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.

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%.

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.

A new interacting capillary bundle model on the multiphase flow in micropores of tight rocks

Surfactants are widely used in the fracturing fluid to enhance the imbibition and thus the oil recovery rate. However, current numerical models cannot capture the physics behind capillary imbibition during the wettability alteration by surfactants. Although the interacting capillary bundle(ICB) model shows potential in characterizing imbibition rates in different pores during wettability alteration, the existing ICB models neglect the influence of wettability and viscosity ratio on the imbibition behavior, making it difficult to accurately describe the oil-water imbibition behavior within the porous media. In this work,a new ICB mathematical model is established by introducing pressure balance without assuming the position of the leading front to comprehensively describe the imbibition behavior in a porous medium under different conditions, including gas-liquid spontaneous imbibition and oil-water imbibition.When the pore size distribution of a tight rock is known, this new model can predict the changes of water saturation during the displacement process in the tight rock, and also determine the imbibition rate in pores of different sizes. The water saturation profiles obtained from the new model are validated against the waterflooding simulation results from the CMG, while the imbibition rates calculated by the model are validated against the experimental observations of gas-liquid spontaneous imbibition. The good match above indicates the newly proposed model can show the water saturation profile at a macroscopic scale while capture the underlying physics of the multiphase flow in a porous medium at a microscopic scale. Simulation results obtained from this model indicate that both wettability and viscosity ratio can affect the sequence of fluid imbibition into pores of different sizes during the multiphase flow, where less-viscous wetting fluid is preferentially imbibed into larger pores while more-viscous wetting fluid tends to be imbibed into smaller pores. Furthermore, this model provides an avenue to calculate the imbibition rate in pores of different sizes during wettability alteration and capture the non-Darcy effect in micro-and nano-scale pores.

Tailoring Light–Matter Interactions in Overcoupled Resonator for Biomolecule Recognition and Detection

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.

Silica-modified Pt/TiO_(2) catalysts with tunable suppression of strong metal-support interaction for cinnamaldehyde hydrogenation

Tuning Strong Metal-support Interactions(SMSI)is a key strategy to obtain highly active catalysts,but conventional methods usually enable TiO_(x) encapsulation of noble metal components to minimize the exposure of noble metals.This study demonstrates a catalyst preparation method to modulate a weak encapsulation of Pt metal nanoparticles(NPs)with the supported TiO_(2),achieving the moderate suppression of SMSI effects.The introduction of silica inhibits this encapsulation,as reflected in the characterization results such as XPS and HRTEM,while the Ti^(4+) to Ti^(3+) conversion due to SMSI can still be found on the support surface.Furthermore,the hydrogenation of cinnamaldehyde(CAL)as a probe reaction revealed that once this encapsulation behavior was suppressed,the adsorption capacity of the catalyst for small molecules like H_(2) and CO was enhanced,which thereby improved the catalytic activity and facilitated the hydrogenation of CAL.Meanwhile,the introduction of SiO_(2) also changed the surface structure of the catalyst,which inhibited the occurrence of the acetal reaction and improved the conversion efficiency of C=O and C=C hydrogenation.Systematic manipulation of SMSI formation and its consequence on the performance in catalytic hydrogenation reactions are discussed.

Effect of electron-electron interaction on polarization process of exciton and biexciton in conjugated polymer

By using one-dimensional tight-binding model modified to include electron-electric field interaction and electron-electron interaction,we theoretically explore the polarization process of exciton and biexciton in cis-polyacetylene.The dynamical simulation is performed by adopting the non-adiabatic evolution approach.The results show that under the effect of moderate electric field,when the strength of electron-electron interaction is weak,the singlet exciton is stable but its polarization presents obvious oscillation.With the enhancement of interaction,it is dissociated into polaron pairs,the spin-flip of which can be observed through modulating the interaction strength.For the triplet exciton,the strong electron-electron interaction restrains its normal polarization,but it is still stable.In the case of biexciton,the strong electron-electron interaction not only dissociate it,but also flip its charge distribution.The yield of the possible states formed after the dissociation of exciton and biexciton is also calculated.

T cell interactions with microglia in immune-inflammatory processes of ischemic stroke

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.