Network Topology Analysis Research Articles

Deciphering Molecular Mechanisms of Cutaneous Leishmaniasis, Pathogenesis and Drug Repurposing through Systems Biology

Cutaneous leishmaniasis (CL) is a major health problem caused by an intracellular pathogen of the genus Leishmania. CL results in morphologically distinct skin injuries, ranging from nodules to plaques and ulcers, which persist as a recuperating incessant injury depending on the type of contaminating parasite. There is still no effective treatment to reduce the skin lesions in patients infected with CL. The aim of this study was to develop strategies to treat skin lesions in CL patients. We retrieved the transcriptomic data of skin lesions from patients with CL and normal skin from the gene Expression Omnibus (GEO) database. The protein-protein interaction network (PPIN) was constructed using the STRING database and Cytoscape v3.10.1 software. Critical genes were identified by topological network analysis and cluster detection. Finally, gene ontology and repurposing drugs for critical genes were determined. CD8A, IFNG, IL-6, PTPRC, CCR7, TLR2, GSTA5, CYBB, IL-12RB2, ITGB2, FCGR3A, CTLA4, and IFNG were identified as the critical genes in PPIN and subnetworks. Enrichment analysis revealed that T-cell receptor signaling, toll-like receptor signaling, cytokine-cytokine receptor interaction, graft-versus-host disease, leishmaniasis, chemokine signaling, primary immunodeficiency, and Th17 cell differentiation were the major pathways associated with critical genes. The drug repurposing results identified cyclosporine, rituximab, infliximab, blinatumomab, and methylprednisolone as candidates for treatment of CL. After validating our model with available experimental data, we found that critical molecules and drug candidates play a crucial role in the treatment of skin lesions caused by Leishmania in prospective studies.

Exploring the mechanism of Liang Xue Wu Hua Tang in the treatment of rosacea via network pharmacology and molecular docking.

Rosacea is a chronic and recurrent inflammatory skin disease affecting the center of the face that causes burning and itching sensations and changes in aesthetics. Liang Xue Wu Hua Tang (LXWHT) is a classic herbal formulation that is efficacious and has been widely used in the clinical treatment of rosacea; however, the pharmacological mechanisms remain unclear. The aim of the present study was to investigate the mechanism of action of LXWHT using network pharmacology and molecular docking. The Traditional Chinese Medicine System Pharmacology database was searched to identify the active ingredients and pharmacological targets of LXWHT, and the GeneCard, Disgenet, and Gene Expression Omnibus databases were applied to screen rosacea-related targets. Cytoscape software was used to visualize the protein-protein interaction network, and network topology analysis was used to identify core targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed for the core targets. Molecular docking simulations and visualization were performed using Maestro and PyMOL, respectively. A total of 43 active compounds and 28 potential targets for LXWHT treatment of rosacea were selected for analysis. The Gene Ontology/Kyoto Encyclopedia of Genes and Genomes results indicated that LXWHT may exert therapeutic effects on rosacea by intervening in immune pathways including tumor necrosis factor pathway, interleukin-17 pathways, and Toll-like receptor signaling pathways. Chemokine ligand 2, interferon-γ, interleukin-1ß, peroxisome proliferator-activated receptor-γ, and matrix metallopeptidase 9 may be the core therapeutic target. Quercetin, stigmasterol, kaempferol, beta-sitosterol, luteolin, beta-carotene, baicalein, acetin, and isorhamnetin were predicted to be the key active ingredients. LXWHT may exert therapeutic effects in the treatment of rosacea by modulating immunity and angiogenesis, laying the foundation for further research.

Analisis Keamanan Jaringan Menggunakan Mikrotik Pada Lab Komputer STMIK Widuri

This study discusses the network security analysis using MikroTik devices in the computer laboratory of STMIK Widuri. The main objective of this research is to evaluate the level of network security in the computer laboratory by implementing appropriate configurations using MikroTik devices. The methods employed include literature review on network security, analysis of network topology in the laboratory, and implementation of security solutions using MikroTik devices. Data collected include security testing results, network performance, and user satisfaction levels. The research findings indicate that the implementation of security solutions with MikroTik effectively enhances network security in the computer laboratory of STMIK Widuri. This study contributes to a practical understanding of using MikroTik in improving network security in campus environments

Zebrafish model and network pharmacology integrated to investigate the possible therapeutic targets of 6′-O-Caffeoylarbutin on anti-inflammatory

6′-O-Caffeoylarbutin (CA) is the most abundant compound found within Vaccinium dunalianum Wight, which is used as a traditional Chinese herbal tea for its effects in lowering uric acid and anti-rheumatoid arthritis. No reports to date, however, have explored the pharmacological impact of CA on inflammatory activity. In this study, the anti-inflammatory targets and molecular mechanisms of CA were evaluated through zebrafish inflammation model, network pharmacology and molecular docking. The results showed that CA was able to inhibit cyclooxygenase (COX-2/1) at a dose-dependent fashion in 12-O-tetradecanoylphorbol-13-acetate (TPA)-treated zebrafish. Network pharmacology analyses was employed to derive 156 putative CA-related anti-inflammatory targets, which were subjected to functional enrichment analyses to obtain 511 associated Gene Ontology (GO) terms and 180 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Moreover, 9 core targets (HRAS, SRC, MMP9, HSP90AA, CASP, ANXA5, EGFR, ESR1, and AKT1) associated with the anti-inflammatory effect of CA were further selected and identified based on network topology analyses and molecular docking. Overall, the results of this study suggest that CA exerts its anti-inflammatory effects through a complex mechanism of action, and these findings offer a robust foundation for future in-depth analyses exploring the pharmacological pathways through which CA can prevent rheumatoid arthritis-associated damage.

A topological analysis of Milan historical surface transport networks from 1856 to the present

This research examines the transport networks operating in Milan, Italy, in seven years, from 1856 to 2016. The networks are transformed into graphs and analysed with several techniques from graph theory, including a new centrality index called Icentr. With the help of this index, we identify the nodes, to be considered primary in the transportation network, that are better related both in terms of topology and more interconnected in terms of distance. The findings provide a detailed picture of how the primary nodes have shifted from the city’s inner core to outer areas over the course of the investigated decades, both for the topological case and when the graphs are weighted based on the distance between nodes. Particularly, the effect of distance is more evident in those historical phases when the city expands, creating longer connections between nodes, in contrast to phases when the city becomes denser. The proposed method of analysis appears suitable to be applied to other cities, both for simplicity and effectiveness.

Mechanism of network pharmacology of Erzhi Pill and Erxian Decoction in treating climacteric syndrome with "treating the same disease with different methods": A review.

Network pharmacology and molecular docking methods were used in the present study to clarify the molecular mechanism of two traditional Chinese medicine prescriptions of climacteric syndrome. Based on oral availability and drug similarity, the main active components of Erzhi Pill and Erxian Decoction were screened through the platform of traditional Chinese medicine system pharmacology. The target database of climacteric syndrome was established by using GENECARD, OMIM, PharmGKB, Targets and Drugbank. The "component - target" network diagram was constructed using Cytoscape software (version 3.8.2). Topology analysis, module analysis, and GO and KEGG enrichment analyses were used to explore the core target and action pathway of Erzhi Pill-Erxian Decoction for treating climacteric syndrome of same disease with different treatments. There were 16 active components and 103 corresponding targets found in Erzhi Pill; 69 active components and 121 corresponding targets were found in Erxian Decoction; and 100 potential targets were found in Erzhi Pill and Erxian Decoction. Through network analysis, topology and module analysis, TP53, AKT1, Jun, ESR1, IL1B, CASP3, MMP9, PTGS2, HIF1A, MYC and EGFR could be considered as potential targets of the 2 prescriptions for alleviating climacteric syndrome. The effects of Erzhi pill and Erxian Decoction on climacteric syndrome are mainly in the pathway of lipid and atherosclerosis, AGE-RAGE signaling pathway and PI3K-Akt signaling pathway in diabetic complications. The active components in Erzhi Pill - Erxian Decoction, such as quercetin, show considerable potential as a candidate drug for the treatment of climacteric syndrome.

Proposal of Testing Procedure for Resonance and Ferroresonance Inception Possibility in Instrument Transformers

This paper deals with the possibility of ferroresonance occurence in the interaction between circuit breakers and inductive instrument transformers. Existing standards lack guidance on testing for ferroresonant behaviour. The paper proposes a standardized testing procedure and presents measurements on a full-scale system. EMTP simulations complement the measurements for a broader network topology analysis, i.e. circuit breaker capacitance combinations. EMTP simulations are validated for a 170 kV voltage transformer and a combined instrument transformer, showing accuracy within 10%. The paper also extends the EMTP modelling application to a 420 kV voltage power transformer during design phase, ensuring it doesn't experience ferroresonance. This study offers a practical approach for testing and simulating ferroresonance in inductive instrument transformers, contributing to the safe operation of power networks.

Potential anti-liver cancer targets and mechanisms of kaempferitrin based on network pharmacology, molecular docking and experimental verification

AimKaempferitrin is an active component in Chenopodium ambrosioides, showing medicinal functions against liver cancer. This study aimed to identify the potential targets and pathways of kaempferitrin against liver cancer using network pharmacology and molecular docking, and verify the essential hub targets and pathway in mice model of SMMC-7721 cells xenografted tumors and SMMC-7721 cells. MethodsKaempferitrin therapeutical targets were obtained by searching SwissTargetPrediction, PharmMapper, STITCH, DrugBank, and TTD databases. Liver cancer specific genes were obtained by searching GeneCards, DrugBank, TTD, OMIM, and DisGeNET databases. PPI network of “kaempferitrin-targets-liver cancer” was constructed to screen the hub targets. GO, KEGG pathway and MCODE clustering analyses were performed to identify possible enrichment of genes with specific biological subjects. Molecular docking and molecular dynamics simulation were employed to determine the docking pose, potential and stability of kaempferitrin with hub targets. The potential anti-liver cancer mechanisms of kaempferitrin, as predicted by network pharmacology analyses, were verified by in vitro and in vivo experiments. Results228 kaempferitrin targets and 2186 liver cancer specific targets were identified, of which 50 targets were overlapped. 8 hub targets were identified through network topology analysis, and only SIRT1 and TP53 had a potent binding activity with kaempferitrin as indicated by molecular docking and molecular dynamics simulation. MCODE clustering analysis revealed the most significant functional module of PPI network including SIRT1 and TP53 was mainly related to cell apoptosis. GO and KEGG enrichment analyses suggested that kaempferitrin exerted therapeutic effects on liver cancer possibly by promoting apoptosis via p21/Bcl-2/Caspase 3 signaling pathway, which were confirmed by in vivo and in vitro experiments, such as HE staining of tumor tissues, CCK-8, qRT-PCR and Western blot. ConclusionThis study provided not only insight into how kaempferitrin could act against liver cancer by identifying hub targets and their associated signaling pathways, but also experimental evidence for the clinical use of kaempferitrin in liver cancer treatment.

Experience-dependent regulation of dopaminergic signaling in the somatosensory cortex

Dopamine critically influences reward processing, sensory perception, and motor control. Yet, the modulation of dopaminergic signaling by sensory experiences is not fully delineated. Here, by manipulating sensory experience using bilateral single-row whisker deprivation, we demonstrated that gene transcription in the dopaminergic signaling pathway (DSP) undergoes experience-dependent plasticity in both granular and supragranular layers of the primary somatosensory (barrel) cortex (S1). Sensory experience and deprivation compete for the regulation of DSP transcription across neighboring cortical columns, and sensory deprivation-induced changes in DSP are topographically constrained. These changes in DSP extend beyond cortical map plasticity and influence neuronal information processing. Pharmacological regulation of D2 receptors, a key component of DSP, revealed that D2 receptor activation suppresses excitatory neuronal excitability, hyperpolarizes the action potential threshold, and reduces the instantaneous firing rate. These findings suggest that the dopaminergic drive originating from midbrain dopaminergic neurons, targeting the sensory cortex, is subject to experience-dependent regulation and might create a regulatory feedback loop for modulating sensory processing. Finally, using topological gene network analysis and mutual information, we identify the molecular hubs of experience-dependent plasticity of DSP. These findings provide new insights into the mechanisms by which sensory experience shapes dopaminergic signaling in the brain and might help unravel the sensory deficits observed after dopamine depletion.

Causal network topology analysis: Characterizing causal context for risk management.

The ways that risk assessments are commonly performed in organizations have limitations that undermine their quality. They typically focus on individual risk events one at a time but are weak at integrating their relevant causal context, into decision-making processes. Network topology analysis has previously been applied to address this weakness through quantitatively characterizing the importance of the causal interactions of risk events. However, there remains a lack of both clarity and consistency in terminology, methods, and interpretation of the results of this approach. This paper presents and formalizes causal network topology analysis, a methodology that contributes to (1) characterizing the causal context of a risk event to inform its management, (2) articulating the ontological concepts underpinning a repeatable topology network analysis, and (3) justifying the selection and usage of network metrics for this purpose. The theory and methodology are discussed, and an exemplar application to a mining project feasibility study is presented.

Discovering weak signals of emerging topics with a triple-dimensional framework

In the rapidly evolving landscape of innovation, the early identification of emerging topics is crucial across diverse research domains. This study views weak signals as the preliminary stage of emerging topics and constructs an innovative weak signal triple-dimensional analytical framework to discern nascent emerging topics. The framework uses triads to represent signals by constructing keyword citation networks and establish a collection of novel signals through network topology analysis. Weak signals are subsequently identified by examining the visibility, diffusion and social influence of signals with time-weighted attributes. An altmetrics indicator is employed to formally measure the social influence of weak signals from the perspective of public perception. We apply the proposed framework to the field of gene editing, and the outcomes of literature analysis and dynamic validation substantiate the efficacy of our approach. Compared to related methods, our framework demonstrates a more nuanced ability to distinguish between various signals, identifying more weak signals and research topics with increased potential for social impact. This research provides valuable insights for strategic decision-making, innovation management, and future foresight.

A dynamic topology analysis method for multi-ship encounters based on multi time-space network trees

This paper innovatively proposes a novel approach of topological analysis in the dynamic time-space domain of ship encounters under the joint action of multi-space network structural elements, based on the GIS spatial information platform and spatial topology analysis theory. The proposed method based on the ship's navigational motion information, encounter dynamic mode, relative time-space position distribution, etc., the method divides and intersects the time-space domain of the ship's encounter dynamics, and establishes an encountering dynamic time-space network tree in which space and attribute elements are collaboratively associated during the navigation. From the perspective of network topology analysis, the high-precision analysis of the spatial coupling characteristics and time-space trends of potential encountered dangers during ships dynamic navigation is achieved. To verify the effectiveness of the method, real encounter scenarios of M/T SANCHI and M/V CF Crystal were used as analysis cases. The results showed that the proposed method can precisely extract spatial relationships and spatio-temporal coupling feature information of potential hazards encountered between ships, with an average error of about 2.54% and an overall error between 1.94% and 3.53%.Simultaneously, the method's time efficiency results are thoroughly studied and compared, and it is discovered that the proposed method has good stability.

Exploring the Mechanisms of Yuanhu Zhitong Oral Liquid for Primary Dysmenorrhea through Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation

Objective: Primary dysmenorrhea (PD) is a prevalent gynecological disorder. Yuanhu Zhitong oral liquid (YHZT) presents a promising alternative treatment for PD. However, the mechanisms underlying its efficacy remain unclear. This study aims to investigate the potential targets and mechanisms of action of YHZT in treating PD using network pharmacology, molecular docking, and molecular dynamics simulations. Methods: Potential compounds from YHZT were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and the Traditional Chinese Medicine Information Database (TCMID). The relevant targets of these compounds were identified using the similarity ensemble approach (SEA) and the Swiss Target Prediction database. PD-related targets were retrieved from the Genecards, DrugBank, and Disgenet databases. ClusterProfiler was utilized for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The compound-target-pathway (CTP) network was constructed to facilitate the identification of key compounds, core targets, and signaling pathways. Finally, molecular docking and molecular dynamics simulations were performed to evaluate the interactions between the targets and compounds. Results: A total of 153 putative compounds and 129 targets of YHZT were identified. Network topology analysis revealed eight core targets and six key compounds. The effects of YHZT were mediated by genes associated with hormone and steroid metabolism, as well as pathways involved in steroid hormone biosynthesis and cytochrome P450 enzymes. Docking results showed free-binding energies ranging from -6.06 to -10.85 kcal/mol, indicating strong binding affinity between the compounds and targets. Molecular dynamics simulation results further confirmed the stability of these interactions. Conclusion: This study demonstrates that YHZT treats PD by suppressing inflammatory reactions and modulating hormone and cytochrome P450 concentrations. Key compounds such as ferulic acid, (R)-canadine, (S)-canadine, canadine, and asristolone are implicated in this process. These findings offer insights into the mechanisms underlying the action of YHZT and provide a foundation for further research in this area.

Analysis of mechanism of core points in acupuncture and moxibustion treatment for epilepsy based on data mining.

To explore the mechanism of core points in acupuncture and moxibustion treatment for epilepsy by using data mining technique, so as to provide a reference for clinical practice and experimental research. The data comes from relevant documents collected from CNKI, Wanfang, SinoMed, VIP, PubMed, Embase, Cochrane Library, EBSCO, Web of Science databases. The selected acupoints were analyzed in descriptive statistics, high-frequency acupoints group and core acupoint prescription. Further, potential target mining, "core acupoint prescription-target-epilepsy" network construction, protein-protein interactions (PPI) network establishment and core target extraction, gene ontology (GO) and KEGG gene enrichment analysis of the core acupoint prescription were carried out to predict its anti-epileptic potential mechanism. A total of 122 acupoint prescriptions were included. The core acupoint prescriptions were Baihui (GV20), Hegu (LI4), Neiguan (PC6), Shuigou (GV26) and Taichong (LR3). 277 potential targets were identified, among which 134 were shared with epilepsy. The core targets were extracted by PPI network topology analysis, including signal transducer and activator of transcription 3, tumor necrosis factor (TNF), interleukin (IL)-6, protein kinase B1, c-Jun N-terminal kinase, brain-derived neurotrophic factor, tumor protein 53, vascular endothelial growth factor A, Caspase-3, epidermal growth factor receptor, etc. The main anti-epileptic pathways of the core acupoints were predicted by KEGG enrichment, including lipid and atherosclerosis, neurodegeneration, phosphatidylinositol-3-kinase/protein B kinase signaling pathway, mitogen-activated protein kinase signaling pathway, cyclic adenosine monophosphate signaling pathway, TNF signaling pathway, IL-17 signaling pathway, hypoxia-inducible factor-1 signaling pathway, apoptosis, etc., involving neuronal death, synaptic plasticity, oxidative stress, inflammation and other related biological process. The core acupoint prescription of acupuncture and moxibustion intervention for epilepsy can act on multiple targets and multiple pathways to exert anti-epileptic effects, which can provide a theoretical basis for further clinical application and mechanism research.

Risk-Informed Performance-Based methods for cyber-attack on nuclear power facilities

A new approach is described that offers a Risk-Informed Performance-Based (RIPB) framework for quantifying the risk associated with a cyber-attack on a nuclear power-generating facility. The first part of the method involves 1) the creation of a simplified 10 CFR 73.54 compliant cyber infrastructure, 2) modeling of design basis threats against the network and passive defense of the network and 3) applying the model metrics as inputs into a Bayesian analysis to calculate the exploit probability of a plant controller. The RAVEN code package was used to perform a stochastic calculation to quantify the aleatory uncertainty associated with exploiting a plant controller and produce basic statistics associated with those outputs, such as the standard deviation and standard error. Other tools, such as ADAPT, were also explored, which could be leveraged for direct DPRA analysis of network topology, such that new failure modes or initiating events could be discovered. The second aspect of the RIPB method considers the impact of the controller on the physical plant. This evaluation was conducted by postulating an accident scenario possibly caused by the dynamics of an exploited process controller, initiating that event in a RELAP5 model controlled by the RAVEN risk analysis package, and demonstrating the types of algorithms that can be used to quantify the consequences of the accident scenario. The new two-part method explored in this work provides the uncertainty associated with a cyber-initiating event and the associated consequences of a postulated accident resulting from that exploit, as well as example tools and algorithms for performing the analysis.

Post global financial crisis multiplex financial network structure longevity: Does it predict re-globalization? Empirical investigation for 234 countries

Research background: International capital flows show decreasing trend after each financial crisis as countries become unwilling to invest in risky counterparties. Recent discussions over structural changes within the global financial network suggest that its structure may be still undergoing some changes. Uncovered weaknesses of over-connectedness with unstable un-ally countries during global financial crisis were further highlighted by recent Covid-19 pandemic. However, previous research suggest that important structural changes happened after global financial crisis. Thus, such situation raises a question whether post global financial crisis multiplex network structure is long-term and is it exhibiting re-globalization pattern as suggested by re-globalization megatrend. Purpose of the article: The main objective of the paper is to assess post global financial crisis multiplex financial network structure longevity and to identify whether it exhibits re-globalization pattern. Methods: Multiplex financial network mapping, network topological analysis and structure longevity methods were employed to evaluate network connectedness, topological structural properties of multiplex financial network and its’ structure longevity. 5-layer multiplex financial network was mapped for different types of capital flows for each layer: net direct and portfolio investments in debt, equity and net banking assets for each year in the post global financial crisis period 2009–2020. Each network layer employed bilateral data from up to 234 countries of the world. Next step of research employed a set of network-level measures defining topological features of each network in the period of 2009–2020 in order to capture the trend of structural changes and evidence of re-globalization. The final stage analyzes multiplex financial network structure by layer and country longevity. Findings & value added: Analysis reveals that stock (positions) multiplex financial network aggregate connectedness, i.e., density and value, increased during post- global financial crisis period until Covid-19 pandemic period, thus, suggesting that globalization in terms of stock is continuing. Topological structural properties of multiplex financial network changed as number of strongly and weakly connected countries decreased and more countries became included in network. Longevity analysis of layer and country structure within multiplex financial network reveal that banking and debt investments are increasing since 2018, while equity part is decreasing. Developed countries, i.e., the United Kingdom and Germany, decrease in multiplex financial network structure, while developing, especially from Asia region (i.e., Hong Kong SAR, China and Singapore) increase. Such empirical results support the re-globalization megatrend in terms of investment type and counterparty structure as highlighted by most recent scientific discussion showing that it started early after global financial crisis. Research also uncovers some regional trends of Asia region increasing in investment network structure, while Europe decreasing. As developing countries attract more and more investment and further develop, global cost saving and, thus, returns from global investment into these countries may be decreasing, resulting in lower gain from globalization. Our analysis may facilitate investment strategy decisions by suggesting that even though gains from globalization might be decreasing, instead of localization, countries could follow ally investment strategy to manage the risk of over-dependency from unstable counterparty while preserving globalization wealth.

Detecting the horizontal/vertical price relationship patterns in the global oil industry chain through network analysis

The investigation of price relationship patterns within the horizontal regional and vertical industry chain domains of oil market represents a crucial yet under-researched area. This study tackles the inherent complexities in identifying these patterns, arising from three key challenges: the presence of numerous downstream petrochemical products, the interconnectedness of oil product prices across two domains, and the existence of price influence loop. To address these challenges, this study selected 51 oil products from various regions and different segments of oil industry chain, and calculated and tested their price lead-lag relationships. Subsequently, we established and analyzed the price lead-lag relationship networks within two domains. Furthermore, we expanded network topological structure analysis from a single domain to encompass both domains. Finally, employing the network motif analysis method, we successfully detected the price relationship patterns, taking into consideration the intricate nature of price influence loops. Our findings illuminate the general characteristics of the oil market within two domains but also shed light on previous ignored price lead-lag relationships. The thorough analysis and conclusions drawn from this study offer detailed policy implications to downstream refineries and policy makers.

Systems and Computational Screening identifies SRC and NKIRAS2 as Baseline Correlates of Risk (CoR) for Live Attenuated Oral Typhoid Vaccine (TY21a) associated Protection

AimWe investigated the molecular underpinnings of variation in immune responses to the live attenuated typhoid vaccine (Ty21a) by analyzing the baseline immunological profile. We utilized gene expression datasets obtained from the Gene Expression Omnibus (GEO) database (accession number: GSE100665) before and after immunization. We then employed two distinct computational approaches to identify potential baseline biomarkers associated with responsiveness to the Ty21a vaccine. Main methodsThe first pipeline (knowledge-based) involved the retrieval of differentially expressed genes (DEGs), functional enrichment analysis, protein-protein interaction network construction, and topological network analysis of post-immunization datasets before gauging their pre-vaccination expression levels. The second pipeline utilized an unsupervised machine learning algorithm for data-driven feature selection on pre-immunization datasets. Supervised machine-learning classifiers were employed to computationally validate the identified biomarkers. Key findingsBaseline activation of NKIRAS2 (a negative regulator of NF-kB signalling) and SRC (an adaptor for immune receptor activation) was negatively associated with Ty21a vaccine responsiveness, whereas LOC100134365 exhibited a positive association. The Stochastic Gradient Descent (SGD) algorithm accurately distinguished vaccine responders and non-responders, with 88.8%, 70.3%, and 85.1% accuracy for the three identified genes, respectively. SignificanceThis dual-pronged novel analytical approach provides a comprehensive comparison between knowledge-based and data-driven methods for the prediction of baseline biomarkers associated with Ty21a vaccine responsiveness. The identified genes shed light on the intricate molecular mechanisms that influence vaccine efficacy from the host perspective while pushing the needle further towards the need for development of precise enteric vaccines and on the importance of pre-immunization screening.

Topological analysis of roadway and railway networks of the Ukrainian-Polish borderlands (on the example of Lviv Oblast and Subcarpathian Voivodeship)


 
 
 The paper presents an analysis of functioning of roadway and railway networks in the context of logistics flows. The interaction of road vehicles and railroad cars within the given territories was characterized. The provided spatiotemporal modelling allows comparing the configuration of roadways and railways from the peripheral settlements to the regional capitals. The points that form transport links with the administrative centres of each studied territory were identified. A comparative topological analysis of the given lines of roadway and railway transport within the Ukrainian-Polish borderland employed quantitative (distance, time) and qualitative (curvature, travel speed) modelling parameters, characterizing the relationship of the borderland territories in two neighbouring countries of Eastern Europe. Relative indicators, which include curvature and speed, were estimated. A database of settlements based on accessibility to the city by road and rail transport was created, taking into account the top-10 centres of territorial communities, or hromadas, in Lviv Oblast and Subcarpathian Voivodeship. Alternative modes of transport for travelling from a centre of territorial community to the regional centre in Ukraine and Poland were highlighted. The study compared the settlements with low transport accessibility to the regional capital (oblast, voivodeship), taking into account the functioning of the roadway and railway networks. Social-geographical problems of the given territories were identified based on the analysis of topological indicators of each transport connections. I found that the network system of transport infrastructure in Subcarpathian Voivodeship is low-dense, especially in mountainous areas. Also, there was analyzed high accessibility of suburban settlements to the city of Rzeszów. In Lviv, connection between the suburbs and the city centre can be called problematic. Within the studied borderland areas, there were also found cases of disuse of the existing railway stations for passenger traffic. Variants that would promote the development of public transport in the Lviv Oblast have been proposed, based on the example of the transport model in Subcarpathian Voivodeship. Applied developments include the need to build the Opillia-Roztocze highway, assignement of high-speed electric trains from remote areas to the regional capital.
 
 

Deep Structural Knowledge Exploitation and Synergy for Estimating Node Importance Value on Heterogeneous Information Networks

The classic problem of node importance estimation has been conventionally studied with homogeneous network topology analysis. To deal with practical network heterogeneity, a few recent methods employ graph neural models to automatically learn diverse sources of information. However, the major concern revolves around that their fully adaptive learning process may lead to insufficient information exploration, thereby formulating the problem as the isolated node value prediction with underperformance and less interpretability. In this work, we propose a novel learning framework namely SKES. Different from previous automatic learning designs, SKES exploits heterogeneous structural knowledge to enrich the informativeness of node representations. Then based on a sufficiently uninformative reference, SKES estimates the importance value for any input node, by quantifying its informativeness disparity against the reference. This establishes an interpretable node importance computation paradigm. Furthermore, SKES dives deep into the understanding that "nodes with similar characteristics are prone to have similar importance values" whilst guaranteeing that such informativeness disparity between any different nodes is orderly reflected by the embedding distance of their associated latent features. Extensive experiments on three widely-evaluated benchmarks demonstrate the performance superiority of SKES over several recent competing methods.