Initial host-pathogen interactions explained by the Organism Prearranged Recognition Theory: fundamental role of saccharides

Herein based on literature available a hypothesis is provided about molecular basis for initial events in establishment interactions.This hypothesis asserts that:"recognition and interaction that occur between organisms is prearranged.There are membrane receptors with or without soluble components derived from the respective organisms that bridge specific interactions".Organisms'prearranged recognition theory(OPRT)can be specifically applied to host-microbe interactions where most microbes are coated(opsonised)by soluble components(opsonins)from the host,but there are also some microbes that can bypass host opsonization expressing receptors for the host cells or secreting host’s opsonin-like molecules.The receptors involved in organism's interactions,their specificity and repertoire depend on saccharides from glycoproteins,glycolipids,and polysaccharides(glycans)which are abundant extracellular components.Based in OPRT is possible to explain species-specific interactions and several other phenomena,such as hyper-infectivity,tissue tropism,differential sensitivity to disease depending on type O-blood,and tumoral cell promiscuity.The lipid raft domain in cellular membrane is proposed as the main location where interactions will trigger cellular responses.Possible scientific and biotechnology applications and alternative routes to modify organism's interactions and consequences are discussed.It is a novel hypothesis regarding the degree to which an organism's interactions are prearranged and the role of saccharides epitopes.

Novel insights into host-pathogen interactions of large yellow croakers(Larimichthys crocea)and pathogenic bacterium Pseudomonas plecoglossicida using time-resolved dual RNA-seq of infected spleens

Host-pathogen interactions are highly complex,involving large dynamic changes in gene expression during infection. These interactions are fundamental to understanding anti-infection immunity of hosts, as well as the pathogenesis of pathogens. For bacterial pathogens interacting with animal hosts, timeresolved dual RNA-seq of infected tissue is difficult to perform due to low pathogen load in infected tissue. In this study, an acute infection model of Larimichthys crocea infected by Pseudomonas plecoglossicida was established. The spleens of infected fish exhibited typical symptoms, with a maximum bacterial load at two days post-injection(dpi). Time-resolved dual RNA-seq of infected spleens was successfully applied to study hostpathogen interactions between L. crocea and P.plecoglossicida. The spleens of infected L. crocea were subjected to dual RNA-seq, and transcriptome data were compared with those of noninfected spleens or in vitro cultured bacteria. Results showed that pathogen-host interactions were highly dynamically regulated, with corresponding fluctuations in host and pathogen transcriptomes during infection. The expression levels of many immunogenes involved in cytokine-cytokine receptor,Toll-like receptor signaling, and other immunerelated pathways were significantly up-regulated during the infection period. Furthermore, metabolic processes and the use of oxygen in L. crocea were strongly affected by P. plecoglossicida infection. The WGCNA results showed that the metabolic process was strongly related to the entire immune process.For P. plecoglossicida, the expression levels of motility-related genes and flagellum assemblyrelated genes were significantly up-regulated. The results of this study may help to elucidate the interactions between L. crocea and P.plecoglossicida.

Roles of HIV-1 auxiliary proteins in viral pathogenesis and host-pathogen interactions

Active host-pathogen interactions take place during infection of human immunodeficiency virus type 1 (HIV-1). Outcomes of these interactions determine the efficiency of viral infection and subsequent disease progression. HIV- infected cells respond to viral invasion with various defensive strategies such as innate, cellular and humoral immune antiviral mechanisms. On the other hand, the virus has also developed various offensive tactics to suppress these host cellular responses. Among many of the viral offensive strategies, HIV-1 viral auxiliary proteins (Tat, Rev, Nef, Vif, Vpr and Vpu) play important roles in the host-pathogen interaction and thus have significant impacts on the outcome of HIV infection. One of the best examples is the interaction of Vif with a host cytidine deaminase APOBEC3G. Although specific roles of other auxiliary proteins are not as well described as Vif-APOBEC3G interaction, it is the goal of this brief review to summarize some of the preliminary findings with the hope to stimulate further discussion and investiga- tion in this exhilarating area of research.

New insights of Helicobacter pylori host-pathogen interactions: The triangle of virulence factors, epigenetic modifications and non-coding RNAs

Helicobacter pylori(H. pylori) is a model organism for understanding host-pathogen interactions and infection-mediated carcinogenesis. Gastric cancer and H. pylori colonization indicates the strong correlation. The progression and exacerbation of H. pylori infection are influenced by some factors of pathogen and host. Several virulence factors involved in the proper adherence and attenuation of immune defense to contribute the risk of emerging gastric cancer, therefore analysis of them is very important. H. pylori also modulates inflammatory and autophagy process to intensify its pathogenicity. From the host regard, different genetic factors particularly affect the development of gastric cancer. Indeed, epigenetic modifications, Micro RNA and long non-coding RNA received more attention. Generally, various factors related to pathogen and host that modulate gastric cancer development in response to H. pylori need more attention due to develop an efficacious therapeutic intervention. Therefore, this paper will present a brief overview of host-pathogen interaction especially emphases on bacterial virulence factors, interruption of host cellular signaling, the role of epigenetic modifications and non-coding RNAs.

A mathematic equation derived from host-pathogen interactions elucidates the significance of integrating modern medicine with traditional Chinese medicine to treat infectious diseases

The prognosis of infectious diseases is determined by host-pathogen interactions.Control of pathogens has been the central dogma of treating infectious diseases in modern medicine,but the pathogen-directed medicine is facing significant challenges,including a lack of effective antimicrobials for newly emerging pathogens,pathogen drug resistance,and drug side effects.Here,a mathematic equation(ter-med equation of host-pathogen interactions,HPI-Equation)is developed to dissect the key variables of hostpathogen interactions.It shows that control of pathogens does not necessarily lead to host recov-ery.Instead,a combination of promoting a host’s power of self-healing and balancing immune responses provides the best benefit for host.Moreover,the HPI-Equation elucidates the scientific basis of traditional Chinese medicine(TCM),a host-based medicine that treats infectious diseases by promot-ing self-healing power and balancing immune responses.The importance of self-healing power eluci-dated in the HPIEquation is confirmed by recent studies that the tolerance mechanism,which is discovered in plants and animals and conceptually similar to self-healing power,improves host survival without directly attacking pathogens.In summary,the HPI-Equation describes host-pathogen interac-tions with mathematical logic and precision;it translates the ancient wisdoms of TCM into apprehen-sible modern sciences and opens a new venue for integrating TCM and modern medicine for a future medicine.

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.

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.

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.

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.

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%.

Temporal trends and cohort variations of gender-specific major depressive disorders incidence in China:analysis based on the age-period-cohortinteraction model

Background Major depressive disorders(MDDs)impose substantial burdens on individuals and society;however,further detailed analysis is still needed for its long-term trends.Aims This study aimed to analyse the gender-specific temporal trends and cohort variations of MDD incidence among Chinese residents over the past three decades.Methods Employing the age-period-cohort-interaction model and leveraging data from the Global Burden of Disease Study 2019,this research identified and analysed incidence trends of MDD among Chinese males and females aged 5-94 years from 1990 to 2019 across three dimensions,encompassing age,period and birth cohort.Results The analysis reveals age-related effects,indicating heightened MDD risk among adolescents and older adults.Specifically,individuals entering the older adulthood at the age of 65-69 significantly increased the risk of MDD by 64.9%.People aged 90-94 years witnesseda 105.4%increase in MDD risk for the overall population,with females and males in this age group experiencing a 75.1%and 103.4%increase,respectively.In terms of period effects,the risk of MDD displayed a decline from 1990 to 1994,followed by a rebound in 2008.Cohort effects demonstrated diverse generational patterns,with generationⅠand generationⅢmanifesting opposing‘age-as-level'trends.GenerationⅡand generationⅣexhibited'cumulative disadvantage'and'cumulative advantage'patterns,respectively.Age effects indicated an overall higher risk of MDD incidence in females,while cohort effects showed greater variations of MDD incidence among females.Conclusions The study underscores the substantial effects of age,period and cohort on MDD across genders in China.Priority interventions targeting vulnerable populations,including children,adolescents,older adults,females and the post-millennium birth cohort,are crucial to mitigate the impact of MDD.

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.

Dzyaloshinskii–Moriya interaction and field-free sub-10 nm topological magnetism in Fe/bismuth oxychalcogenides heterostructures

Topological magnetism with strong robustness,nanoscale dimensions and ultralow driving current density(106 A/m^(2))is promising for applications in information sensing,storage,and processing,and thus sparking widespread research interest.Exploring candidate material systems with nanoscale size and easily tunable properties is a key for realizing practical topological magnetism-based spintronic devices.Here,we propose a class of ultrathin heterostructures,Fe/Bi_(2)O_(2)X(X=S,Se,Te)by deposing metal Fe on quasi-two-dimensional(2D)bismuth oxychalcogenides Bi_(2)O_(2)X(X=S,Se,Te)with excellent ferroelectric/ferroelastic properties.Large Dzyaloshinskii–Moriya interaction(DMI)and topological magnetism can be realized.Our atomistic spin dynamics simulations demonstrate that field-free vortex–antivortex loops and sub-10 nm skyrmions exist in Fe/Bi_(2)O_(2)S and Fe/Bi_(2)O_(2)Se interfaces,respectively.These results provide a possible strategy to tailor topological magnetism in ultrathin magnets/2D materials interfaces,which is extremely vital for spintronics applications.

The Gravitational Interaction between Moving Mass Particles Explained by the Theory of Informatons

In the article “Newtons Law of Universal Gravitation Explained by the Theory of Informatons” the gravitational interaction between mass particles at rest has been explained by the hypothesis that g-information carried by informatons is the substance of the medium that the interaction in question makes possible. It has been showed that, on the macroscopic level, that medium—the “gravitational field”—manifests itself as the vector field Eg. In this article we will deduce from the postulate of the emission of informatons, that the informatons emitted by a moving mass particle carry not only information about the position (g-information) but also about the velocity (“β-information”) of their emitter. It follows that the gravitational field of a moving mass particle is a dual entity always having a field- and an induction-component (Egand Bg) simultaneously created by their common sources: time-variable masses and mass flows and that the gravitational interaction is the effect of the fact that an object in a gravitational field always tends to become “blind” for that field by accelerating according to a Lorentz-like law.

Dynamics of Non-Markovianity, Quantum Correlations and Information Scrambling of Three Qubits Systems Interacting via Rashba Interaction

The behavior of the quantum correlations, information scrambling and the non-Markovianity of three entangling qubits systems via Rashba is discussed. The results showed that, the three physical quantities oscillate between their upper and lower bounds, where the number of oscillations increases as the Rashba interaction strength increases. The exchanging rate of these three quantities depends on the Rashba strength, and whether the entangled state is generated via direct/indirect interaction. Moreover, the coherence parameter can be used as a control parameter to maximize or minimize the three physical quantities.