Hub Topology Research Articles

Sex-dependent effects of amyloidosis on functional network hub topology is associated with downregulated neuronal gene signatures in the APPswe/PSEN1dE9 double transgenic mouse.

Extracellular beta-amyloid (Aβ) is thought to cause impairments in brain-wide functional connectivity, although mechanisms linking Aβ to broader functional network processing remain elusive. In the present study, we evaluated the effects of Aβ on fear memory and functional connectome measures in male and female mice. Middle-aged (9-11mo) double transgenic APP-PS1 mice and age and sex-matched controls were tested on a fear conditioning protocol and then imaged at 11.1 Tesla. Brains were harvested and processed for analysis of Aβ plaques and Iba1 immunolabeling in neocortical areas, hippocampus, and basolateral amygdala. Additional RNA sequencing data from separate age, strain, and sex-matched mice were analyzed for differentially expressed genes (DEGs) and weighted gene co-expression networks. In both male and female mice, we observed increased functional connectivity in a dorsal striatal/amygdala network as a result of Aβ. Increased functional connectivity within this network was matched by increases in APP gene expression, Aβ and Iba1 immunolabeling, and an upregulated cluster of DEGs involved in the immune response. Conversely, the network measure representing node hubness, eigenvector centrality, was increased in prefrontal cortical brain regions, but only in female APP-PS1 mice. This female-specific effect of amyloid was associated with down-regulation of a cluster of DEGs involved in cortical and striatal GABA transmission, anxiogenic responses, and motor activity, in female APP-PS1 mice, but not males. Our results contribute to a growing literature linking between Aβ, immune activation, and functional network connectivity. Furthermore, our results reveal outcomes of Aβ on gene expression patterns in female mice that may contribute to amyloidosis-induced dysregulation of non-cognitive circuitry.

Analyzing effective external interventions for optimizing energy hubs with electric and TS: A numerical study from a network topology perspective

Currently, there has been a notable surge in sabotage targeting critical infrastructures, particularly energy hub systems. External interventions on these infrastructures have significantly affected various loads, including electrical and thermal loads. Considering the significance of cybersecurity in energy hubs, there are high expectations for investigating the role of topology in their measures. The aim of this study is to investigate the impact of cyber sabotage on energy management within the demand sector, with a specific emphasis on the topology of an energy hub system. According to the structure of the desired energy hub that has been mathematically modeled, the CPLEX solver is used as a powerful optimization tool with the mixed integer linear programming (MILP) model, which serves as a framework for optimizing the operation cost of the energy hub. The findings reveal the occurrence of false data injection (FDI) into the real network loads. This inconsistency has led to disruption of energy management in the system. Utilizing considered scenarios, the first of them as the base scenario, representing the system under normal network conditions. The second scenario is modeled an attack vector aimed at the electric load, specifically utilizing FDI tactics with an understanding of the network topology. In the third scenario, attention turns to modeling a thermal load attack vector, utilizing FDI tactics with an understanding of its topology. In the final scenario, the emphasis is placed on designing an FDI-based attack vector that targets electric loads within the network, without prior knowledge of the energy hub's topology. Although in all scenarios where the attack is executed, the measuring devices during peak load indicate values lower than the actual ones, the intensity of the attack on the system is considerable in attacks conducted with knowledge of the energy hub topology. Taking into account the importance of the peak load intervals, the maximum changes in electric load during peak hours in the second scenario are compared to those in the first scenario, attributing them to interventions, representing approximately a 17.4 % difference. Similarly, assuming knowledge of the network topology during peak consumption, the impact of the attack on the thermal loads results in changes of 17.17 %. Additionally, in the fourth scenario compared to the first, the maximum changes in electric load during peak hours are approximately 2 %. In the meantime, the optimal cost has remained consistent across all scenarios, rendering the attacks undetectable to the operator and ultimately demonstrating the effectiveness of the proposed method.

Alterations in the hub structure of whole-brain functional networks in patients with drug-naïve schizophrenia: Insights from electroencephalography-based research.

This study aimed to identify atypical hubs in the whole-brain networks of patients with schizophrenia (SZ) and examine the effects of antipsychotic medications, using electroencephalography (EEG) data. We estimated the functional connectivity across all electrodes by applying the phase lag index to the EEG signals of 21 drug-naïve patients with SZ and 31 age-matched healthy controls. Betweenness centrality (BC), a measure of hub status, was calculated for each electrode and frequency band. Data from 14 patients were re-evaluated after initiating treatment with antipsychotic medications. BC values decreased significantly at the Fz site in the beta band, decreased significantly at Pz in the gamma band, and increased significantly at O1 in the gamma band among patients with SZ. These changes persisted after antipsychotic treatment and were unrelated to clinical symptoms. The abnormal hub topology we observed, especially in the high-frequency band, may reflect the pathophysiology of SZ, and this study highlights the utility of BC analysis of EEG data for detecting alterations in the whole-brain networks of patients with SZ.

Multistability of synchronous modes in a multimachine power grid with a common load and their global and non-local stability

The purpose of this work is studying the dynamics of the power grid consisting of an arbitrary number of synchronous generators supplying a common passive linear load. We focus on searching the conditions for the existence and stability of synchronous modes, i.e. the main operating modes of a power grid. The possibility of the existence of non-synchronous (quasi-synchronous and asynchronous) modes is investigated. Methods. To study the dynamics of a power grid we use the effective network model in the form of an ensemble of globally coupled nodes-generators. The state of every node is described by the swing equation. The approach for reducing the effective network to the network with a hub topology (star topology) is proposed. We use numerical methods to construct a partition of the parameter space into areas with different operating modes of the power grid. Results. The conditions for the existence, stability and multistability of synchronous modes are obtained. The main characteristics of these modes are considered, such as the power supplied by generators to the grid and the distribution of currents along transmission lines. We constructed the partition of the power gird parameter space into areas with different dynamics. Conclusion. The power grid consisting of an arbitrary number of synchronous generators supplying a common passive linear load has been studied. We shown the presence of two types of synchronous modes: homogeneous and inhomogeneous. The first is characterized by equal powers and currents flowing through all load supply paths except one. The second provides another additional path, which differs from the others in current and transmitted power. Moreover, the currents flowing along the same path, but in various modes, differ. The presence of high multistability of inhomogeneous synchronous modes has been established. The possibility of coexistence of homogeneous and inhomogeneous synchronous modes, as well as quasi-synchronous and asynchronous modes, is shown. In the power grid parameters space we found areas corresponding both the existence of only synchronous modes and their coexistence with quasi-synchronous and/or asynchronous modes.

Rich-club reorganization of functional brain networks in acute mild traumatic brain injury with cognitive impairment.

Mild traumatic brain injury (mTBI) is typically characterized by temporally limited cognitive impairment and regarded as a brain connectome disorder. Recent findings have suggested that a higher level of organization named the "rich-club" may play a central role in enabling the integration of information and efficient communication across different systems of the brain. However, the alterations in rich-club organization and hub topology in mTBI and its relationship with cognitive impairment after mTBI have been scarcely elucidated. Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from 88 patients with mTBI and 85 matched healthy controls (HCs). Large-scale functional brain networks were established for each participant. Rich-club organizations and network properties were assessed and analyzed between groups. Finally, we analyzed the correlations between the cognitive performance and changes in rich-club organization and network properties. Both mTBI and HCs groups showed significant rich-club organization. Meanwhile, the rich-club organization was aberrant, with enhanced functional connectivity (FC) among rich-club nodes and peripheral regions in acute mTBI. In addition, significant differences in partial global and local network topological property measures were found between mTBI patients and HCs (P<0.01). In patients with mTBI, changes in rich-club organization and network properties were found to be related to early cognitive impairment after mTBI (P<0.05). Our findings suggest that such patterns of disruption and reorganization will provide the basic functional architecture for cognitive function, which may subsequently be used as an earlier biomarker for cognitive impairment after mTBI.

Localization phase transition in stochastic dynamics on networks with hub topology

Dynamics among central sources (hubs) providing a resource and large number of components enjoying and contributing to this resource describes many real life situations. Modeling, controlling, and balancing this dynamics is a challenging problem that arises in many scientific disciplines. We analyze a stochastic dynamical system exhibiting this dynamics with a multiplicative noise. We show that this model can be solved exactly by passing to variables that describe the mass ratio between the components and the hub. We derive a deterministic equation for the average mass ratio in the absence of noise on the hub. This equation describes logistic growth. We derive the phase diagram of the model with and without noise on the hub. We show that when there in no noise on the hub there is no localization phase. In the presence of noise on the hub, we identify two regimes by deriving the equilibrium distribution of the process. The first regime describes balance between the non-hub components and the hub, in the second regime the resource is concentrated mainly on the hub. We generalize the results to a system with multiple hubs. We show that there is less concentration on the hubs as the number of hubs increases, and in the limit of infinite hubs the average mass ratio grows or decays exponentially. Surprisingly, in the limit of large number of components the transition values do not depend on the amount of resource given by the non-hub nodes. We propose an interesting application of this model in the context of porous media using Magnetic Resonance (MR) techniques.

PC-FACS

PC-FACS

Functional and neurochemical disruptions of brain hub topology in chronic pain.

A critical component of brain network architecture is a robust hub structure, wherein hub regions facilitate efficient information integration by occupying highly connected and functionally central roles in the network. Across a wide range of neurological disorders, hub brain regions seem to be disrupted, and the character of this disruption can yield insights into the pathophysiology of these disorders. We applied a brain network-based approach to examine hub topology in fibromyalgia, a chronic pain condition with prominent central nervous system involvement. Resting state functional magnetic resonance imaging data from 40 fibromyalgia patients and 46 healthy volunteers, and a small validation cohort of 11 fibromyalgia patients, were analyzed using graph theoretical techniques to model connections between 264 brain regions. In fibromyalgia, the anterior insulae functioned as hubs and were members of the rich club, a highly interconnected nexus of hubs. In fibromyalgia, rich-club membership varied with the intensity of clinical pain: the posterior insula, primary somatosensory, and motor cortices belonged to the rich club only in patients with the highest pain intensity. Furthermore, the eigenvector centrality (a measure of how connected a region is to other highly connected regions) of the posterior insula positively correlated with clinical pain and mediated the relationship between glutamate + glutamine (assessed by proton magnetic resonance spectroscopy) within this structure and the patient's clinical pain report. Together, these findings reveal altered hub topology in fibromyalgia and demonstrate, for the first time to our knowledge, a neurochemical basis for altered hub strength and its relationship to the perception of pain.

Altered brain connectivity in sudden unexpected death in epilepsy (SUDEP) revealed using resting-state fMRI.

The circumstances surrounding SUDEP suggest autonomic or respiratory collapse, implying central failure of regulation or recovery. Characterisation of the communication among brain areas mediating such processes may shed light on mechanisms and noninvasively indicate risk. We used rs-fMRI to examine network properties among brain structures in people with epilepsy who suffered SUDEP (n = 8) over an 8-year follow-up period, compared with matched high- and low-risk subjects (n = 16/group) who did not suffer SUDEP during that period, and a group of healthy controls (n = 16). Network analysis was employed to explore connectivity within a 'regulatory-subnetwork' of brain regions involved in autonomic and respiratory regulation, and over the whole-brain. Modularity, the extent of network organization into separate modules, was significantly reduced in the regulatory-subnetwork, and the whole-brain, in SUDEP and high-risk. Increased participation, a local measure of inter-modular belonging, was evident in SUDEP and high-risk groups, particularly among thalamic structures. The medial prefrontal thalamus was increased in SUDEP compared with all other control groups, including high-risk. Patterns of hub topology were similar in SUDEP and high-risk, but were more extensive in low-risk patients, who displayed greater hub prevalence and a radical reorganization of hubs in the subnetwork. SUDEP is associated with reduced functional organization among cortical and sub-cortical brain regions mediating autonomic and respiratory regulation. Living high-risk subjects demonstrated similar patterns, suggesting such network measures may provide prospective risk-indicating value, though a crucial difference between SUDEP and high-risk was altered connectivity of the medial thalamus in SUDEP, which was also elevated compared with all sub-groups. Disturbed thalamic connectivity may reflect a potential non-invasive marker of elevated SUDEP risk.

Superstructural approach to the synthesis of free-cooling system through an integrated chilled and cooling water network

Chillers are major energy consumers in industrial facilities. They are indispensable in such industries as semiconductor fabrication, food processing, and plastics manufacturing, among others. Previous studies aimed at improving the energy efficiency of chilled water systems have focused on optimizing the performance of individual chillers. However, an alternative method to recover energy is to perform system-wide water source/sink integration using a superstructural approach. In our previous study, several schemes for chilled and cooling water systems (CCWS) with hub topology were proposed for energy savings. The main contribution of this study is in the development of a methodology to achieve energy savings by introducing free cooling in an integrated superstructure for CCWS. Two examples are used to demonstrate three different scenarios of CCWS with free cooling. It is shown that the integration of free cooling into chilled water system improve the cost and energy saving significantly, and can avoid the need to invest in a new chiller and/or cooling tower to enhance the energy efficiency of CCWS.

Pancreatic Cancer: Insights from Counterterrorism Theories

Recently, a molecular tumor profile analyzed at our medical institution evoked an uncommon communications hub in one of the molecular pathway networks. The patient was a multiyear survivor of pancreatic cancer, and the oncologist requested molecular analyses that would assist in treatment decisions. The hub was noticed because of its topological similarity to optimal terrorist networks that are resilient against attack. Although the hub's topology could have been simply a methodological artifact, its presence did support the consulting pathologist's recommendation that the oncologist refrain from overstimulating the patient's active immune system. In addition, the terrorism/cancer analogy sparked investigation into environments that neutralize covert networks; this led to novel hypotheses about cancer prevention and control for further research. Despite parallels between the “war on cancer” and the “war on terrorism,” there has been very little crossover work between biomedical researchers and researchers in military intelligence. Here is an example of how analytical methods based on infrastructure similarities between molecular interaction pathways and terrorism networks support preclinical research and medical decision making for diseases that have progressed beyond standard-of-care treatments.

Research on Topology Optimization Design Based on Finite Unit Analysis of the Flywheel Hub

Topology optimization design is to ensure the normal functioning of the machine, remove the invalid element structure makes the best structure to maintain the structure and keep the stress or strain level close to the same in each part of the security configuration, the pursuit of the best efficiency, lightest weight , smallest, or the longest service life and so on. Traditional structural optimization design one or several parameters set as the primary determination. This method only to the extent required. With the development and analysis of the efficiency of the computer, we have introduced in the design of finite element analysis. This article uses the basic evolutionary structural optimization method In this paper, load the hub topology optimization analysis of different groups.

A note on an extended fuzzy bi-level optimization approach for water exchange in eco-industrial parks with hub topology

In our previous paper, a fuzzy bi-level programming model was developed to determine optimal interplant water integration networks in eco-industrial parks (EIPs). This approach allowed the appropriate incentive mechanisms, in the form of fresh water and effluent fees as well as water reuse subsidies, to be optimized from the perspective of the EIP authority. This work extends the original mathematical model by modifying the role of the EIP authority to include water regeneration and redistribution via a centralized hub. The resulting fuzzy bi-level programming model may then be solved to yield a “satisficing” solution that reflects a reasonable compromise between the EIP authority's desire to minimize fresh water usage, and the participating companies’ desire to minimize costs. A case study is used to illustrate the modeling approach.