Network Interactions Research Articles

Phased characterization of soy protein gel modified by lactobacillus plantarum JYLP-326 in cooperation with acidic tremella fuciformis fruiting body polysaccharide: Focus on structural network, interaction and gel properties.

Soybean protein isolate (SPI) and acidic tremella fuciformis fruiting body polysaccharide (AP) were used to prepare phased products "sterilized soft gel (SPI-AP)" and "fermented strong gel (FSPI-AP)" to study the structural network, interaction and gel characteristics. The contents of α-helix (20.43% to 25.36%) and β-sheet (31.24% to 35.12%) of FSPI-AP increased compared with that of SPI. The introduction of AP and microorganisms improved the orderliness of peptide chain through non-covalent and covalent interactions, with hydrophobic (33.33%), electrostatic (26.77%), and disulfide bonds (24.45%) being the dominant forces in the formation of gels. Furthermore, AP could decrease the crystallinity and disrupt the regular rigid structure of protein molecules, so FSPI-AP had stronger cohesion to resist external force. FSPI-AP had the highest proportion of interaction (12.57%) in the interaction network, while SPI-AP was 9.07%. This study will provide a new idea for innovating the application of protein-polysaccharide gel systems.

Self-similar scaling of higher order interactions in complex networks

Self-similar scaling of higher order interactions in complex networks

Cell-Interface-Deciphering Lipid Nanotablet for Nanoparticle Logic Gate-Based Real-Time Single-Cell Analysis.

Analyzing the cell interface is of paramount importance in understanding how cells interact and communicate with other cells, but an advanced analytical platform that can process complex and networked interactions between cell surface ligands and receptors is lacking. Herein, we developed the cell-interface-deciphering lipid nanotablet (CID-LNT) for multiplexed real-time cell analysis. LNT is a nanoparticle-tethered lipid bilayer chip where freely diffusing plasmonic nanoparticles induce scattering signal changes. The CID-LNT transduces cell surface protein information into DNA data, which operate as nanoparticle logic gates. As a proof of concept, we detected and analyzed programmed death-ligand 1 (PD-L1) and associated immune signals (TNF-α, EGF, and IFN-γ). PD-L1 is an immune checkpoint that suppresses T cell activity with inflammatory biomolecules facilitating its expression. The CID-LNT can serve as a dynamic nanoparticle logic board, enabling the logic gate-based analysis of membrane proteins, and can be expanded to immunological synapse analysis, cell interface engineering, and molecular diagnostics.

In Silico Structural Insights into a Glucanase from Clostridium perfringens and Prediction of Structural Stability Improvement Through Hydrophobic Interaction Network and Aromatic Interaction.

Glucanases are widely applied in industrial applications such as brewing, biomass conversion, food, and animal feed. Glucanases catalyze the hydrolysis of glucan to produce the sugar hemiacetal through hydrolytic cleavage of glycosidic bonds. Current study aimed to investigate structural insights of a glucanase from Clostridium perfringens through blind molecular docking, site-specific molecular docking, molecular dynamics (MD) simulation, and binding energy calculation. Furthermore, we aimed to enhance structural stabilization through formation of hydrophobic interaction network. The molecular docking results illustrated that residues Glu222 and Asp187 may act as nucleophile acid/base catalyst. Moreover, the MM/PBSA results illustrated a high binding affinity of 108.71 ± 8.5kJ/mol between glucanase and barely glucan during 100 ns simulation. The RMSF analysis illustrated a high flexible surface loop with the highest mobility at position D130. Therefore, the structural engineering was carried out through introducing a double-mutant S125Y/D130P, and the structural stability was improved by forming the hydrophobic interaction network and one π-π aromatic interaction. The spatial distance between the mutation sites and the catalytic pocket attenuates their direct impact on binding interactions within the catalytic pocket.

AI-Driven Security Posture Management: A Revolutionary Approach to Multi-Cloud Enterprise Security

The landscape of cloud security has undergone a transformative evolution, driven by the complexity of modern digital infrastructures and the escalating sophistication of cyber threats. This comprehensive article explores an innovative AI-driven Cloud Security Posture Management (CSPM) framework that transcends traditional security methodologies. By leveraging advanced machine learning algorithms, neural network architectures, and intelligent automation, the framework offers a proactive, adaptive approach to cybersecurity that addresses the multifaceted challenges of multi-cloud environments. The article demonstrates how intelligent systems can dynamically analyze network interactions, predict potential vulnerabilities, and implement rapid, context-aware response mechanisms, fundamentally reshaping how organizations conceptualize and implement security strategies.

Exploring the mechanisms of Yang Wei Shu granule for the treatment of chronic atrophic gastritis using UPLC-QTOF-MS/MS, network pharmacology, and cell experimentation.

Chronic atrophic gastritis (CAG) is a global disease of the digestive system and is an important precancerous lesion in the development of gastric cancer. Yang Wei Shu granule (YWSG), which evolved from the formula 'Warm Stomach Soup' of the Jin and Yuan Dynasties in China, is frequently used as a classic herbal compound in the treatment of CAG. However, the active ingredients and mechanisms by which it works are not clear. To elucidate the chemical composition of YWSG and investigate the potential mechanisms of YWSG on CAG by composition analysis, network pharmacology and cellular experimental studies. The chemical and blood-entry constituents of YWSG were analyzed by ultra-high performance liquid chromatography-Quadrupole tandem time-of-flight mass spectrometry (UPLC-QTOF-MS/MS). Subsequently, potential targets of YWSG for CAG treatment were identified through utilization of publicly available online resources. The YWSG-component-target-pathway network and protein-protein interaction (PPI) network were constructed using Cytoscape software. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of potential targets was performed using the DAVID database. Finally, a cellular model of lipopolysaccharide (LPS)-activated RAW 264.7 macrophages was established and validated by in vitro experiments. A total of 150 compounds in YWSG and 47 blood-entry constituents were identified by using UPLC-QTOF-MS/MS. Based on network pharmacology, a total of 132 target genes were identified as being involved in the therapeutic effect of YWSG on CAG. Network pharmacology and molecular docking results suggest that AKT1, PIK3CA, PTPN11, SRC and STAT3 may be potential targets of YWSG for the treatment of CAG. Cellular experiments showed that the YWSG-containing serum had no cytotoxic effect on RAW264.7 cells and could inhibit nitric oxide (NO) production and the expression of pro-inflammatory factors TNF-α, IL-6, and IL-1β. Additionally, it was observed to promote the expression of the anti-inflammatory factor IL-10 in LPS-stimulated RAW264.7 cells. The immunofluorescence results showed that YWSG treated CAG by inhibiting the PI3K-Akt pathway. The mechanism of action of YWSG on CAG was preliminarily elucidated using UPLC-Q-TOF-MS/MS, network pharmacology and in vitro experiments. The main active components and potential targets of YWSG were investigated, providing a scientific basis for further research.

The Alteration of Brain Network Topology in Tinnitus Transition From Recent-Onset to Chronic.

The occurrence and persistence of tinnitus result from the interaction of multiple neural networks. This study aims to explore the alterations in brain network topology associated with the transition of tinnitus from recent-onset to chronic. Twenty-eight patients with chronic tinnitus, 28 patients with recent-onset tinnitus and 28 sex- and age-matched healthy controls (HC) were enrolled in this study. We performed a graph theory analysis to identify aberrant brain network topologies and calculated the correlation between differential brain regions and clinical indicators. Compared with the recent-onset tinnitus group, patients with chronic tinnitus showed decreased global efficiency (Eg, decreased by 3.7%, p < 0.001), local efficiency (Eloc, decreased by 1.8%, p = 0.031) and small-worldness (decreased by 13.8%, p = 0.007) and increased characteristic path length (Lp, increased by 6.8%, p = 0.001). Additionally, ANOVA revealed significant differences in the AUC of degree centrality (DC), nodal efficiency (Ne), nodal clustering coefficient (NCp) and nodal local efficiency (Nle) among the three groups in brain regions such as the superior temporal gyrus, inferior temporal gyrus, anterior cingulate cortex, precuneus, middle occipital gyrus, inferior occipital gyrus, fusiform gyrus, cuneus and putamen (q < 0.05, FDR corrected). Notably, several of these regions were associated with tinnitus duration, distress and loudness. The topological properties of several brain networks were altered in patients with chronic tinnitus compared to those with recent-onset tinnitus, providing new insights into the neural mechanisms of tinnitus chronification. These findings could inform the development of targeted interventions aimed at mitigating the progression from recent-onset to chronic tinnitus.

THE TWO FACES OF E-COMMERCE: A COMPARISON OF E-COMMERCE PLATFORMS AND SOCIAL COMMERCE

E-commerce today is primarily concentrated in two main systems: commerce through e-commerce platforms and social commerce. E-commerce platforms, such as Amazon and Hepsiburada, are large online marketplaces offering a wide range of products, requiring significant initial investments, and providing a secure shopping experience. On the other hand, social commerce takes place through social media platforms, is based on personal interactions at lower costs, and focuses on converting users' social network interactions into shopping activities. While e-commerce platforms stand out for their reliability and comprehensive services, social commerce offers a more direct and interactive shopping experience. In this context, the aim of this study is to examine the differences between commerce through e-commerce platforms and social commerce in the field of digital marketing. To achieve this goal, the research question "What are the differences between e-commerce platforms and social commerce?" was posed. To address this question, document analysis, one of the qualitative analysis techniques, was employed, and the differences between e-commerce platforms and social commerce were revealed.

THEORETICAL MODEL FOR MANAGING THE IMPORT SUBSTITUTION PROCESS

The article is devoted to the current problem of import substitution, since increasing technological independence is identified as a priority in the Strategy for Scientific and Technological Development of the Russian Federation. In the context of ongoing sanctions from the West, the processes of import substitution require the formation of scientific and methodological tools for the diversification of production processes based on technologies, materials and components of domestic production. The theoretical analysis carried out made it possible to identify and characterize the main integration forms of interaction between organizations in the process of import substitution (holding, cluster, union, technology park), determine their advantages and disadvantages from the standpoint of combining production capacities and complementary resources and technologies. An analysis of the regulatory and legislative framework governing the processes of import substitution was carried out to ensure the overall orderliness of actions. As part of the work of the Government Commission on Import Substitution, the “Plan for Promoting Import Substitution in Industry” was adopted; in accordance with the priority areas of scientific and technological development until 2030, private regulatory legal acts are constantly being developed. The analysis of statistical data showed that the domestic industrial complex is successfully coping with the consequences of the lack of imports, options have been found to intensify import substitution processes within the framework of innovation infrastructure, and “digital production” technologies are being developed. The import substitution policy has received a new round of development from 2022, aimed at replacing missing imported products along with critical end-to-end technologies. There is an annual increase in indicators of intellectual activity and infrastructure support for import substitution processes. A methodological approach to managing import substitution processes is proposed, which involves creating an infrastructure to support developers of new technologies, taking into account the possibility of network interaction. A generalized model of the mechanism for managing import substitution processes is proposed, ensuring the achievement of goals at the micro-macro and meso levels, which can be the basis for developing a methodology for forming the import substitution process of an organization.

Comprehensive Analysis of the GiTCP Gene Family and Its Expression Under UV-B Radiation in Glycyrrhiza inflata Bat.

TCP is a plant-specific transcription factor that plays an important role in plant growth and development. In this study, we used bioinformatics to identify the entire genome of the TCP gene family in Glycyrrhiza inflata Bat, and we analyzed the expression characteristics of GiTCP genes under UV-B radiation using qRT-PCR. The results were as follows: (1) 24 members of the TCP gene family were identified in G. inflata, evenly distributed on its 24 chromosomes. (2) The GiTCP genes contained 0-4 introns and 0-5 exons. (3) The GiTCP genes were phylogenetically divided into three subfamilies-PCF, CIN, and CYC/TB1, with 14, 9, and 1 GiTCP proteins, respectively. (4) A covariance analysis showed that two pairs of GiTCP genes underwent a fragmentary duplication event. (5) A cis-element analysis showed that the cis-responsive elements of the GiTCP genes' promoter regions were mainly comprised of light-responsive, stress-responsive, hormone-regulated, growth and development, and metabolic-regulated elements. (6) A protein network interaction analysis revealed a total of 14 functional molecules of TCPs and 8 potential interacting proteins directly related to GiTCP proteins. (7) GO annotation showed that the GiTCP genes were mainly enriched in BP, CC, and MF groups and had corresponding functions. (8) RNA-seq and qRT-PCR further indicated that GiTCP3, 6, 7, 8, 12, 14, 17, 23, and 24 were up- or down-regulated in G. inflata after UV-B radiation, demonstrating that these genes responded to UV-B radiation in G. inflata. (9) Subcellular localization analysis showed that the GiTCP8 protein was localized in the nucleus. The results of this study provide a basis for further exploration of the function of the GiTCP gene family in the growth and development of G. inflata.

МОДЕЛИРОВАНИЕ ЦИФРОВОЙ ПЛАТФОРМЫ ИННОВАЦИОННОЙ ПРОИЗВОДСТВЕННОЙ ЭКОСИСТЕМЫ РЕГИОНА

The innovation paradigm defines the ecosystem approach as one of the frontier directions in the theory and practice of the development of complex social and economic systems. A characteristic feature of the current stage is the leading role of the Russian financial sector in the creation of ecosystems. At the same time, in order to achieve technological sovereignty and increase competitive advantages, it is important to introduce an ecosystem approach in the real sector of the economy with the participation of actors belonging to sectors of material production industries (industry and agro-industrial complex). The importance of regional-level innovation ecosystems is increasing, because territories with significant scientific, technological, production, and intellectual potential are becoming the locomotives of current and future transformations. The regional innovative production ecosystem (IPER) is a modern format for interaction between actors that allows for the synergy of partnerships between the state, business, science and the real sector of the economy based on network interactions, which is especially important in the agenda of sustainable innovation-oriented growth. A feature of the IPER in the sphere of agricultural production (and the agro-industrial complex as a whole) is a higher level of systemic complexity, which is due to a significant range of factor influence, including not only complex resource provision, but also natural and climatic conditions. Digital transformation is defined as one of the key national development goals until 2030, the number of projects in this area has increased in Russia by 27% over the past five years, and growth potential remains. The level of achievement of digital maturity at the end of 2023 was 74.7% against the planned indicator of 64.2%. The presented algorithm for the digital transition of IPER involves a step-by-step strategizing of the process with the identification of targets, risk assessment and possible realistic scenarios. The interaction of actors based on the joint of resources, the coordination of interests within the framework of IPER with the prospect of platformization is aimed both at achieving their individual goals and at increasing the sustainability of the entire ecosystem, with a projection on regional development and strengthening positions at the national and international levels.

Социальность в социальном. Постсоциальность как возможность

The article substantiates the distinction between social and sociality as two levels of social ontology. The concept of the invariant of sociality is introduced to denote the ability of a set of active agents of natural or artifi cial origin to form a stable homogeneous or heterogeneous unity by orienting each agent to the coordination and coordination of interactions. The analysis of the polemics between J. Habermas and K. Popper regarding the explanation of the mode of emergence of symbolic objects that are part of intersubjective life worlds allowed the author to clarify the peculiarities of interactions in digital communications. If the life world of an individual is constructed for him in the space of the technosystem, and is not a product of the cultural tradition of practices of a certain community, then the content of symbolic formations necessary for interactions with other individuals also arises in the information space organized and fi lled with the technosystem. The conditions of the possible transition of society to a post-social state are considered. According to the author, post-sociality emerges as a format of patterns of interactions between individuals in interactions with imaginary Others. These patterns are objectifi ed symbolic formations and are incorporated into the practices of interactions with the Other in three parallel spaces: a) in the space of direct interpersonal interactions, b) in the space of network interactions mediated by patterns of virtual origin, and c) in the space imposed by network platforms in the form of ‘digital twins’. These three spaces in the intersubjective life world are now being formed as regulators of the behavior of individuals not only in the interhuman, but also in the space of inseparable connection with the digital technosystem.

ANALYSIS AND EVALUATION OF KNOWLEDGE DIFFUSION IN NETWORK STRUCTURES

The article is devoted to the analysis and assessment of knowledge diffusion in network structures. Various models of network interaction are considered, including the knowledge diffusion model based on the adjacency matrix and the method of stochastic actor-oriented models (SAOM). An example of calculating knowledge diffusion in a network structure based on a petrochemical cluster is given, and factors influencing the dissemination of knowledge in the digital economy are analyzed. Particular attention is paid to digital economy tools, such as cloud technologies, knowledge management systems and blockchain, which help to accelerate knowledge sharing and improve the efficiency of interaction between network structure participants. The article presents recommendations for the implementation of digital technologies to optimize the process of knowledge diffusion in emerging and existing network structures.

Implementation of the network interaction model "school - college - university" in the prevention of addiction to psychoactive substances

The existing problems associated with the involvement of the younger generation in drug use require the search for new and conceptual approaches to prevent addiction. To prevent drug addiction among schoolchildren and students, it is important to examine the internal qualities that define their uniqueness and individuality. This will help identify the mechanisms of anesthesia and develop a protection system that will cover students from various educational organizations and age groups. A comprehensive program for primary prevention of surfactant addiction in the continuous educational system of 'school-college-university' and the model of network interaction in the prevention of addiction to surfactants, specifically 'school-college-university' in the Ivanovo region, provides a modern theoretical and practical basis for psychological support in general, secondary, and higher education And also for forming students' opposition to involvement in drug use and preventing dependence on psychoactive substances.

The bHLH transcription factor gene EGL3 accounts for the natural diversity in Arabidopsis fruit trichome pattern and morphology.

The number and distribution of trichomes, i.e., the trichome pattern, in different plant organs shows a conspicuous inter- and intraspecific diversity across Angiosperms that is presumably involved in adaptation to numerous environmental factors. The genetic and molecular mechanisms accounting for the evolution of trichome patterns have just begun to be elucidated. In this study, we aimed to identify and characterize MALAMBRUNO 1 (MAU1), a locus affecting trichome number in the fruits of Arabidopsis (Arabidopsis thaliana) natural populations. To this end, we developed introgression lines (ILs) from the hairy fruit accession Don-0 in the genetic background of the Ler strain with glabrous fruits. Genetic analyses of ILs showed that MAU1 affects fruit trichome patterns through synergistic epistasis with the MYB genes TRICHOMELESS1 (TCL1), GLABRA1 (GL1), and TRIPTYCHON (TRY). In addition, fine mapping and characterization of transgenic lines demonstrated that MAU1 is the bHLH transcription factor gene EGL3, for which Don-0 carries a gain-of-function semidominant allele. Gene expression analyses did not detect differences between EGL3 alleles, thus supporting that a structural missense mutation is the causal nucleotide polymorphism of Don-0. Further phylogenetic analyses of EGL3 showed that most Arabidopsis populations with hairy fruits belong to three haplogroups, suggesting that additional EGL3 natural alleles account for fruit trichome development. Finally, the characterization of EGL3 pleiotropy indicates that Don-0 hyperfunction also increases stem trichome branching. We conclude that EGL3 interactions in the core gene regulatory network of trichome development explain the Arabidopsis natural diversity for fruit trichome pattern and morphology.

Community Assembly Mechanisms of nirK- and nirS-type Denitrifying Bacteria in Sediments of Eutrophic Lake Taihu, China.

Denitrifying bacteria, particularly nirK- and nirS-type, are functionally equivalent and could occupy different niches, but their community assembly mechanisms and responses to environmental heterogeneity are poorly understood in eutrophic lakes. In this study, we investigated the community assembly mechanisms of nirK- and nirS-type denitrifying bacteria and clarified their responses to sediments environmental factors in Lake Taihu, China. The quantitative real-time PCR and Illumina HiSeq-based sequencing revealed that the abundance and composition of two types of denitrifyingbacterial communities varied among different sites in the sediments of Lake Taihu. The functions of these two types of denitrifying bacteria were assigned to mainly nitrogen cycling along with carbon, oxygen, and sulfur cycling, indicating their diverse ecosystems functions. Neutral community model showed that majority of nirK- and nirS-type denitrifying bacteria were neutrally distributed, while dispersal and selection were the dominant drivers in shaping community assembly of nirK-type bacteria. The community assembly of nirS-type was mainly driven by homogeneous selection. We found complex network interactions between nirK- and nirS-type denitrifying bacteria with other bacterial communities, indicating the importance of otherbacterial coexistence for ecosystem functions by denitrifying bacteria in lake sediments. Keystone taxa of other bacteria showed the highest interactions with denitrifying bacteria; further, a strong significant correlation between keystone taxa with environmental factors and sediment enzyme content revealed by Mantel tests. Specially, total phosphorous was the key environmental factor determining the composition and diversity of nirK and nirS-type denitrifying bacteria in lake sediments, whereas NAR, AmoA, and NIR were the key reductase enzymes directly or indirectly affected to them. Our results provide significant insights into understanding the effects of changing nirK- and nirS-type denitrifying bacterial diversities and underlying community assembly mechanisms under changing environmental conditions in eutrophic lake ecosystems.

Substituent Effects on Cooperativity in Three-Component H-Bond Networks Involving Phenol-Phenol Interactions.

Cooperativity between H-bonding interactions in networks is a fundamental aspect of solvation and self-assembly in molecular systems. The interaction of a series of bisphenols, which make an intramolecular H-bond between the two hydroxyl groups, and quinuclidine was used to quantify cooperativity in three-component networks. The presence of the intramolecular H-bond in the bisphenols was established by using 1H NMR spectroscopy in solution and X-ray crystallography in the solid state. The interactions with quinuclidine were investigated using UV-vis and 1H NMR titrations, which show that the intramolecular hydrogen bonds persist in the 1:1 complexes. By varying substituents on one of the phenol groups, it was possible to measure the effect of changing the strength of the intramolecular H-bond between the hydroxyl groups on the strength of the intermolecular H-bond with quinuclidine. Strong positive cooperativity was observed between the two interactions, with increases in binding free energy of up to 16 kJ mol-1. By varying substituents on the other phenol group, which makes both an intramolecular H-bond and an intermolecular H-bond in the complex, it was possible to measure how the properties of this central hydroxyl group modulate cooperativity between the interactions with the other two functional groups. Changing the polarity of this phenol had no effect on the measured cooperativity. The results indicate that cooperativity in H-bond networks can be understood as a polar interaction between two remote functional groups that is damped by a central functional group. The extent of damping is quantified by cooperativity parameter κ, which is 0.33 for the hydroxyl group and appears to be an intrinsic property of the geometry or polarizability of the functional group rather than polarity.

Soil fungal networks exhibit sparser interactions than bacterial networks in diseased banana plantations.

Soil microorganisms are pivotal in mitigating soil-borne diseases. The intricate mechanisms underlying the interactions among microbes and their impact on disease occurrence remain enigmatic. This study underscores that a reduction in fungal network interactions correlates with the incidence of soil-borne Fusarium wilt.

How Connectivity in Foreign Direct Investment Networks Affects MNE Decision-Making and Performance

The foreign direct investment (FDI) activity of multinational enterprises (MNEs) is inherently a multilateral phenomenon. In the real world, locations rarely receive investments from a single MNE, and MNEs seldom invest in one location. Thus, FDIs create links between locations (e.g., home-host) and connect MNEs with other collocated firms. My dissertation provides insights into how the structural properties of the locations and MNEs, i.e., patterns of relationships and connectivity, influence the decisions and observed behaviors of MNEs. By analyzing MNEs’ interactions in different networks, my dissertation assesses the varying influence of different networks on MNEs’ strategies.

Stochastic step-wise feature selection for Exponential Random Graph Models (ERGMs).

This study introduces a novel methodology for endogenous variable selection in Exponential Random Graph Models (ERGMs) to enhance the analysis of social networks across various scientific disciplines. Addressing critical challenges such as ERGM degeneracy and computational complexity, our method integrates a systematic step-wise feature selection process. This approach effectively manages the intractable normalizing constants characteristic of ERGMs, ensuring the generation of accurate and non-degenerate network models. An empirical application to nine real-life binary networks demonstrates the method's effectiveness in accommodating network dependencies and providing meaningful insights into complex network interactions. Particularly notable is the adaptability of this methodology to both directed and undirected networks, overcoming the limitations of traditional ERGMs in capturing realistic network structures. The findings contribute to network analysis, offering a robust framework for modeling and interpreting social networks and laying a foundation for future advancements in statistical network analysis techniques.