Biological Interaction and Imaging of Ultrasmall Gold Nanoparticles

Ultrasmall gold nanoparticles(AuNPs)typically includes atomically precise gold nanoclusters(AuNCs)and AuNPs with a core size below 3 nm.Serving as a bridge between small molecules and traditional inorganic nanoparticles,the ultrasmall AuNPs show the unique advantages of both small molecules(e.g.,rapid distribution,renal clearance,low non-specific organ accumulation)and nanoparticles(e.g.,long blood circulation and enhanced permeability and retention effect).The emergence of ultrasmall AuNPs creates significant opportunities to address many challenges in the health field including disease diagnosis,monitoring and treatment.Since the nano–bio interaction dictates the overall biological applications of the ultrasmall AuNPs,this review elucidates the recent advances in the biological interactions and imaging of ultrasmall AuNPs.We begin with the introduction of the factors that influence the cellular interactions of ultrasmall AuNPs.We then discuss the organ interactions,especially focus on the interactions of the liver and kidneys.We further present the recent advances in the tumor interactions of ultrasmall AuNPs.In addition,the imaging performance of the ultrasmall AuNPs is summarized and discussed.Finally,we summarize this review and provide some perspective on the future research direction of the ultrasmall AuNPs,aiming to accelerate their clinical translation.

Ecological network analysis reveals complex responses of tree species life stage interactions to stand variables

Tree interactions are essential for the structure,dynamics,and function of forest ecosystems,but variations in the architecture of life-stage interaction networks(LSINs)across forests is unclear.Here,we constructed 16 LSINs in the mountainous forests of northwest Hebei,China based on crown overlap from four mixed forests with two dominant tree species.Our results show that LSINs decrease the complexity of stand densities and basal areas due to the interaction cluster differentiation.In addition,we found that mature trees and saplings play different roles,the first acting as“hub”life stages with high connectivity and the second,as“bridges”controlling information flow with high centrality.Across the forests,life stages with higher importance showed better parameter stability within LSINs.These results reveal that the structure of tree interactions among life stages is highly related to stand variables.Our efforts contribute to the understanding of LSIN complexity and provide a basis for further research on tree interactions in complex forest communities.

Study of the Relationship Between New Ionic Interaction Parameters and Salt Solubility in Electrolyte Solutions Based on Molecular Dynamics Simulation

Studying the relationship between ionic interactions and salt solubility in seawater has implications for seawater desalination and mineral extraction.In this paper,a new method of expressing ion-to-ion interaction is proposed by using molecular dynamics simulation,and the relationship between ion-to-ion interaction and salt solubility in a simulated seawater water-salt system is investigated.By analyzing the variation of distance and contact time between ions in an electrolyte solution,from both spatial and temporal perspectives,new parameters were proposed to describe the interaction between ions:interaction distance(ID),and interaction time ratio(ITR).The best correlation between characteristic time ratio and solubility was found for a molar ratio of salt-to-water of 10:100 with a correlation coefficient of 0.96.For the same salt,a positive correlation was found between CTR and the molar ratio of salt and water.For type 1-1,type 2-1,type 1-2,and type 2-2 salts,the correlation coefficients between CTR and solubility were 0.93,0.96,0.92,and 0.98 for a salt-to-water molar ratio of 10:100,respectively.The solubility of multiple salts was predicted by simulations and compared with experimental values,yielding an average relative deviation of 12.4%.The new ion-interaction parameters offer significant advantages in describing strongly correlated and strongly hydrated electrolyte solutions.

Numerical investigation of the effects of soil-structure and granular material-structure interaction on the seismic response of a flat-bottom reinforced concrete silo

In this work,a numerical study of the effects of soil-structure interaction(SSI)and granular material-structure interaction(GSI)on the nonlinear response and seismic capacity of flat-bottomed storage silos is conducted.A series of incremental dynamic analyses(IDA)are performed on a case of large reinforced concrete silo using 10 seismic recordings.The IDA results are given by two average IDA capacity curves,which are represented,as well as the seismic capacity of the studied structure,with and without a consideration of the SSI while accounting for the effect of GSI.These curves are used to quantify and evaluate the damage of the studied silo by utilizing two damage indices,one based on dissipated energy and the other on displacement and dissipated energy.The cumulative energy dissipation curves obtained by the average IDA capacity curves with and without SSI are presented as a function of the base shear,and these curves allow one to obtain the two critical points and the different limit states of the structure.It is observed that the SSI and GSI significantly influence the seismic response and capacity of the studied structure,particularly at higher levels of PGA.Moreover,the effect of the SSI reduces the damage index of the studied structure by 4%.

CNKSR2 interactome analysis indicates its association with the centrosome/microtubule system

The protein connector enhancer of kinase suppressor of Ras 2(CNKSR2),present in both the postsynaptic density and cytoplasm of neurons,is a scaffolding protein with several protein-binding domains.Variants of the CNKSR2 gene have been implicated in neurodevelopmental disorders,particularly intellectual disability,although the precise mechanism involved has not yet been fully understood.Research has demonstrated that CNKSR2 plays a role in facilitating the localization of postsynaptic density protein complexes to the membrane,thereby influencing synaptic signaling and the morphogenesis of dendritic spines.However,the function of CNKSR2 in the cytoplasm remains to be elucidated.In this study,we used immunoprecipitation and high-resolution liquid chromatography-mass spectrometry to identify the interactors of CNKSR2.Through a combination of bioinformatic analysis and cytological experiments,we found that the CNKSR2 interactors were significantly enriched in the proteome of the centrosome.We also showed that CNKSR2 interacted with the microtubule protein DYNC1H1 and with the centrosome marker CEP290.Subsequent colocalization analysis confirmed the centrosomal localization of CNKSR2.When we downregulated CNKSR2 expression in mouse neuroblastoma cells(Neuro 2A),we observed significant changes in the expression of numerous centrosomal genes.This manipulation also affected centrosome-related functions,including cell size and shape,cell proliferation,and motility.Furthermore,we found that CNKSR2 interactors were highly enriched in de novo variants associated with intellectual disability and autism spectrum disorder.Our findings establish a connection between CNKSR2 and the centrosome,and offer new insights into the underlying mechanisms of neurodevelopmental disorders.

Hybrid Multi-Infeed Interaction Factor Calculation Method Considering Voltage Regulation Control Characteristics of Voltage Source Converter

Voltage source converter based high voltage direct current(VSC-HVDC)can participate in voltage regulation by flexible control to help maintain the voltage stability of the power grid.In order to quantitatively evaluate its influence on the voltage interaction between VSC-HVDC and line commutated converter based high voltage direct current(LCC-HVDC),this paper proposes a hybrid multi-infeed interaction factor(HMIIF)calculation method considering the voltage regulation control characteristics of VSC-HVDC.Firstly,for a hybrid multi-infeed high voltage direct current system,an additional equivalent operating admittance matrix is constructed to characterize HVDC equipment characteristics under small disturbance.Secondly,based on the characteristic curve between the reactive power and the voltage of a certain VSC-HVDC project,the additional equivalent operating admittance of VSC-HVDC is derived.The additional equivalent operating admittance matrix calculation method is proposed.Thirdly,the equivalent bus impedance matrix is obtained by modifying the alternating current(AC)system admittance matrix with the additional equivalent operating admittance matrix.On this basis,the HMIIF calculation method based on the equivalent bus impedance ratio is proposed.Finally,the effectiveness of the proposed method is verified in a hybrid dual-infeed high voltage direct current system constructed in Power Systems Computer Aided Design(PSCAD),and the influence of voltage regulation control on HMIIF is analyzed.

Spastin and alsin protein interactome analyses begin to reveal key canonical pathways and suggest novel druggable targets

Developing effective and long-term treatment strategies for rare and complex neurodegenerative diseases is challenging. One of the major roadblocks is the extensive heterogeneity among patients. This hinders understanding the underlying disease-causing mechanisms and building solutions that have implications for a broad spectrum of patients. One potential solution is to develop personalized medicine approaches based on strategies that target the most prevalent cellular events that are perturbed in patients. Especially in patients with a known genetic mutation, it may be possible to understand how these mutations contribute to problems that lead to neurodegeneration. Protein–protein interaction analyses offer great advantages for revealing how proteins interact, which cellular events are primarily involved in these interactions, and how they become affected when key genes are mutated in patients. This line of investigation also suggests novel druggable targets for patients with different mutations. Here, we focus on alsin and spastin, two proteins that are identified as “causative” for amyotrophic lateral sclerosis and hereditary spastic paraplegia, respectively, when mutated. Our review analyzes the protein interactome for alsin and spastin, the canonical pathways that are primarily important for each protein domain, as well as compounds that are either Food and Drug Administration–approved or are in active clinical trials concerning the affected cellular pathways. This line of research begins to pave the way for personalized medicine approaches that are desperately needed for rare neurodegenerative diseases that are complex and heterogeneous.

An analysis of the interaction mechanism between the social history of medicine research and health communication from the perspective of mass communication

The mass communication model and interactive ritual chain theory,which serve as communication paradigms in the new media era,facilitate and enhance the synergy between the fields of social history of medicine and health communication.This study employs a comprehensive framework based on the five elements of the mass communication model:information source,communication subject,communication object,message content,and post-communication feedback.Additionally,it incorporates the interactive ritual chain theory to examine the evolving dynamics and developmental trajectory of research in the social history of medicine during the new media era.Conclusively,this paper acknowledges the existing interaction gaps in the interaction between health communication and the social history of medicine research while outlining the challenges for fostering collaboration and proposing strategic optimizations for effective integration.

Schisming as an Interactional Resource for Learning at the Frontiers of Work and Vocational Training-A Secondary Publication

This paper examines the sorts of interactional competencies and institutional demands required from students as they engage in complex forms of participation combining work and training purposes.It focuses on a series of empirical cases,recorded through video data and analyzed from a conversation analytic perspective,in which mentors make the decision to intervene during work sessions moderated by students.Such interventions do not interrupt the student’s activity and lead to the emergence of two distinct but not impermeable interactional spaces.This complex participation framework,known as“schisming,”contributes to overcoming practical issues within multiparty settings.Our study shows how schisming constitutes a particular sequential phenomenon where participants reorganize the interaction and co-construct a social and cognitive interactional space,thus enabling a shared understanding of the specific training context.Empirical data from the practical training of medical radiographers are used to illustrate how schisming may contribute to learning in the conditions of guided practice.

Machine learning with active pharmaceutical ingredient/polymer interaction mechanism:Prediction for complex phase behaviors of pharmaceuticals and formulations

The high throughput prediction of the thermodynamic phase behavior of active pharmaceutical ingredients(APIs)with pharmaceutically relevant excipients remains a major scientific challenge in the screening of pharmaceutical formulations.In this work,a developed machine-learning model efficiently predicts the solubility of APIs in polymers by learning the phase equilibrium principle and using a few molecular descriptors.Under the few-shot learning framework,thermodynamic theory(perturbed-chain statistical associating fluid theory)was used for data augmentation,and computational chemistry was applied for molecular descriptors'screening.The results showed that the developed machine-learning model can predict the API-polymer phase diagram accurately,broaden the solubility data of APIs in polymers,and reproduce the relationship between API solubility and the interaction mechanisms between API and polymer successfully,which provided efficient guidance for the development of pharmaceutical formulations.

Dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates

Interactive holography offers unmatched levels of immersion and user engagement in the field of future display.Despite of the substantial progress has been made in dynamic meta-holography,the realization of real-time,highly smooth interactive holography remains a significant challenge due to the computational and display frame rate limitations.In this study,we introduced a dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates.To our knowledge,this is the first reported practical dynamic interactive metasurface holographic system.We spa-tially divided the metasurface device into multiple distinct channels,each projecting a reconstructed sub-pattern.The switching states of these channels were mapped to bitwise operations on a set of bit values,which avoids complex holo-gram computations,enabling an ultra-high computational frame rate.Our approach achieves a computational frame rate of 800 kHz and a display frame rate of 23 kHz on a low-power Raspberry Pi computational platform.According to this methodology,we demonstrated an interactive dynamic holographic Tetris game system that allows interactive gameplay,color display,and on-the-fly hologram creation.Our technology presents an inspiration for advanced dynamic meta-holography,which is promising for a broad range of applications including advanced human-computer interaction,real-time 3D visualization,and next-generation virtual and augmented reality systems.

Strong metal–support interaction boosts the electrocatalytic hydrogen evolution capability of Ru nanoparticles supported on titanium nitride

Ruthenium(Ru)has been regarded as one of the most promising alternatives to substitute Pt for catalyzing alkaline hydrogen evolution reaction(HER),owing to its inherent high activity and being the cheapest platinum-group metal.Herein,based on the idea of strong metal–support interaction(SMSI)regulation,Ru/TiN catalysts with different degrees of TiN overlayer over Ru nanoparticles were fabricated,which were applied to the alkaline electrolytic water.Characterizations reveal that the TiN overlayer would gradually encapsulate the Ru nanoparticles and induce more electron transfer from Ru nanoparticles to TiN support by the Ru–N–Ti bond as the SMSI degree increased.Further study shows that the exposed Ru–TiN interfaces greatly promote the H_(2) desorption capacity.Thus,the Ru/TiN-300 with a moderate SMSI degree exhibits excellent HER performance,with an overpotential of 38 mV at 10 mA cm^(−2).Also,due to the encapsulation role of TiN overlayer on Ru nanoparticles,it displays super long-term stability with a very slight potential change after 24 h.This study provides a deep insight into the influence of the SMSI effect between Ru and TiN on HER and offers a novel approach for preparing efficient and stable HER electrocatalysts through SMSI engineering.

Electrostatic Interaction-directed Construction of Hierarchical Nanostructured Carbon Composite with Dual Electrical Conductive Networks for Zinc-ion Hybrid Capacitors with Ultrastability

Metal-organic framework(MOF)-derived carbon composites have been considered as the promising materials for energy storage.However,the construction of MOF-based composites with highly controllable mode via the liquid-liquid synthesis method has a great challenge because of the simultaneous heterogeneous nucleation on substrates and the self-nucleation of individual MOF nanocrystals in the liquid phase.Herein,we report a bidirectional electrostatic generated self-assembly strategy to achieve the precisely controlled coatings of single-layer nanoscale MOFs on a range of substrates,including carbon nanotubes(CNTs),graphene oxide(GO),MXene,layered double hydroxides(LDHs),MOFs,and SiO_(2).The obtained MOF-based nanostructured carbon composite exhibits the hierarchical porosity(V_(meso)/V_(micro)∶2.4),ultrahigh N content of 12.4 at.%and"dual electrical conductive networks."The assembled aqueous zinc-ion hybrid capacitor(ZIC)with the prepared nanocarbon composite as a cathode shows a high specific capacitance of 236 F g^(-1)at 0.5 A g^(-1),great rate performance of 98 F g^(-1)at 100 A g^(-1),and especially,an ultralong cycling stability up to 230000 cycles with the capacitance retention of 90.1%.This work develops a repeatable and general method for the controlled construction of MOF coatings on various functional substrates and further fabricates carbon composites for ZICs with ultrastability.

ST-Map:an Interactive Map for Discovering Spatial and Temporal Patterns in Bibliographic Data

Getting insight into the spatiotemporal distribution patterns of knowledge innovation is receiving increasing attention from policymakers and economic research organizations.Many studies use bibliometric data to analyze the popularity of certain research topics,well-adopted methodologies,influential authors,and the interrelationships among research disciplines.However,the visual exploration of the patterns of research topics with an emphasis on their spatial and temporal distribution remains challenging.This study combined a Space-Time Cube(STC)and a 3D glyph to represent the complex multivariate bibliographic data.We further implemented a visual design by developing an interactive interface.The effectiveness,understandability,and engagement of ST-Map are evaluated by seven experts in geovisualization.The results suggest that it is promising to use three-dimensional visualization to show the overview and on-demand details on a single screen.

Probing the interaction between asphaltene-wax and its effects on the crystallization behavior of waxes in heavy oil via molecular dynamics simulation

High content of asphaltenes and waxes leads to the high pour point and the poor flowability of heavy oil,which is adverse to its efficient development and its transportation in pipe.Understanding the interaction mechanism between asphaltene-wax is crucial to solve these problems,but it is still unclear.In this paper,molecular dynamics simulation was used to investigate the interaction between asphaltenewax and its effects on the crystallization behavior of waxes in heavy oil.Results show that molecules in pure wax are arranged in a paralleled geometry.But wax molecules in heavy oil,which are close to the surface of asphaltene aggregates,are bent and arranged irregularly.When the mass fraction of asphaltenes in asphaltene-wax system(ω_(asp))is 0-25 wt%,the attraction among wax molecules decreases and the bend degree of wax molecules increases with the increase ofω_(asp).Theω_(asp)increases from 0 to 25 wt%,and the attraction between asphaltene-wax is stronger than that among waxes.This causes that the wax precipitation point changes from 353 to 333 K.While theω_(asp)increases to 50 wt%,wax molecules are more dispersed owing to the steric hindrance of asphaltene aggregates,and the interaction among wax molecules transforms from attraction to repulsion.It causes that the ordered crystal structure of waxes can't be formed at normal temperature.Simultaneously,the asphaltene,with the higher molecular weight or the more hetero atoms,has more obvious inhibition to the formation of wax crystals.Besides,resins also have an obvious inhibition on the wax crystal due to the formation of asphalteneresin aggregates with a larger radius.Our results reveal the interaction mechanism between asphaltene-wax,and provide useful guidelines for the development of heavy oil.

Dynamical nonlinear excitations induced by interaction quench in a two-dimensional box-trapped Bose-Einstein condensate

Manipulating nonlinear excitations,including solitons and vortices,is an essential topic in quantum many-body physics.A new progress in this direction is a protocol proposed in[Phys.Rev.Res.2043256(2020)]to produce dark solitons in a one-dimensional atomic Bose–Einstein condensate(BEC)by quenching inter-atomic interaction.Motivated by this work,we generalize the protocol to a two-dimensional BEC and investigate the generic scenario of its post-quench dynamics.For an isotropic disk trap with a hard-wall boundary,we find that successive inward-moving ring dark solitons(RDSs)can be induced from the edge,and the number of RDSs can be controlled by tuning the ratio of the after-and before-quench interaction strength across different critical values.The role of the quench played on the profiles of the density,phase,and sound velocity is also investigated.Due to the snake instability,the RDSs then become vortex–antivortex pairs with peculiar dynamics managed by the initial density and the after-quench interaction.By tuning the geometry of the box traps,demonstrated as polygonal ones,more subtle dynamics of solitons and vortices are enabled.Our proposed protocol and the discovered rich dynamical effects on nonlinear excitations can be realized in near future cold-atom experiments.

Molecular dynamics simulations on the interactions between nucleic acids and a phospholipid bilayer

Recently,lipid nanoparticles(LNPs)have been extensively investigated as non-viral carriers of nucleic acid vaccines due to their high transport efficiency,safety,and straightforward production and scalability.However,the molecular mechanism underlying the interactions between nucleic acids and phospholipid bilayers within LNPs remains elusive.In this study,we employed the all-atom molecular dynamics simulation to investigate the interactions between single-stranded nucleic acids and a phospholipid bilayer.Our findings revealed that hydrophilic bases,specifically G in single-stranded RNA(ssRNA)and single-stranded DNA(ssDNA),displayed a higher propensity to form hydrogen bonds with phospholipid head groups.Notably,ssRNA exhibited stronger binding energy than ssDNA.Furthermore,divalent ions,particularly Ca2+,facilitated the binding of ssRNA to phospholipids due to their higher binding energy and lower dissociation rate from phospholipids.Overall,our study provides valuable insights into the molecular mechanisms underlying nucleic acidphospholipid interactions,with potential implications for the nucleic acids in biotherapies,particularly in the context of lipid carriers.

Electrochemistry and DFT study of galvanic interaction on the surface of monoclinic pyrrhotite(001)and galena(100)

The electrochemical interaction between galena and monoclinic pyrrhotite was investigated to examine its impact on the physical and chemical properties of the mineral micro-surface.This investigation employed techniques such as electrochemistry,metal ion stripping,X-ray photoelectron spectroscopy,and quantum chemistry.The electrochemical test results demonstrate that the galena surface in the electro-couple system exhibits a lower electrostatic potential and higher electrochemical activity compared to the monoclinic pyrrhotite surface,rendering it more susceptible to oxidation dissolution.Monoclinic pyrrhotite significantly amplifies the corrosion rate of the galena surface.Mulliken charge population calculations indicate that electrons are consistently transferred from galena to monoclinic pyrrhotite,with the number of electron transfers on the mineral surface increasing as the interaction distance decreases.The analysis of state density revealed a shift in the surface state density of galena towards lower energy levels,resulting in decreased reactivity and increased difficulty for the reagent to adsorb onto the mineral surface.Conversely,monoclinic pyrrhotite exhibited an opposite trend.The X-ray photoelectron spectroscopy(XPS)test results indicate that galvanic interaction leads to the formation of hydrophilic substances,PbS_(x)O_(y) and Pb(OH)_(2),on the surface of galena.Additionally,the surface of monoclinic pyrrhotite not only adsorbs Pb^(2+)but also undergoes S^(0) formation,thereby augmenting its hydrophobic nature.

Interatomic Interaction Models for Magnetic Materials:Recent Advances

Atomistic modeling is a widely employed theoretical method of computational materials science.It has found particular utility in the study of magnetic materials.Initially,magnetic empirical interatomic potentials or spinpolarized density functional theory(DFT)served as the primary models for describing interatomic interactions in atomistic simulations of magnetic systems.Furthermore,in recent years,a new class of interatomic potentials known as magnetic machine-learning interatomic potentials(magnetic MLIPs)has emerged.These MLIPs combine the computational efficiency,in terms of CPU time,of empirical potentials with the accuracy of DFT calculations.In this review,our focus lies on providing a comprehensive summary of the interatomic interaction models developed specifically for investigating magnetic materials.We also delve into the various problem classes to which these models can be applied.Finally,we offer insights into the future prospects of interatomic interaction model development for the exploration of magnetic materials.

Bioinspired Multifunctional Self-Sensing Actuated Gradient Hydrogel for Soft-Hard Robot Remote Interaction

The development of bioinspired gradient hydrogels with self-sensing actuated capabilities for remote interaction with soft-hard robots remains a challenging endeavor. Here, we propose a novel multifunctional self-sensing actuated gradient hydrogel that combines ultrafast actuation and high sensitivity for remote interaction with robotic hand. The gradient network structure, achieved through a wettability difference method involving the rapid precipitation of MoO_(2) nanosheets, introduces hydrophilic disparities between two sides within hydrogel. This distinctive approach bestows the hydrogel with ultrafast thermo-responsive actuation(21° s^(-1)) and enhanced photothermal efficiency(increase by 3.7 ℃ s^(-1) under 808 nm near-infrared). Moreover, the local cross-linking of sodium alginate with Ca^(2+) endows the hydrogel with programmable deformability and information display capabilities. Additionally, the hydrogel exhibits high sensitivity(gauge factor 3.94 within a wide strain range of 600%), fast response times(140 ms) and good cycling stability. Leveraging these exceptional properties, we incorporate the hydrogel into various soft actuators, including soft gripper, artificial iris, and bioinspired jellyfish, as well as wearable electronics capable of precise human motion and physiological signal detection. Furthermore, through the synergistic combination of remarkable actuation and sensitivity, we realize a self-sensing touch bioinspired tongue. Notably, by employing quantitative analysis of actuation-sensing, we realize remote interaction between soft-hard robot via the Internet of Things. The multifunctional self-sensing actuated gradient hydrogel presented in this study provides a new insight for advanced somatosensory materials, self-feedback intelligent soft robots and human–machine interactions.