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.

Catalyst–Support Interaction in Polyaniline‑Supported Ni_(3)Fe Oxide to Boost Oxygen Evolution Activities for Rechargeable Zn‑Air Batteries

Catalyst–support interaction plays a crucial role in improving the catalytic activity of oxygen evolution reaction(OER).Here we modulate the catalyst–support interaction in polyaniline-supported Ni_(3)Fe oxide(Ni_(3)Fe oxide/PANI)with a robust hetero-interface,which significantly improves oxygen evolution activities with an overpotential of 270 mV at 10 mA cm^(-2)and specific activity of 2.08 mA cm_(ECSA)^(-2)at overpotential of 300 mV,3.84-fold that of Ni_(3)Fe oxide.It is revealed that the catalyst–support interaction between Ni_(3)Fe oxide and PANI support enhances the Ni–O covalency via the interfacial Ni–N bond,thus promoting the charge and mass transfer on Ni_(3)Fe oxide.Considering the excellent activity and stability,rechargeable Zn-air batteries with optimum Ni_(3)Fe oxide/PANI are assembled,delivering a low charge voltage of 1.95 V to cycle for 400 h at 10 mA cm^(-2).The regulation of the effect of catalyst–support interaction on catalytic activity provides new possibilities for the future design of highly efficient OER catalysts.

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.

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.

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.

AAV mediated carboxyl terminus of Hsp70 interacting protein overexpression mitigates the cognitive and pathological phenotypes of APP/PS1 mice

The E3 ubiquitin ligase,carboxyl terminus of heat shock protein 70(Hsp70)interacting protein(CHIP),also functions as a co-chaperone and plays a crucial role in the protein quality control system.In this study,we aimed to investigate the neuroprotective effect of overexpressed CHIP on Alzheimer’s disease.We used an adeno-associated virus vector that can cross the blood-brain barrier to mediate CHIP overexpression in APP/PS1 mouse brain.CHIP overexpression significantly ameliorated the performance of APP/PS1 mice in the Morris water maze and nest building tests,reduced amyloid-βplaques,and decreased the expression of both amyloid-βand phosphorylated tau.CHIP also alleviated the concentration of microglia and astrocytes around plaques.In APP/PS1 mice of a younger age,CHIP overexpression promoted an increase in ADAM10 expression and inhibitedβ-site APP cleaving enzyme 1,insulin degrading enzyme,and neprilysin expression.Levels of HSP70 and HSP40,which have functional relevance to CHIP,were also increased.Single nuclei transcriptome sequencing in the hippocampus of CHIP overexpressed mice showed that the lysosomal pathway and oligodendrocyte-related biological processes were up-regulated,which may also reflect a potential mechanism for the neuroprotective effect of CHIP.Our research shows that CHIP effectively reduces the behavior and pathological manifestations of APP/PS1 mice.Indeed,overexpression of CHIP could be a beneficial approach for the treatment of Alzheimer’s disease.

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.

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.

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.

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.

Enhanced Ion-Selective Diffusion Achieved by Supramolecular Interaction for High Thermovoltage and Thermal Stability

Thermoelectric(TE)generators capable of converting thermal energy into applicable electricity have gained great popularity among emerging energy conversion technologies.Biopolymer-based ionic thermoelectric(i-TE)materials are promising candidates for energy conversion systems because of their wide sources,innocuity,and low manufacturing cost.However,common physically crosslinked biopolymer gels induced by single hydrogen bonding or hydrophobic interaction suffer from low differential thermal voltage and poor thermodynamic stability.Here,we develop a novel i-TE gel with supramolecular structures through multiple noncovalent interactions between ionic liquids(ILs)and gelatin molecular chains.The thermopower and thermoelectric power factor of the ionic gels are as high as 2.83 mV K-1 and 18.33μW m^(-1)K^(-2),respectively.The quasi-solid-state gelatin-[EMIM]DCA i-TE cells achieve ultrahigh 2 h output energy density(E_(2h)=9.9 mJ m^(-2))under an optimal temperature range.Meanwhile,the remarkable stability of the supramolecular structure provides the i-TE hydrogels with a thermal stability of up to 80℃.It breaks the limitation that biopolymer-based i-TE gels can only be applied in the low temperature range and enables biopolymer-based i-TE materials to pursue better performance in a higher temperature range.

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.

Plume-lithosphere interaction in the Comei Large Igneous Province: Evidence from two types of mafic dykes in Gyangze, south Tibet, China

Two suites of mafic dykes,T1193-A and T1194-A,outcrop in Gyangze area,southeast Tibet.They are in the area of Comei LIP and have indistinguishable field occurrences with two other dykes in Gyangze,T0902 dyke with 137.7±1.3 Ma zircon age and T0907 dyke with 142±1.4 Ma zircon age reported by Wang YY et al.(2016),indicating coeval formation time.Taking all the four diabase dykes into consideration,two different types,OIB-type and weak enriched-type,can be summarized.The“OIB-type”samples,including T1193-A and T0907 dykes,show OIB-like geochemical features and have initial Sr-Nd isotopic values similar with most mafic products in Comei Large Igneous Provinces(LIP),suggesting that they represent melts directly generated from the Kerguelen mantle plume.The“weak enriched-type”samples,including T1194-A and T0902 dykes,have REEs and trace element patterns showing withinplate affinity but have obvious Nb-Ta-Ti negative anomalies.They show uniform lowerεNd(t)values(−6‒−2)and higher 87Sr/86Sr(t)values(0.706‒0.709)independent of their MgO variation,indicating one enriched mantle source.Considering their closely spatial and temporal relationship with the widespread Comei LIP magmatic products in Tethyan Himalaya,these“weak enriched-type”samples are consistent with mixing of melts from mantle plume and the above ancient Tethyan Himalaya subcontinental lithospheric mantle(SCLM)in different proportions.These weak enriched mafic rocks in Comei LIP form one special rock group and most likely suggest large scale hot mantle plume-continental lithosphere interaction.This process may lead to strong modification of the Tethyan Himalaya lithosphere in the Early Cretaceous.

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.

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.

Resistive field generation in intense proton beam interaction with solid targets

The Brown-Preston-Singleton(BPS)stopping power model is added to our previously developed hybrid code to model ion beam-plasma interaction.Hybrid simulations show that both resistive field and ion scattering effects are important for proton beam transport in a solid target,in which they compete with each other.When the target is not completely ionized,the self-generated resistive field effect dominates over the ion scattering effect.However,when the target is completely ionized,this situation is reversed.Moreover,it is found that Ohmic heating is important for higher current densities and materials with high resistivity.The energy fraction deposited as Ohmic heating can be as high as 20%-30%.Typical ion divergences with half-angles of about 5°-10°will modify the proton energy deposition substantially and should be taken into account.

Isotope Tracking of Surface Water Groundwater Interaction in the Beninese Part of the Iullemeden Aquifer System

The Kandi basin is located in northeast Benin (West Africa). This study is focused on the estimation of water fluxes exchanged between the river Niger (and its tributaries) and the transboundary Iullemeden Aquifer System. In that framework, an innovative approach based on the application of the Bayesian Mixing Model (MixSIAR) analysis on water isotopes (oxygen-18, deuterium and tritium) was performed. Moreover, to assess the relevance of the model outputs, Pearson’s correlation and Principal Component Analysis (PCA) have been done. A complex relationship between surface water and groundwater has been found. Sixty percent (60%) of groundwater samples are made of more than 70% river water and rainwater;while 31.25% of surface water samples are made of about 84% groundwater. To safeguard sustainable water resources for the well-being of the local communities, surface water and groundwater must be managed as a unique component in the Kandi basin.

Docking of Human Band 3 Anion Transporter Proteins with Their Plasmodium falciparum Interactors Based on Short Linear Motifs

Plasmodium (P.) falciparum is a pathogen that causes severe forms of malaria. Protein interactions have been shown to occur between P. falciparum and human erythrocytes in human blood. The Band 3 Anion Transporter (B3AT) protein is considered the main invasive pathway for the parasite in erythrocytes that causes clinical symptoms for malaria in humans. The interactions between P. falciparum parasites and erythrocytes along this receptor have previously been explored. Short linear motifs (SLIMs) are short linear mediator sequences that involve several biological processes, acting as mediators of protein interactions identifiable by computational tools such as SLiMFinder. For a given protein, the identification of SLIMs allows predicting its interactors. Using the SLIMs approach, protein-protein interaction network analyses between P. falciparum and its human host, were used to identify a tryptophan-rich protein, A5K5E5_PLAVS as an essential interactor of B3AT. To better understand the interaction mechanism, a guided protein-protein docking approach based on SLIM motifs was performed for human B3AT and A5K5E5_PLAVS. The highlights of this important interaction between P. falciparum and its human host have the potential to pave the way to identify new therapeutic candidates.