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Brain network hubs are both highly connected and highly inter-connected, forming a critical communication backbone for coherent neural dynamics. The mechanisms driving this organization are poorly understood. Using diffusion-weighted magnetic resonance imaging in twins, we identify a major role for genes, showing that they preferentially influence connectivity strength between network hubs of the human connectome. Using transcriptomic atlas data, we show that connected hubs demonstrate tight coupling of transcriptional activity related to metabolic and cytoarchitectonic similarity. Finally, comparing over thirteen generative models of network growth, we show that purely stochastic processes cannot explain the precise wiring patterns of hubs, and that model performance can be improved by incorporating genetic constraints. Our findings indicate that genes play a strong and preferential role in shaping the functionally valuable, metabolically costly connections between connectome hubs. How genes sculpt the complex architecture of the human connectome remains unclear. Here, the authors show that genes preferentially influence the strength of connectivity between functionally valuable, metabolically costly connections between brain network hubs.

Diffuse gliomas, particularly glioblastomas, are incurable brain tumours 1 . They are characterized by networks of interconnected brain tumour cells that communicate via Ca 2+ transients 2 – 6 . However, the networks’ architecture and communication strategy and how these influence tumour biology remain unknown. Here we describe how glioblastoma cell networks include a small, plastic population of highly active glioblastoma cells that display rhythmic Ca 2+ oscillations and are particularly connected to others. Their autonomous periodic Ca 2+ transients preceded Ca 2+ transients of other network-connected cells, activating the frequency-dependent MAPK and NF-κB pathways. Mathematical network analysis revealed that glioblastoma network topology follows scale-free and small-world properties, with periodic tumour cells frequently located in network hubs. This network design enabled resistance against random damage but was vulnerable to losing its key hubs. Targeting of autonomous rhythmic activity by selective physical ablation of periodic tumour cells or by genetic or pharmacological interference with the potassium channel KCa3.1 (also known as IK1, SK4 or KCNN4) strongly compromised global network communication. This led to a marked reduction of tumour cell viability within the entire network, reduced tumour growth in mice and extended animal survival. The dependency of glioblastoma networks on periodic Ca 2+ activity generates a vulnerability 7 that can be exploited for the development of novel therapies, such as with KCa3.1-inhibiting drugs. A population of highly interconnected cells in glioblastoma makes these tumours resistant to general damage but vulnerable to targeted disruption of this small fraction of cells and their rhythmic Ca 2+ oscillations.

Although complex interactions between hosts and microbial associates are increasingly well documented, we still know little about how and why hosts shape microbial communities in nature. In addition, host genetic effects on microbial communities vary widely depending on the environment, obscuring conclusions about which microbes are impacted and which plant functions are important. We characterized the leaf microbiota of 200 Arabidopsis thaliana genotypes in eight field experiments and detected consistent host effects on specific, broadly distributed microbial species (operational taxonomic unit [OTUs]). Host genetic effects disproportionately influenced central ecological hubs, with heritability of particular OTUs declining with their distance from the nearest hub within the microbial network. These host effects could reflect either OTUs preferentially associating with specific genotypes or differential microbial success within them. Host genetics associated with microbial hubs explained over 10% of the variation in lifetime seed production among host genotypes across sites and years. We successfully cultured one of these microbial hubs and demonstrated its growth-promoting effects on plants in sterile conditions. Finally, genome-wide association mapping identified many putatively causal genes with small effects on the relative abundance of microbial hubs across sites and years, and these genes were enriched for those involved in the synthesis of specialized metabolites, auxins, and the immune system. Using untargeted metabolomics, we corroborate the consistent association between variation in specialized metabolites and microbial hubs across field sites. Together, our results reveal that host genetic variation impacts the microbial communities in consistent ways across environments and that these effects contribute to fitness variation among host genotypes.

Background Microbial interactions shape the structure and function of microbial communities; microbial co-occurrence networks in specific environments have been widely developed to explore these complex systems, but their interconnection pattern across microbiomes in various environments at the global scale remains unexplored. Here, we have inferred an Earth microbial co-occurrence network from a communal catalog with 23,595 samples and 12,646 exact sequence variants from 14 environments in the Earth Microbiome Project dataset. Results This non-random scale-free Earth microbial co-occurrence network consisted of 8 taxonomy distinct modules linked with different environments, which featured environment specific microbial co-occurrence relationships. Different topological features of subnetworks inferred from datasets trimmed into uniform size indicate distinct co-occurrence patterns in the microbiomes of various environments. The high number of specialist edges highlights that environmental specific co-occurrence relationships are essential features across microbiomes. The microbiomes of various environments were clustered into two groups, which were mainly bridged by the microbiomes of plant and animal surface. Acidobacteria Gp2 and Nisaea were identified as hubs in most of subnetworks. Negative edges proportions ranged from 1.9% in the soil subnetwork to 48.9% the non-saline surface subnetwork, suggesting various environments experience distinct intensities of competition or niche differentiation. 2NmSq7Q5noeLTtkrbKwa4L Video abstract Conclusion This investigation highlights the interconnection patterns across microbiomes in various environments and emphasizes the importance of understanding co-occurrence feature of microbiomes from a network perspective.

This paper contributes to the integrated design issue of urban and rural logistics networks under demand uncertainty. A hierarchical hub location model is proposed, which minimizes the expected total system cost by optimizing the locations, number and capacities of “urban-town‒village” hierarchical logistics hubs. The interactions among the logistics hubs and among the hub‒and‒spoke connections, as well as the hub capacity constraints are explicitly considered in the presence of logistics demand uncertainty. A demand scenario‒based branch‒and‒Benders‒cut algorithm is developed to solve the proposed model. A case study of Jiangling urban‒rural region in Hubei province of China is conducted for the illustration of the model and solution algorithm. The results generated by the proposed algorithm are benchmarked against those obtained by GUROBI solver and the practical scheme being currently implemented in the region. The results showed that the proposed methodology can greatly improve the efficiency of the urban‒rural logistics system in terms of expected total system cost. It is important to explicitly model the demand uncertainty, otherwise a significant decision bias may emerge. The proposed algorithm outperforms the GUROBI solver in terms of problem size solved and computational time.

Hub-and-spoke networks play a critical role in reducing cost and enhancing service levels in various infrastructural sectors since hubs act as the consolidation and transshipment points of the flows. The failure of hubs in such a network can cause severe disruptions. While disruptions can be natural or man-made, a disruption by a rational individual or entity can be significantly detrimental to the network and is often studied as an interdiction problem. It is important to take interdiction effects at the design stage; therefore, we study the three-level capacitated hub-and-spoke network design problem from the perspective of a defender who considers the risk of interdiction by a rational attacker. Within the three levels, the upper level represents the network design level, and the lower two levels represent the bi-level hub interdiction problem. The introduction of capacity constraints within an interdiction model dramatically increases the complexity of the problem, as there can be some unfulfilled flows post-interdiction. Moreover, a flow may or may not be fulfilled through the least-cost route using the nearest hubs. This work makes two major contributions: the first contribution is on the efficient handling of the bi-level hub interdiction problem using the Dual-based approach and the Penalty-based approach, and the second contribution is on solving the overall three-level problem using a super valid inequality. These two contributions allow us to solve large-scale versions of the capacitated multiple allocation p-median hub location problem under the risk of interdiction, which is otherwise mathematically intractable and can be handled only using complete enumeration techniques.

Reactive oxygen species (ROS) are key signalling molecules that enable cells to rapidly respond to different stimuli. In plants, ROS play a crucial role in abiotic and biotic stress sensing, integration of different environmental signals and activation of stress-response networks, thus contributing to the establishment of defence mechanisms and plant resilience. Recent advances in the study of ROS signalling in plants include the identification of ROS receptors and key regulatory hubs that connect ROS signalling with other important stress-response signal transduction pathways and hormones, as well as new roles for ROS in organelle-to-organelle and cell-to-cell signalling. Our understanding of how ROS are regulated in cells by balancing production, scavenging and transport has also increased. In this Review, we discuss these promising developments and how they might be used to increase plant resilience to environmental stress.Reactive oxygen species (ROS) signalling is crucial in plant responses to abiotic and biotic stresses. This Review discusses our current understanding of ROS regulation and sensing in plants, key regulatory hubs that connect ROS signalling with other stress-response pathways and how ROS signalling could be harnessed to increase plant resilience to environmental stress.

Hubs are highly connected brain regions important for coordinating processing in brain networks. It is unclear, however, which measures of network “hubness” are most useful in identifying brain regions critical to human cognition. We tested how closely two measures of hubness—edge density and participation coefficient, derived from white and gray matter, respectively—were associated with general cognitive impairment after brain damage in two large cohorts of patients with focal brain lesions (N = 402 and 102, respectively) using cognitive tests spanning multiple cognitive domains. Lesions disrupting white matter regions with high edge density were associated with cognitive impairment, whereas lesions damaging gray matter regions with high participation coefficient had a weaker, less consistent association with cognitive outcomes. Similar results were observed with six other gray matter hubness measures. This suggests that damage to densely connected white matter regions is more cognitively impairing than similar damage to gray matter hubs, helping to explain interindividual differences in cognitive outcomes after brain damage.

Over the past 10 years, transport interchange hubs (TIH) in Russia have turned from projects with a strictly transit purpose into key elements of urban infrastructure modernization, increasingly attracting people's attention and acquiring additional functions. It is worth noting that in the living conditions of a modern metropolis, mobility, speed and ease of movement are the most important criteria for the development of transport infrastructure, and projects to create a TIH, meeting these requirements, give a new impetus to the formation of public spaces where people can receive the necessary services and services without leaving the area of residence. These factors require timely adaptation to the existing situation and the search for new solutions, one of which may be the integration of real estate into the TIH and adjacent territories, which will allow projects to be implemented on more investment-attractive land plots, within walking distance from the metro, MCC, public transport stops. It is assumed that office and shopping centers built in the adjacent territories of the TIH will have a higher demand due to passenger traffic passing through the shopping areas, reducing the time of office users on the road and the advantageous territorial location of the property, which will positively affect the growth of prices for renting and selling these objects and, as a result, on profitability and efficiency of development projects.

Collaboration plays a key role in the success attained to date by networks of innovation ecosystems generated around entities known as Digital Innovation Hubs (DIHs), recently created following European Commission initiatives to boost the digitisation of the European economic fabric. This article proposes a conceptual framework that brings together, defines, structures and relates the concepts involved in the collaborative interaction processes within and between these innovation ecosystems to allow comprehensive conceptualisation. The developed framework also provides an approach that helps to tangibilise collaboration as a management process. Here the goal is to ultimately move towards not only qualitative, but also quantitative modelling to bridge the research gap in the state of the art in this respect. The data-driven business-ecosystem-skills-technology (D-BEST) model, devised to configure DIHs service portfolios in a collaborative context, provides the reference basis for the interorganisational asset transfer methodology (IOATM). This is the keystone that structures the framework and constitutes its main contribution. Through the IOATM, this conceptual framework points out collaboration quantification, and serves as a lever for its modelling to deal with collaboration accounting by: turning it into a more controllable management element; guiding practitioners' efforts to improve collaborative processes efficiency with an approach that pursues objectivity and maximises synergies.