catalyst also demonstrated largely enhanced multicycle stability without any visible metal aggregation owing to the increased EMSIs,which sharply differed from the severe metal aggregation of large nanoparticles on the Rh_(1)/g-C_(3)N_(4)SAC.Mechan-istic studies revealed that the enhanced catalytic performance could be attributed to electron-deficient Rh species,which reduced CO adsorption while simultaneously promoting alkene adsorption through increased EMSIs.These findings suggest that tuning EMSIs is an effective way to achieve SACs with high activity and durability.展开更多
Background:Triple-negative breast cancer(TNBC),characterized by its lack of traditional hormone receptors and HER2,presents a significant challenge in oncology due to its poor response to conventional therapies.Autoph...Background:Triple-negative breast cancer(TNBC),characterized by its lack of traditional hormone receptors and HER2,presents a significant challenge in oncology due to its poor response to conventional therapies.Autophagy is an important process for maintaining cellular homeostasis,and there are currently autophagy biomarkers that play an effective role in the clinical treatment of tumors.In contrast to targeting protein activity,intervention with proteinprotein interaction(PPI)can avoid unrelated crosstalk and regulate the autophagy process with minimal interference pathways.Methods:Here,we employed Naive Bayes,Decision Tree,and k-Nearest Neighbors to elucidate the complex PPI network associated with autophagy in TNBC,aiming to uncover novel therapeutic targets.Meanwhile,the candidate proteins interacting with Beclin 2 were initially screened in MDA-MB-231 cells using Beclin 2 as bait protein by immunoprecipitation-mass spectrometry assay,and the interaction relationship was verified by molecular docking and CO-IP experiments after intersection.Colony formation,cellular immunofluorescence,cell scratch and 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide(MTT)tests were used to predict the clinical therapeutic effects of manipulating candidate PPI.Results:By developing three PPI classification models and analyzing over 13,000 datasets,we identified 3733 previously unknown autophagy-related PPIs.Our network analysis revealed the central role of Beclin 2 in autophagy regulation,uncovering its interactions with 39 newly identified proteins.Notably,the CO-IP studies identified the substantial interaction between Beclin 2 and Ubiquilin 1,which was anticipated by our model and discovered in immunoprecipitation-mass spectrometry assay results.Subsequently,in vitro investigations showed that overexpressing Beclin 2 increased Ubiquilin 1,promoted autophagy-dependent cell death,and inhibited proliferation and metastasis in MDA-MB-231 cells.Conclusions:This study not only enhances our understanding of autophagy regulation in TNBC but also identifies the Beclin 2-Ubiquilin 1 axis as a promising target for precision therapy.These findings open new avenues for drug discovery and offer inspiration for more effective treatments for this aggressive cancer subtype.展开更多
Nuclear magnetic resonance(NMR)serves as a powerful tool for studying both the structure and dynamics of proteins.The NOE method,alongside residual dipolar;coupling,paramagnetic effects,J-coupling,and other related te...Nuclear magnetic resonance(NMR)serves as a powerful tool for studying both the structure and dynamics of proteins.The NOE method,alongside residual dipolar;coupling,paramagnetic effects,J-coupling,and other related techniques,has reached a level of maturity that allows for the determination of protein structures.Furthermore,NMR relaxation methods prove to be highly effective in characterizing protein dynamics across various timescales.The properties of protein systems are dictated by intra-and intermo-lecular interactions among atoms,which involve covalent bonds,hydrogen bonds(H-bonds),electrostatic interactions,and van der Waals forces.Multiple NMR approaches have been developed to measure noncovalent interactions,and this paper offers a concise overview of noncovalent interaction measurements using NMR,with a specific emphasis on the advancements accomplished in our laboratory.展开更多
Chemical communication in plant–microbiome and intra-microbiome interactions weaves a complex network,critically shaping ecosystem stability and agricultural productivity.This non-contact interaction is driven by sma...Chemical communication in plant–microbiome and intra-microbiome interactions weaves a complex network,critically shaping ecosystem stability and agricultural productivity.This non-contact interaction is driven by small-molecule signals that orchestrate crosstalk dynamics and beneficial association.Plants leverage these signals to distinguish between pathogens and beneficial microbes,dynamically modulate immune responses,and secrete exudates to recruit a beneficial microbiome,while microbes in turn influence plant nutrient acquisition and stress resilience.Such bidirectional chemical dialogues underpin nutrient cycling,co-evolution,microbiome assembly,and plant resistance.However,knowledge gaps persist regarding validating the key molecules involved in plant–microbe interactions.Interpreting chemical communication requires multi-omics integration to predict key information,genome editing and click chemistry to verify the function of biomolecules,and artificial intelligence(AI)models to improve resolution and accuracy.This review helps advance the understanding of chemical communication and provides theoretical support for agriculture to cope with food insecurity and climate challenges.展开更多
Cowl-induced incident Shock Wave/Boundary Layer Interactions (SWBLI) under the influence of gradual expansion waves are frequently observed in supersonic inlets. However, the analysis and prediction of interaction len...Cowl-induced incident Shock Wave/Boundary Layer Interactions (SWBLI) under the influence of gradual expansion waves are frequently observed in supersonic inlets. However, the analysis and prediction of interaction lengths have not been sufficiently investigated. First, this study presents a theoretical scaling analysis and validates it through wind tunnel experiments. It conducts detailed control volume analysis of mass conservation, considering the differences between inviscid and viscous cases. Then, three models for analysing interaction length under gradual expansion waves are derived. Related experiments using schlieren photography are conducted to validate the models in a Mach 2.73 flow. The interaction scales are captured at various relative distances between the shock impingement location and the expansion regions with wedge angles ranging from 12° to 15° and expansion angles of 9°, 12°, and 15°. Three trend lines are plotted based on different expansion angles to depict the relationship between normalised interaction length and normalised interaction strength metric. In addition, the relationship between the coefficients of the trend line and the expansion angles is introduced to predict the interaction length influenced by gradual expansion waves. Finally, the estimation of normalised interaction length is derived for various coefficients within a unified form.展开更多
Soil denitrification,anammox,and Feammox are key for nitrogen(N)removal in agriculture.Despite potassium(K)fertilizer enhancing N efficiency,their role in regulation of these processes is unclear.A soil column incubat...Soil denitrification,anammox,and Feammox are key for nitrogen(N)removal in agriculture.Despite potassium(K)fertilizer enhancing N efficiency,their role in regulation of these processes is unclear.A soil column incubation with 15N isotope tracingwas conducted to explore millimeter-scale interactions of N and K on these pathways in soil fertilization zones.After 28 days,individual applications of N and K reduced denitrification-nitrogen removal rate(DNRR),anammox-nitrogen removal rate(ANRR),and feammox-nitrogen removal rate(FNRR)compared to a non-fertilizer control.N fertilizer had a greater effect than K,likely due to the high consumption of dissolved organic carbon by N fertilizer or the increased soil organic matter decomposition by K fertilizer.Combing of N and K increased DNRR,ANRR and FNRR rates by 31%,3090%and 244%compared to single N,and by-53.7%,885%and 222%compared to single K.These effects diminished with depth and distance from fertilizer sites.The effects of N fertilizer on these N removal processes might be regulate abundance of key microbes(e.g.,Limnobacter and Clostridium)and key gene(nirK,hzsB,ACM and Geo)by providing N substrates,while K enhances N metabolism efficiency through enzyme activation,indicated by the downregulation of certain genes(hzsB,ACM and Geo)and a negative correlation with N removal by simultaneously increasing gene expression and enzyme activity.These findings provide insights into how N and K together enhance N removal,emphasizing their importance for optimizing this process.展开更多
Supramolecular materials,characterized by dynamic reversibility and responsiveness to environmental stimuli,have found widespread applications in numerous fields.Unlike traditional materials,supramolecular materials t...Supramolecular materials,characterized by dynamic reversibility and responsiveness to environmental stimuli,have found widespread applications in numerous fields.Unlike traditional materials,supramolecular materials that rely on non-covalent interactions can allow spontaneous reorganization and self-healing at room temperature.However,these materials typically exhibit low strength due to the weak bonding energies of non-covalent interactions.This study presents the development of a high-strength self-healing supramolecular material that combines multiple interactions including ionic bonding,hydrogen bonding,and coordination bonding.The material,formed by the aggregation of the negatively charged picolinate-grafted copolymer(PCM)with positively charged hyperbranched molecules(HP),is further enhanced by Eu^(3+)ion complexation.The resulting film exhibits a high modulus of 427 MPa,tensile strength of 10.5 MPa,and toughness of 14.7 MJ m^(−3).Meanwhile,the non-covalent interaction of this supramolecular material endows it with a self-healing efficiency of 92%within 24 h at room temperature,as well as multiple remolding properties.The incorporation of lanthanide ions also imparts tunable fluorescence.This study not only provides insights into the development of high-strength self-healing materials but also offers new possibilities for the functionalization of supramolecular materials.展开更多
基金supported by the National Key R&D Program of China(Grant No.2023YFA1406200)the National Natural Science Foundation of China(No.12274177 and 12304261)the China Postdoctoral Science Foundation(No.2024M751076)。
文摘Luminescent metal-organic frameworks(MOFs)have garnered significant attention due to their structural tunability and potential applications in solid-state lighting,bioimaging,sensing,anticounterfeiting,and other fields.Nevertheless,due to the tendency of1,4-benzenedicarboxylic acid(BDC)to rotate within the framework,MOFs composed of it exhibit significant non-radiative energy dissipation and thus impair the emissive properties.In this study,efficient luminescence of MIL-140A nanocrystals(NCs)with BDC rotors as ligands is achieved by pressure treatment strategy.Pressure treatment effectively modulates the pore structure of the framework,enhancing the interactions between the N,N-dimethylformamide vip molecules and the BDC ligands.The enhanced host-vip interaction contributes to the structural rigidity of the MOF,thereby suppressing the rotation-induced excited-state energy loss.As a result,the pressure-treated MIL-140A NCs displayed bright blue-light emission,with the photoluminescence quantum yield increasing from an initial 6.8%to 69.2%.This study developed an effective strategy to improve the luminescence performance of rotor ligand MOFs,offers a new avenue for the rational design and synthesis of MOFs with superior luminescent properties.
基金supported by the National Natural Science Foundation of China,Nos.82104560(to CL),U21A20400(to QW)the Natural Science Foundation of Beijing,No.7232279(to XW)the Project of Beijing University of Chinese Medicine,No.2022-JYB-JBZR-004(to XW)。
文摘The primary mechanism of secondary injury after cerebral ischemia may be the brain inflammation that emerges after an ischemic stroke,which promotes neuronal death and inhibits nerve tissue regeneration.As the first immune cells to be activated after an ischemic stroke,microglia play an important immunomodulatory role in the progression of the condition.After an ischemic stroke,peripheral blood immune cells(mainly T cells)are recruited to the central nervous system by chemokines secreted by immune cells in the brain,where they interact with central nervous system cells(mainly microglia)to trigger a secondary neuroimmune response.This review summarizes the interactions between T cells and microglia in the immune-inflammatory processes of ischemic stroke.We found that,during ischemic stroke,T cells and microglia demonstrate a more pronounced synergistic effect.Th1,Th17,and M1 microglia can co-secrete proinflammatory factors,such as interferon-γ,tumor necrosis factor-α,and interleukin-1β,to promote neuroinflammation and exacerbate brain injury.Th2,Treg,and M2 microglia jointly secrete anti-inflammatory factors,such as interleukin-4,interleukin-10,and transforming growth factor-β,to inhibit the progression of neuroinflammation,as well as growth factors such as brain-derived neurotrophic factor to promote nerve regeneration and repair brain injury.Immune interactions between microglia and T cells influence the direction of the subsequent neuroinflammation,which in turn determines the prognosis of ischemic stroke patients.Clinical trials have been conducted on the ways to modulate the interactions between T cells and microglia toward anti-inflammatory communication using the immunosuppressant fingolimod or overdosing with Treg cells to promote neural tissue repair and reduce the damage caused by ischemic stroke.However,such studies have been relatively infrequent,and clinical experience is still insufficient.In summary,in ischemic stroke,T cell subsets and activated microglia act synergistically to regulate inflammatory progression,mainly by secreting inflammatory factors.In the future,a key research direction for ischemic stroke treatment could be rooted in the enhancement of anti-inflammatory factor secretion by promoting the generation of Th2 and Treg cells,along with the activation of M2-type microglia.These approaches may alleviate neuroinflammation and facilitate the repair of neural tissues.
文摘Deficiency or restriction of Zn absorption in soils is one of the most common micronutrients deficient in cereal plants. To investigate critical micronutrient interaction in zinc deficiency and zinc sufficient in soil, a factorial experiment based on completely randomized design (CRD) with three replications was conducted in 2023. Six wheat cultivars with different Zn efficiency were used. The cultivars were grown under Zn deficiency and adequate conditions. Results showed that in Zn deficiency conditions, with increasing Zn concentration in the roots, Fe concentrations were increased too, while the Cu and Mn concentrations decreased. In the same condition and with increasing Zn concentration in shoots, the concentrations of Fe and Mn decreased, while Cu were increased. However, by increasing Zn concentration, Fe, Cu, and Mn concentrations were increased in Zn deficiency condition in grains, as well as Zn sufficient conditions. RST (root to shoot micronutrient translocation) comparison of cultivars showed that in lack of Zn, the ability of translocation of Zn, Fe, and Mn in Zn-inefficient cultivar from root to shoot was higher than inefficient cultivar. In the same conditions, the capability of Zn-inefficient cultivar in Cu translocation from root to shoot was lower than other cultivars. In general, it seems that in Zn deficiency conditions, there are antagonistic effects among Zn, Cu and Mn and synergistic effects between Zn and Fe in the root. Also, in Zn sufficient conditions, there were synergistic effects among all studies micronutrients which include Zn, Fe, Cu, and Mn.
基金supported by the National Natural Science Foundation of China(42277087,42130708,42471021,42277482,and 42361144876)the Natural Science Foundation of Guangdong Province(2024A1515012550)+3 种基金the Hainan Institute of National Park grant(KY-23ZK01)the Tsinghua Shenzhen International Graduate School Cross-disciplinary Research and Innovation Fund Research Plan(JC2022011)the Shenzhen Science and Technology Program(JCYJ20240813112106009 and ZDSYS20220606100806014)the Scientific Research Start-up Funds(QD2021030C)from Tsinghua Shenzhen International Graduate School。
文摘Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air pollution is crucial for mitigating climate change,improving air quality,and promoting the sustainable development of food systems.However,the literature lacks a comprehensive review of these interactions,particularly in the current phase of rapid development in the field.To address this gap,this study systematically reviews recent research on the impacts of climate change and air pollution on food systems,as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution.In addition,this study summarizes various strategies for mitigation and adaptation,including adjustments in agricultural practices and food supply chains.Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions.This review offers a critical overview of current research on the interactions among food systems,climate change,and air pollution and highlights future research directions to support the transition to sustainable food systems.
基金financial support from the Department of Science and Technology of Jilin Province(20240304104SF,20240304103SF)the Research and Innovation Fund of the Beihua University for the Graduate Student(Major Project 2023012)。
文摘Lithium-ion batteries are widely recognized as prime candidates for energy storage devices.Ethylene carbonate(EC)has become a critical component in conventional commercial electrolytes due to its exceptional film-forming properties and high dielectric constant.However,the elevated freezing point,high viscosity,and strong solvation energy of EC significantly hinder the transport rate of Li^(+)and the desolvation process at low temperatures.This leads to substantial capacity loss and even lithium plating on graphite anodes.Herein,we have developed an efficient electrolyte system specifically designed for lowtemperature conditions,which consists of 1.0 M lithium bis(fluorosulfonyl)imide(LiFSI)in isoxazole(IZ)with fluorobenzene(FB)as an uncoordinated solvent and fluoroethylene carbonate(FEC)as a filmforming co-solvent.This system effectively lowers the desolvation energy of Li^(+)through dipole-dipole interactions.The weak solvation capability allows more anions to enter the solvation sheath,promoting the formation of contact ion pairs(CIPs)and aggregates(AGGs)that enhance the transport rate of Li^(+)while maintaining high ionic conductivity across a broad temperature range.Moreover,the formation of inorganic-dominant interfacial phases on the graphite anode,induced by fluoroethylene carbonate,significantly enhances the kinetics of Li^(+)transport.At a low temperature of-20℃,this electrolyte system achieves an impressive reversible capacity of 200.9 mAh g^(-1)in graphite half-cell,which is nearly three times that observed with conventional EC-based electrolytes,demonstrating excellent stability throughout its operation.
基金supported by A*STAR under the“Nanosystems at the Edge”program(Grant No.A18A4b0055)Ministry of Education(MOE)under the research grant of R-263-000-F18-112/A-0009520-01-00+1 种基金National Research Foundation Singapore grant CRP28-2022-0038the Reimagine Re-search Scheme(RRSC)Project(Grant A-0009037-02-00&A0009037-03-00)at National University of Singapore.
文摘Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from the obstacles of low sensitivity,narrow bandwidth,and asymmetric Fano resonance perturbations.Here,we demonstrated an overcoupled resonator with a high plasmon-molecule coupling coefficient(μ)(OC-Hμresonator)by precisely controlling the radiation loss channel,the resonator-oscillator coupling channel,and the frequency detuning channel.We observed a strong dependence of the sensing performance on the coupling state,and demonstrated that OC-Hμresonator has excellent sensing properties of ultra-sensitive(7.25%nm^(−1)),ultra-broadband(3–10μm),and immune asymmetric Fano lineshapes.These characteristics represent a breakthrough in SEIRA technology and lay the foundation for specific recognition of biomolecules,trace detection,and protein secondary structure analysis using a single array(array size is 100×100μm^(2)).In addition,with the assistance of machine learning,mixture classification,concentration prediction and spectral reconstruction were achieved with the highest accuracy of 100%.Finally,we demonstrated the potential of OC-Hμresonator for SARS-CoV-2 detection.These findings will promote the wider application of SEIRA technology,while providing new ideas for other enhanced spectroscopy technologies,quantum photonics and studying light–matter interactions.
基金supported by grants from the National Natural Science Foundation of China(Grant No.:T2341008)Intelligent and Precise Research on TCM for Spleen and Stomach Diseases(20233930063).
文摘Drug development remains a critical issue in the field of biomedicine.With the rapid advancement of information technologies such as artificial intelligence(AI)and the advent of the big data era,AI-assisted drug development has become a new trend,particularly in predicting drug-target associations.To address the challenge of drug-target prediction,AI-driven models have emerged as powerful tools,offering innovative solutions by effectively extracting features from complex biological data,accurately modeling molecular interactions,and precisely predicting potential drug-target outcomes.Traditional machine learning(ML),network-based,and advanced deep learning architectures such as convolutional neural networks(CNNs),graph convolutional networks(GCNs),and transformers play a pivotal role.This review systematically compiles and evaluates AI algorithms for drug-and drug combination-target predictions,highlighting their theoretical frameworks,strengths,and limitations.CNNs effectively identify spatial patterns and molecular features critical for drug-target interactions.GCNs provide deep insights into molecular interactions via relational data,whereas transformers increase prediction accuracy by capturing complex dependencies within biological sequences.Network-based models offer a systematic perspective by integrating diverse data sources,and traditional ML efficiently handles large datasets to improve overall predictive accuracy.Collectively,these AI-driven methods are transforming drug-target predictions and advancing the development of personalized therapy.This review summarizes the application of AI in drug development,particularly in drug-target prediction,and offers recommendations on models and algorithms for researchers engaged in biomedical research.It also provides typical cases to better illustrate how AI can further accelerate development in the fields of biomedicine and drug discovery.
基金supported by the National Key R&D Program of China(Grant No.2019YFA0405300)the National Natural Science Foundation of China(Grant No.11972368)the Natural Science Foundation of Hunan Province(Grant No.2021JJ10045).
文摘The stability of supersonic inlets faces challenges due to various changes in flight conditions,and flow control methods that address shock wave/boundary layer interactions under only one set of conditions cannot meet developmental requirements.This paper proposes an adaptive bump control scheme and employs dynamic mesh technology for numerical simulation to investigate the unsteady control effects of adaptive bumps.The obtained results indicate that the use of moving bumps to control shock wave/boundary layer interactions is feasible.The adaptive control effects of five different bump speeds are evaluated.Within the range of bump speeds studied,the analysis of the flow field structure reveals the patterns of change in the separation zone area during the control process,as well as the relationship between the bump motion speed and the control effect on the separation zone.It is concluded that the moving bump endows the boundary layer with additional energy.
基金supported by the National Natural Science Foundation of China(Nos.82173746 and U23A20530)Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism(Shanghai Municipal Education Commission)。
文摘Accurate prediction of drug-target interactions(DTIs)plays a pivotal role in drug discovery,facilitating optimization of lead compounds,drug repurposing and elucidation of drug side effects.However,traditional DTI prediction methods are often limited by incomplete biological data and insufficient representation of protein features.In this study,we proposed KG-CNNDTI,a novel knowledge graph-enhanced framework for DTI prediction,which integrates heterogeneous biological information to improve model generalizability and predictive performance.The proposed model utilized protein embeddings derived from a biomedical knowledge graph via the Node2Vec algorithm,which were further enriched with contextualized sequence representations obtained from ProteinBERT.For compound representation,multiple molecular fingerprint schemes alongside the Uni-Mol pre-trained model were evaluated.The fused representations served as inputs to both classical machine learning models and a convolutional neural network-based predictor.Experimental evaluations across benchmark datasets demonstrated that KG-CNNDTI achieved superior performance compared to state-of-the-art methods,particularly in terms of Precision,Recall,F1-Score and area under the precision-recall curve(AUPR).Ablation analysis highlighted the substantial contribution of knowledge graph-derived features.Moreover,KG-CNNDTI was employed for virtual screening of natural products against Alzheimer's disease,resulting in 40 candidate compounds.5 were supported by literature evidence,among which 3 were further validated in vitro assays.
文摘This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The participants were a 17-year-old young lady with ASD and intellectual deficit, and a control participant: a preadolescent with ASD but no intellectual deficit (Asperger syndrome). The game is comprised of four phases: greetings, pairing, imitation, and closing. Field educators were involved, playing specific roles: visual or physical inciter. The use of a robot allows for catching the participants’ attention, playing the imitation game for a longer period of time than with a human partner, and preventing the game partner’s negative facial expressions resulting from tiredness, impatience, or boredom. The participants’ behavior was observed in terms of initial approach towards the robot, positioning relative to the robot in terms of distance and orientation, reactions to the robot’s voice or moves, signs of happiness, and imitation attempts. Results suggest a more and more natural approach towards the robot during the sessions, as well as a higher level of social interaction, based on the variations of the parameters listed above. We use these preliminary results to draw the next steps of our research work as well as identify further perspectives, with this aim in mind: improving social interactions with adolescents with ASD and intellectual deficit, allowing for better integration of these people into our societies.
基金supported by the fundamental research funds of Zhejiang Sci-Tech University(No.22212286-Y)the Natural Science Foundation of Zhejiang Province(No.LQ24B040003)。
文摘Aromatic nitro compounds present substantial health and environmental concerns due to their toxic nature and potential explosive properties.Consequently,the development of host–vip molecular recognition systems for these compounds serves a dual-purpose:enabling the fabrication of high-performance sensors for detection and guiding the design of efficient adsorbents for environmental remediation.This study investigated the host–vip recognition behavior of perethylated pillar[n]arenes toward two aromatic nitro molecules,1-chloro-2,4-dinitrobenzene and picric acid.Various techniques including^(1)H NMR,2D NOESY NMR,and UV-vis spectroscopy were employed to explore the binding behavior between pillararenes and aromatic nitro vips in solution.Moreover,valuable single crystal structures were obtained to elucidate the distinct solid-state assembly behaviors of these vips with different pillararenes.The assembled solid-state supramolecular structures observed encompassed a 1:1 host–vip inclusion complex,an external binding complex,and an exo-wall tessellation complex.Furthermore,based on the findings from these systems,a pillararene-based test paper was developed for efficient picric acid detection,and the removal of picric acid from solution was also achieved using pillararenes powder.This research provides novel insights into the development of diverse host–vip systems toward hazardous compounds,offering potential applications in environmental protection and explosive detection domains.
文摘This study investigates the establishment of scientific links between the People's Republic of China(PRC)and the United Kingdom(UK)in the mid-2Oth century,focusing on the early development of China's nuclear industry.Sino-British scientific interactions took place across multiple dimensions,involving various institutions and individuals.Around 1949,UK-trained Chinese nuclear scientists returned to China,bringing advanced technological knowledge and extensive practical experience.The PRC regarded the UK as a crucial gateway to overcoming the technological blockade imposed by the United States(and later the Soviet Union)and sought to establish scientific relations with the UK through semi-official and unofficial channels.Specifically,these connections manifested in the interactions between the Chinese Academy of Sciences(CAS)and the Royal Society of London,the guiding role of the Chinese Charge d'Affaires Office in London in facilitating scientific and technological exchanges,and the technology investigations led by the Ministry of Foreign Trade in the name of trade.Additionally,the Sino-British scientific network extended to the international arena,allowing China to engage in nuclear-related global organizations and events.This study highlights the significant British influence on the early development of China's nuclear industry,revealing the extent of its British influence.It argues that China's urgent need for nuclear science and industrial advancement was a key driver of its scientific engagement withthe UK.
文摘The concept of neuroimmune interactions has shown significant advancements over the years. Modern research has revealed many areas of connection between fields, which were previously viewed as distinct disciplines. For example, the nervous system can sense changes in the external environment and convey these changes through molecules and mediators with receptors in the immune system to modulate immune responses. Neuromediators can act on different receptors in the same group of cells, producing antipodal effects. Identification of the anti-inflammatory role of glucocorticoids highlighted that the body functions properly in an integrated manner. These interactions and crosstalk are not unidirectional, as the immune system can also influence various aspects of the nervous system, such as synaptic plasticity and fever. Strict integration of neuro-immuno-endocrine circuits is indispensable for homeostasis. Understanding these circuits and molecules can lead to advances in the understanding of various immune diseases, which will offer promising therapeutic options.
基金supported by the Petrochemical Research Institute Foundation(21-CB-09-01)the National Natural Science Foundation of China(22302186,22025205)+1 种基金the China Postdoctoral Science Foundation(2022M713030,2023T160618)the Fundamental Research Funds for the Central Universities(WK2060000058,WK2060000038).
文摘By simplifying catalyst-product separation and reducing phosphorus waste,heterogeneous hydroformylation offers a more sustainable alternative to homogeneous processes.However,heterogeneous hydroformylation catalysts developed thus far still suffer from the issues of much lower activity and metal leaching,which severely hinder their practical application.Here,we demonstrate that incorporating phosphorus(P)atoms into graphitic carbon nitride(PCN)supports facilitates charge transfer from Rh to the PCN support,thus largely enhancing electronic metal-support interactions(EMSIs).In the styrene hydroformylation reaction,the activity of Rh_(1)/PCN single-atom catalysts(SACs)with varying P contents exhibited a volcano-shaped relationship with P doping,where the Rh_(1)/PCN SAC with optimal P doping showed exceptional activity,approximately 5.8-and 3.3-fold greater than that of the Rh_(1)/g-C_(3)N_(4)SAC without P doping and the industrial homogeneous catalyst HRh(CO)(PPh_(3))_(3),respectively.In addition,the optimal Rh_(1)/PCN SAC catalyst also demonstrated largely enhanced multicycle stability without any visible metal aggregation owing to the increased EMSIs,which sharply differed from the severe metal aggregation of large nanoparticles on the Rh_(1)/g-C_(3)N_(4)SAC.Mechan-istic studies revealed that the enhanced catalytic performance could be attributed to electron-deficient Rh species,which reduced CO adsorption while simultaneously promoting alkene adsorption through increased EMSIs.These findings suggest that tuning EMSIs is an effective way to achieve SACs with high activity and durability.
基金the National Natural Science Foundation of China(Nos.22307009,82374155,82073997,82104376)the Sichuan Science and Technology Program(Nos.2023NSFSC1108,2024NSFTD0023)+1 种基金the Postdoctoral Research Project of Sichuan Provincethe Xinglin Scholar Research Promotion Project of Chengdu University of TCM.
文摘Background:Triple-negative breast cancer(TNBC),characterized by its lack of traditional hormone receptors and HER2,presents a significant challenge in oncology due to its poor response to conventional therapies.Autophagy is an important process for maintaining cellular homeostasis,and there are currently autophagy biomarkers that play an effective role in the clinical treatment of tumors.In contrast to targeting protein activity,intervention with proteinprotein interaction(PPI)can avoid unrelated crosstalk and regulate the autophagy process with minimal interference pathways.Methods:Here,we employed Naive Bayes,Decision Tree,and k-Nearest Neighbors to elucidate the complex PPI network associated with autophagy in TNBC,aiming to uncover novel therapeutic targets.Meanwhile,the candidate proteins interacting with Beclin 2 were initially screened in MDA-MB-231 cells using Beclin 2 as bait protein by immunoprecipitation-mass spectrometry assay,and the interaction relationship was verified by molecular docking and CO-IP experiments after intersection.Colony formation,cellular immunofluorescence,cell scratch and 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide(MTT)tests were used to predict the clinical therapeutic effects of manipulating candidate PPI.Results:By developing three PPI classification models and analyzing over 13,000 datasets,we identified 3733 previously unknown autophagy-related PPIs.Our network analysis revealed the central role of Beclin 2 in autophagy regulation,uncovering its interactions with 39 newly identified proteins.Notably,the CO-IP studies identified the substantial interaction between Beclin 2 and Ubiquilin 1,which was anticipated by our model and discovered in immunoprecipitation-mass spectrometry assay results.Subsequently,in vitro investigations showed that overexpressing Beclin 2 increased Ubiquilin 1,promoted autophagy-dependent cell death,and inhibited proliferation and metastasis in MDA-MB-231 cells.Conclusions:This study not only enhances our understanding of autophagy regulation in TNBC but also identifies the Beclin 2-Ubiquilin 1 axis as a promising target for precision therapy.These findings open new avenues for drug discovery and offer inspiration for more effective treatments for this aggressive cancer subtype.
文摘Nuclear magnetic resonance(NMR)serves as a powerful tool for studying both the structure and dynamics of proteins.The NOE method,alongside residual dipolar;coupling,paramagnetic effects,J-coupling,and other related techniques,has reached a level of maturity that allows for the determination of protein structures.Furthermore,NMR relaxation methods prove to be highly effective in characterizing protein dynamics across various timescales.The properties of protein systems are dictated by intra-and intermo-lecular interactions among atoms,which involve covalent bonds,hydrogen bonds(H-bonds),electrostatic interactions,and van der Waals forces.Multiple NMR approaches have been developed to measure noncovalent interactions,and this paper offers a concise overview of noncovalent interaction measurements using NMR,with a specific emphasis on the advancements accomplished in our laboratory.
基金supported by the National Key R&D Program of China(No.2025YFE0104500)the Zhejiang Provincial Natural Science Foundation of China(No.LD25C140002),the Natural Science Foundation of Hangzhou(No.2024SZRZDC 130001)+1 种基金the National Natural Science Foundation of China(Nos.U21A20219 and 32122074)the Zhejiang University Global Partnership Fund,China.
文摘Chemical communication in plant–microbiome and intra-microbiome interactions weaves a complex network,critically shaping ecosystem stability and agricultural productivity.This non-contact interaction is driven by small-molecule signals that orchestrate crosstalk dynamics and beneficial association.Plants leverage these signals to distinguish between pathogens and beneficial microbes,dynamically modulate immune responses,and secrete exudates to recruit a beneficial microbiome,while microbes in turn influence plant nutrient acquisition and stress resilience.Such bidirectional chemical dialogues underpin nutrient cycling,co-evolution,microbiome assembly,and plant resistance.However,knowledge gaps persist regarding validating the key molecules involved in plant–microbe interactions.Interpreting chemical communication requires multi-omics integration to predict key information,genome editing and click chemistry to verify the function of biomolecules,and artificial intelligence(AI)models to improve resolution and accuracy.This review helps advance the understanding of chemical communication and provides theoretical support for agriculture to cope with food insecurity and climate challenges.
基金co-supported by the National Natural Science Foundation of China (No. 12172175)the National Science and Technology Major Project, China (No. J2019-II0014-0035)the Science Center for Gas Turbine Project, China (Nos. P2022-C-II-002-001, P2022-A-II-002-001)
文摘Cowl-induced incident Shock Wave/Boundary Layer Interactions (SWBLI) under the influence of gradual expansion waves are frequently observed in supersonic inlets. However, the analysis and prediction of interaction lengths have not been sufficiently investigated. First, this study presents a theoretical scaling analysis and validates it through wind tunnel experiments. It conducts detailed control volume analysis of mass conservation, considering the differences between inviscid and viscous cases. Then, three models for analysing interaction length under gradual expansion waves are derived. Related experiments using schlieren photography are conducted to validate the models in a Mach 2.73 flow. The interaction scales are captured at various relative distances between the shock impingement location and the expansion regions with wedge angles ranging from 12° to 15° and expansion angles of 9°, 12°, and 15°. Three trend lines are plotted based on different expansion angles to depict the relationship between normalised interaction length and normalised interaction strength metric. In addition, the relationship between the coefficients of the trend line and the expansion angles is introduced to predict the interaction length influenced by gradual expansion waves. Finally, the estimation of normalised interaction length is derived for various coefficients within a unified form.
基金supported by the National Natural Science Foundation of China(Nos.32271726 and 32171648)the Natural Science Foundation of Hubei Province of China(No.2022CFB030)。
文摘Soil denitrification,anammox,and Feammox are key for nitrogen(N)removal in agriculture.Despite potassium(K)fertilizer enhancing N efficiency,their role in regulation of these processes is unclear.A soil column incubation with 15N isotope tracingwas conducted to explore millimeter-scale interactions of N and K on these pathways in soil fertilization zones.After 28 days,individual applications of N and K reduced denitrification-nitrogen removal rate(DNRR),anammox-nitrogen removal rate(ANRR),and feammox-nitrogen removal rate(FNRR)compared to a non-fertilizer control.N fertilizer had a greater effect than K,likely due to the high consumption of dissolved organic carbon by N fertilizer or the increased soil organic matter decomposition by K fertilizer.Combing of N and K increased DNRR,ANRR and FNRR rates by 31%,3090%and 244%compared to single N,and by-53.7%,885%and 222%compared to single K.These effects diminished with depth and distance from fertilizer sites.The effects of N fertilizer on these N removal processes might be regulate abundance of key microbes(e.g.,Limnobacter and Clostridium)and key gene(nirK,hzsB,ACM and Geo)by providing N substrates,while K enhances N metabolism efficiency through enzyme activation,indicated by the downregulation of certain genes(hzsB,ACM and Geo)and a negative correlation with N removal by simultaneously increasing gene expression and enzyme activity.These findings provide insights into how N and K together enhance N removal,emphasizing their importance for optimizing this process.
基金supported by Zhejiang Provincial Natural Science Foundation of China under(LD22A020002)National Natural Science Foundation of China(52473116,22322508)+1 种基金International Cooperation Project of Ningbo City(2023H019)the Sino-German mobility program(M-0424).
文摘Supramolecular materials,characterized by dynamic reversibility and responsiveness to environmental stimuli,have found widespread applications in numerous fields.Unlike traditional materials,supramolecular materials that rely on non-covalent interactions can allow spontaneous reorganization and self-healing at room temperature.However,these materials typically exhibit low strength due to the weak bonding energies of non-covalent interactions.This study presents the development of a high-strength self-healing supramolecular material that combines multiple interactions including ionic bonding,hydrogen bonding,and coordination bonding.The material,formed by the aggregation of the negatively charged picolinate-grafted copolymer(PCM)with positively charged hyperbranched molecules(HP),is further enhanced by Eu^(3+)ion complexation.The resulting film exhibits a high modulus of 427 MPa,tensile strength of 10.5 MPa,and toughness of 14.7 MJ m^(−3).Meanwhile,the non-covalent interaction of this supramolecular material endows it with a self-healing efficiency of 92%within 24 h at room temperature,as well as multiple remolding properties.The incorporation of lanthanide ions also imparts tunable fluorescence.This study not only provides insights into the development of high-strength self-healing materials but also offers new possibilities for the functionalization of supramolecular materials.
