From fat storage to immune hubs: the emerging role of adipocytes in coordinating the immune response to infection.

Adipose tissue is a rich source of diverse cell populations, including immune cells, adipocytes and stromal cells. Interactions between these different cell types are now appreciated to be critical for maintaining tissue structure and function, by governing processes such as adipogenesis, lipolysis and differentiation of white to beige adipocytes. Interactions between these cells also drive inflammation in obesity, leading to an expansion of adipose tissue immune cells, and the secretion of proinflammatory cytokines from immune cells and from adipocytes themselves. However, in evolutionary terms, obesity is a recent phenomenon, raising the question of why adipocytes evolved to express factors that influence the immune response. Studies of various pathogens indicate that adipocytes are highly responsive to infection, altering their metabolic profiles in a way that can be used to release nutrients and fuel the immune response. In the case of infection with the extracellular parasite Trypanosoma brucei, attenuating the ability of adipocytes to sense the cytokine IL-17 results in a loss of control of the local immune response and an increased pathogen load. Intriguingly, comparisons of the adipocyte response to infection suggest that the immune responses of these cells occur in a pathogen-dependent manner, further confirming their complexity. Here, with a focus on murine adipose tissue, we discuss the emerging concept that, in addition to their canonical function, adipocytes are immune signalling hubs that integrate and disseminate signals from the immune system to generate a local environment conducive to pathogen clearance.

Provincial and connector qualities of somatosensory brain network hubs in bipolar disorder.

Brain network hubs are highly connected brain regions serving as important relay stations for information integration. Recent studies have linked mental disorders to impaired hub function. Provincial hubs mainly integrate information within their own brain network, while connector hubs share information between different brain networks. This study used a novel time-varying analysis to investigate whether hubs aberrantly follow the trajectory of other brain networks than their own. The aim was to characterize brain hub functioning in clinically remitted bipolar patients. We analyzed resting-state functional magnetic resonance imaging data from 96 euthymic individuals with bipolar disorder and 61 healthy control individuals. We characterized different hub qualities within the somatomotor network. We found that the somatomotor network comprised mainly provincial hubs in healthy controls. Conversely, in bipolar disorder patients, hubs in the primary somatosensory cortex displayed weaker provincial and stronger connector hub function. Furthermore, hubs in bipolar disorder showed weaker allegiances with their own brain network and followed the trajectories of the limbic, salience, dorsal attention, and frontoparietal network. We suggest that these hub aberrancies contribute to previously shown functional connectivity alterations in bipolar disorder and may thus constitute the neural substrate to persistently impaired sensory integration despite clinical remission.

Neural network architecture of a mammalian brain.

Connectomics research is making rapid advances, although models revealing general principles of connectional architecture are far from complete. Our analysis of 106 published connection reports indicates that the adult rat brain interregional connectome has about 76,940 of a possible 623,310 axonal connections between its 790 gray matter regions mapped in a reference atlas, equating to a network density of 12.3%. We examined the sexually dimorphic network using multiresolution consensus clustering that generated a nested hierarchy of interconnected modules/subsystems with three first-order modules and 157 terminal modules in females. Top-down hierarchy analysis suggests a mirror-image primary module pair in the central nervous system's rostral sector (forebrain-midbrain) associated with behavior control, and a single primary module in the intermediate sector (rhombicbrain) associated with behavior execution; the implications of these results are considered in relation to brain development and evolution. Bottom-up hierarchy analysis reveals known and unfamiliar modules suggesting strong experimentally testable hypotheses. Global network analyses indicate that all hubs are in the rostral module pair, a rich club extends through all three primary modules, and the network exhibits small-world attributes. Simulated lesions of all regions individually enabled ranking their impact on global network organization, and the visual path from the retina was used as a specific example, including the effects of cyclic connection weight changes from the endogenous circadian rhythm generator, suprachiasmatic nucleus. This study elucidates principles of interregional neuronal network architecture for a mammalian brain and suggests a strategy for modeling dynamic structural connectivity.

Detecting and quantifying PM2.5 and NO2 contributions from train and road traffic in the vicinity of a major railway terminal in Dublin, Ireland.

Air pollution from transport hubs is a recognised health concern for local urban inhabitants. Within the domain of transport hubs, significant attention has been given to larger airport and port settings, however concerns have been raised about emissions from urban railway hubs, especially those with diesel trains. This paper presents an approach that adopts low-cost monitoring (LCM) for fixed site monitoring (FSM) to quantify and disaggregate PM2.5 and NO2 contributions from railway station and road traffic on air quality in the vicinity of railway station in Dublin, Ireland. The NO2 sensor showed larger discrepancies than the PM2.5 sensor when compared to the reference monitor. Machine learning models (XGBoost and Random Forest (RF) regression) were applied to calibrate the LCM devices, with the XGBoost model (NO2, R2 = 0.8 and RSME = 9.1 µg/m3 & PM2.5, R2 = 0.92 and RSME = 2.2 µg/m3) deemed more appropriate than the RF model. Local wind conditions, pressure, PM2.5 concentrations, and road traffic significantly impacted NO2 model results, while raw PM2.5 sensor readings greatly influenced the PM2.5 model output. This highlights that the NO2 sensor requires more input data for accurate calibration, unlike the PM2.5 sensor. The monitoring results from the one-month monitoring campaign from May 25, 2023 to June 25, 2023 presented elevated NO2 and PM2.5 concentrations measured at the railway station, which translated to exceedances of the annual WHO limits (PM2.5 = 5 µg/m3, NO2 = 10 µg/m3) by 1.6-1.8 and 3.2-5.2 times respectively at the study site. A subsequent data filtering technique based on wind orientation, revealed that the railway station was the main PM2.5 source and road traffic was the main NO2 source when winds come from the railway station. This study highlights the value of LCM devices alongside robust machine learning techniques to capture air quality in urban settings.

Integration of thermal energy storage for sustainable energy hubs in the forest industry: A comprehensive analysis of cost, thermodynamic efficiency, and availability.

Thermal energy storage (TES) offers a practical solution for reducing industrial operation costs by load-shifting heat demands within industrial processes. In the integrated Thermomechanical pulping process, TES systems within the Energy Hub can provide heat for the paper machine, aiming to minimize electricity costs during peak hours. This strategic use of TES technology ensures more cost-effective and efficient energy consumption management, leading to overall operational savings. This research presents a novel method for optimizing the design and operation of an Energy Hub with TES in the forest industry. The proposed approach for the optimal design involves a comprehensive analysis of the dynamic efficiency, reliability, and availability of system components. The Energy Hub comprises energy conversion technologies such as an electric boiler and a steam generator heat pump. The study examines how the reliability of the industrial Energy Hub system affects operational costs and analyzes the impact of the maximum capacities of its components on system reliability. The method identifies the optimal design point for maximizing system reliability benefits. To optimize the TES system's charging/discharging schedule, an advanced predictive method using time series prediction models, including LSTM (Long Short-Term Memory) and GRU (Gated Recurrent Unit), has been developed to forecast average daily electricity prices. The results highlight significant benefits from the optimal operation of TES integrated with Energy Hubs, demonstrating a 4.5-6 percent reduction in system operation costs depending on the reference year. Optimizing the Energy Hub design improves system availability, reducing operation costs due to unsupplied demand penalty costs. The system's peak availability can reach 98 %, with a maximum heat pump capacity of 2 MW and an electric boiler capacity of 3.4 MW. The GRU method showed superior accuracy in predicting electricity prices compared to LSTM, indicating its potential as a reliable electricity price predictor within the system.

Women's Health Hubs: a rapid mixed-methods evaluation.

Background: Women's sexual and reproductive health needs are complex and vary across the life course. They are met by a range of providers, professionals and venues. Provision is not well integrated, with inequalities in access. In some areas of the United Kingdom Women's Health Hubs have been established to improve provision, experience and outcomes for women, and to address inequalities and reduce costs. These models were established prior to the national implementation of Women's Health Hubs announced in the English 2022 Women's Health Strategy. Objective: To explore the 'current state of the art', mapping the United Kingdom landscape, and studying experiences of delivering and using Women's Health Hubs across England, defining key features and early markers of success to inform policy and practice. Design: A mixed-methods evaluation, comprising three work packages: Mapping the Women's Health Hub landscape and context and developing a definition of Women's Health Hubs, informed by an online national survey of Women's Health Hub leaders, and interviews with regional stakeholders. In-depth evaluation in four hub sites, including interviews with staff and women, focus groups in local communities and documentary analysis. Interviews with national stakeholders and consolidation of findings from work packages 1 and 2. Fieldwork was undertaken from May 2022 to March 2023. The evaluation was initiated prior to the national scale-up of Women's Health Hubs announced in the 2022 Women's Health Strategy. Results: Most areas of the United Kingdom did not have a Women's Health Hub. Seventeen active services were identified, established between 2001 and 2022. Women's Health Hubs were diverse, predominantly GP-led, with different perspectives of the role and definition of a hub. Women using hubs reported positive experiences, finding services caring and convenient. Implementation facilitators included committed, collaborative leaders working across boundaries, sufficient workforce capacity and a supportive policy context. Challenges included access to funding, commissioning, workforce issues, facilities and equipment, stakeholder engagement and wider system integration, priorities and pressures. Leaders were committed to addressing inequalities, but evidence of impact was still emerging. Limitations: It was challenging to locate models; therefore, some may have been missed. Data availability limited assessment of impact, including inequalities. Some population groups were not represented in the data, and the evaluation was more provider-oriented. It was not possible to develop a typology of Women's Health Hubs as planned due to heterogeneity in models. Conclusions: Existing Women's Health Hub models were providing integrated approaches to meet local needs. Many were at an early stage of development. Evidence of system-level impact and costs was still emerging. Women's Health Hubs may widen inequalities if models are more accessible to advantaged groups. The important role of committed leaders in existing 'bottom-up' models may limit scalability and sustainability. Findings suggest that national scale-up will take time and requires funding and that it is necessary to design models according to local needs and resources. In 2023, the Department of Health and Social Care announced funding to establish a Women's Health Hub in every Integrated Care System in England. Future work: Future evaluation should consider system-level impact and costs, explore unintended consequences and test assumptions. Funding: This award was funded by the National Institute of Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR135589) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 30. See the NIHR Funding and Awards website for further award information.

In the National Health Service, care for women's health issues such as heavy periods, menopause, contraception and abortion is provided by different services, such as GPs and hospital gynaecology and sexual health clinics. Services are not always joined up and often women find it hard to access care. To improve care, United Kingdom National Health Service teams have set up Women's Health Hubs. Women's Health Hubs involve a group of health professionals working together to provide more joined-up community-based services to women throughout their lives. This evaluation aimed to explore why, where and how Women's Health Hubs have been set up and what they have achieved and to understand staff and patient experiences. The results will be shared with the government and National Health Service as new Women's Health Hubs are set up. The evaluation included a survey of people who have set up hubs across the United Kingdom and interviews with women's health leaders in England. In four hubs in England, we talked to local women and staff, and reviewed documents. We found 17 hubs, and most areas of the United Kingdom did not have one. Every hub was different, with different views about how hubs should work. Most were set up to improve access and experiences for women, and reduce pressure on other services. Six hubs had involved women in developing their service but most had not. Hubs offered appointments with health professionals, usually in GP or community clinics. The most common services were for coil fitting, menopause and heavy periods. The set-up of hubs was helped by passionate leaders who involved the right people, and identified funding and time. Challenges included National Health Service pressures and a lack of funding, clinic space and staff. Women who have used hubs report a good experience, with caring and convenient services. More work is needed to understand how hubs can improve care for all women, including unfair differences in care.

Cortical hubs of highly superior autobiographical memory.

Highly Superior Autobiographical Memory (HSAM) is a rare form of enhanced memory in which individuals demonstrate an extraordinary ability to remember details of their personal lives with high levels of accuracy and vividness. Neuroimaging studies have identified brain regions - specifically, midline areas within the default network - associated with remembering events from one's past. Extending this research on the neural underpinnings of autobiographical memory, the present study utilizes graph theory analyses to compare functional brain connectivity in a cohort of HSAM (n = 12) and control participants (n = 29). We perform seed-based analysis in resting-state fMRI data to assess how specific cortical regions within the autobiographical memory network are differentially connected in HSAM individuals. Additionally, we apply a whole-brain connectivity analysis to identify differences in brain hub-network topology associated with enhanced autobiographical memory. Seed-based results show converging patterns of increased connectivity in HSAM across midline areas. Whole-brain analysis also reveals enhanced connectivity across medial prefrontal and posterior cingulate cortex in HSAM individuals. Together, these results extend prior research, highlighting cortical hubs within the default network associated with enhanced autobiographical memory.

Harmonizing Microneurography Metadata with Local Data Hubs: A Concept.

This work aims to improve FAIR-ness of the microneurography research by integrating the local (meta)data to existing research data infrastructures. In the previous work, we developed an odML based solution for local metadata storage of microneurography data. However, this solution is limited to a narrow community. As a next step, we propose the integration into the Local Data Hubs, data-sharing services within NFDI4Health infrastructure. We outline a first concept, that streams chosen data from the established odMLtables GUI.

Desiderata for discoverability and FAIR adoption of health data hubs.

BACKGROUND: The future European Health Research and Innovation Cloud (HRIC), as fundamental part of the European Health Data Space (EHDS), will promote the secondary use of data and the capabilities to push the boundaries of health research within an ethical and legally compliant framework that reinforces the trust of patients and citizens. OBJECTIVE: This study aimed to analyse health data management mechanisms in Europe to determine their alignment with FAIR principles and data discovery generating best. practices for new data hubs joining the HRIC ecosystem. In this line, the compliance of health data hubs with FAIR principles and data discovery were assessed, and a set of best practices for health data hubs was concluded. METHODS: A survey was conducted in January 2022, involving 99 representative health data hubs from multiple countries, and 42 responses were obtained in June 2022. Stratification methods were employed to cover different levels of granularity. The survey data was analysed to assess compliance with FAIR and data discovery principles. The study started with a general analysis of survey responses, followed by the creation of specific profiles based on three categories: organization type, function, and level of data aggregation. RESULTS: The study produced specific best practices for data hubs regarding the adoption of FAIR principles and data discoverability. It also provided an overview of the survey study and specific profiles derived from category analysis, considering different types of data hubs. CONCLUSIONS: The study concluded that a significant number of health data hubs in Europe did not fully comply with FAIR and data discovery principles. However, the study identified specific best practices that can guide new data hubs in adhering to these principles. The study highlighted the importance of aligning health data management mechanisms with FAIR principles to enhance interoperability and reusability in the future HRIC.

14-3-3 proteins as a major hub for plant immunity.

14-3-3 proteins, ubiquitously present in eukaryotic cells, are regulatory proteins involved in a plethora of cellular processes. In plants, they have been studied in the context of metabolism, development, and stress responses. Recent studies have highlighted the pivotal role of 14-3-3 proteins in regulating plant immunity. The ability of 14-3-3 proteins to modulate immune responses is primarily attributed to their function as interaction hubs, mediating protein-protein interactions and thereby regulating the activity and overall function of their binding partners. Here, we shed light on how 14-3-3 proteins contribute to plant defense mechanisms, the implications of their interactions with components of plant immunity cascades, and the potential for leveraging this knowledge for crop improvement strategies.

Meso-scale reorganization of local-global brain networks under mild sedation of propofol anesthesia.

The fragmentation of the functional brain network has been identified through the functional connectivity (FC) analysis in studies investigating anesthesia-induced loss of consciousness (LOC). However, it remains unclear whether mild sedation of anesthesia can cause similar effects. This paper aims to explore the changes in local-global brain network topology during mild anesthesia, to better understand the macroscopic neural mechanism underlying anesthesia sedation. We analyzed high-density EEG from 20 participants undergoing mild and moderate sedation of propofol anesthesia. By employing a local-global brain parcellation in EEG source analysis, we established binary functional brain networks for each participant. Furthermore, we investigated the global-scale properties of brain networks by estimating global efficiency and modularity, and examined the changes in meso-scale properties of brain networks by quantifying the distribution of high-degree and high-betweenness hubs and their corresponding rich-club coefficients. It is evident from the results that the mild sedation of anesthesia does not cause a significant change in the global-scale properties of brain networks. However, network components centered on SomMot L show a significant decrease, while those centered on Default L, Vis L and Limbic L exhibit a significant increase during the transition from wakefulness to mild sedation (p<0.05). Compared to the baseline state, mild sedation almost doubled the number of high-degree hubs in Vis L, DorsAttn L, Limbic L, Cont L, and reduced by half the number of high-degree hubs in SomMot R, DorsAttn R, SalVentAttn R. Further, mild sedation almost doubled the number of high-betweenness hubs in Vis L, Vis R, Limbic R, Cont R, and reduced by half the number of high-betweenness hubs in SomMot L, SalVentAttn L, Default L, and SomMot R. Our results indicate that mild anesthesia cannot affect the global integration and segregation of brain networks, but influence meso-scale function for integrating different resting-state systems involved in various segregation processes. Our findings suggest that the meso-scale brain network reorganization, situated between global integration and local segregation, could reflect the autonomic compensation of the brain for drug effects. As a direct response and adjustment of the brain network system to drug administration, this spontaneous reorganization of the brain network aims at maintaining consciousness in the case of sedation.

Modeling and design of solar + storage-powered community resilience hubs across California.

Distributed clean, reliable energy resources like solar plus battery storage (solar + storage) can reduce harmful emissions while supporting resilience. Solar + storage-powered resilience hubs provide energy for critical services during disasters while increasing human adaptive capacity year round. We studied where utility rates, local climate, and historical injustice make solar + storage resilience hubs more valuable and more challenging. We modeled the economic and climate impacts of outfitting candidate hub sites across California with solar + storage for everyday operations and identified designs and costs required to withstand a range of outages considering weather impacts on energy needs and availability. We integrated sociodemographic data to prioritize the siting of resilience hubs, to focus potential policy and funding priorities on regions where solar + storage for resilience hubs is hard or expensive, and where populations are most in need. We identified almost 20,000 candidate buildings with more than 8 GW of total rooftop solar potential capable of reducing CO2 emissions by 5 million tons per year while providing energy for community resilience. Hub capacity for one of the most challenging missions-providing emergency shelter during a power outage and smoke event-could have a statewide average lifetime cost of less than $2000 per seat. We identified regional challenges including insufficient rooftop solar capacity in cities, low sunlight in northern coastal California, and high costs driven by utility rate structures in Sacramento and the Imperial Valley. Results show that rates and net metering rules that incentivize solar + storage during everyday operations decrease resilience costs.

Moving restoration ecology forward with combinatorial approaches.

Our current planetary crisis, including multiple jointly acting factors of global change, moves the need for effective ecosystem restoration center stage and compels us to explore unusual options. We here propose exploring combinatorial approaches to restoration practices: management practices are drawn at random and combined from a locally relevant pool of possible management interventions, thus creating an experimental gradient in the number of interventions. This will move the current degree of interventions to higher dimensionality, opening new opportunities for unlocking unknown synergistic effects. Thus, the high dimensionality of global change (multiple jointly acting factors) would be more effectively countered by similar high-dimensionality in solutions. In this concept, regional restoration hubs play an important role as guardians of locally relevant information and sites of experimental exploration. Data collected from such studies could feed into a global database, which could be used to learn about general principles of combined restoration practices, helping to refine future experiments. Such combinatorial approaches to exploring restoration intervention options may be our best hope yet to achieve decisive progress in ecological restoration at the timescale needed to mitigate and reverse the most severe losses caused by global environmental change.

Transcriptional Hubs Within Cliques in Ensemble Hi-C Chromatin Interaction Networks.

Chromatin conformation capture technologies permit the study of chromatin spatial organization on a genome-wide scale at a variety of resolutions. Despite the increasing precision and resolution of high-throughput chromatin conformation capture (Hi-C) methods, it remains challenging to conclusively link transcriptional activity to spatial organizational phenomena. We have developed a clique-based approach for analyzing Hi-C data that helps identify chromosomal hotspots that feature considerable enrichment of chromatin annotations for transcriptional start sites and, building on previously published work, show that these chromosomal hotspots are not only significantly enriched in RNA polymerase II binding sites as identified by the ENCODE project, but also identify a noticeable increase in FANTOM5 and GTEx transcription within our identified cliques across a variety of tissue types. From the obtained data, we surmise that our cliques are a suitable method for identifying transcription factories in Hi-C data, and outline further extensions to the method that may make it useful for locating regions of increased transcriptional activity in datasets where in-depth expression or polymerase data may not be available.

Multimodal imaging investigation of structural rich club alterations in Alzheimer's disease and mild cognitive impairment: Amyloid deposition, structural atrophy, and functional activation differences.

Alzheimer's disease (AD) is characterized by significant cerebral dysfunction, including increased amyloid deposition, gray matter atrophy, and changes in brain function. The involvement of highly connected network hubs, known as the "rich club," in the pathology of the disease remains inconclusive despite previous research efforts. In this study, we aimed to systematically assess the link between the rich club and AD using a multimodal neuroimaging approach. We employed network analyses of diffusion magnetic resonance imaging (MRI), longitudinal assessments of gray matter atrophy, amyloid deposition measurements using positron emission tomography (PET) imaging, and meta-analytic data on functional activation differences. Our study focused on evaluating the role of both the structural brain network's core and extended rich club regions in individuals with mild cognitive impairment (MCI) and those diagnosed with AD. Our findings revealed that structural rich club regions exhibited accelerated gray matter atrophy and increased amyloid deposition in both MCI and AD. Importantly, these regions remained unaffected by altered functional activation patterns observed outside the core rich club regions. These results shed light on the connection between two major AD biomarkers and the rich club, providing valuable insights into AD as a potential disconnection syndrome.

Imaging extrachromosomal DNA (ecDNA) in cancer.

Extrachromosomal DNA (ecDNA) are circular regions of DNA that are found in many cancers. They are an important means of oncogene amplification, and correlate with treatment resistance and poor prognosis. Consequently, there is great interest in exploring and targeting ecDNA vulnerabilities as potential new therapeutic targets for cancer treatment. However, the biological significance of ecDNA and their associated regulatory control remains unclear. Light microscopy has been a central tool in the identification and characterisation of ecDNA. In this review we describe the different cellular models available to study ecDNA, and the imaging tools used to characterise ecDNA and their regulation. The insights gained from quantitative imaging are discussed in comparison with genome sequencing and computational approaches. We suggest that there is a crucial need for ongoing innovation using imaging if we are to achieve a full understanding of the dynamic regulation and organisation of ecDNA and their role in tumourigenesis.

Local Food System Approaches to Address Food and Nutrition Security among Low-Income Populations: A Systematic Review.

Food and nutrition insecurity disproportionately impact low-income households in the United States, contributing to higher rates of chronic diseases among this population. Addressing this challenge is complex because of various factors affecting the availability and accessibility of nutritious food. Short value chain (SVC) models, informally known as local food systems, offer a systemic approach that aims to optimize resources and align values throughout and beyond the food supply chain. Although specific SVC interventions, such as farmers markets, have been studied individually, a comprehensive review of SVC models was pursued to evaluate their relative impact on food security, fruit and vegetable intake, diet quality, health-related markers, and barriers and facilitators to participation among low-income households. Our systematic literature search identified 37 articles representing 34 studies from 2000-2020. Quantitative, qualitative, and mixed-method studies revealed that farmers market interventions had been evaluated more extensively than other SVC models (i.e., produce prescription programs, community-supported agriculture, mobile markets, food hubs, farm stands, and farm-to-school). Fruit and vegetable intake was the most measured outcome; other outcomes were less explored or not measured at all. Qualitative insights highlighted common barriers to SVC use, such as lack of program awareness, limited accessibility, and cultural incongruence, whereas facilitators included health-promoting environments, community cohesion, financial incentives, and high-quality produce. Social marketing and dynamic nutrition education appeared to yield positive program outcomes. Financial incentives were used in many studies, warranting further investigation into optimal amounts across varying environmental contexts. SVC models are increasingly germane to national goals across the agriculture, social, and health care sectors. This review advances the understanding of key knowledge gaps related to their implementation and impact; it emphasizes the need for research to analyze SVC potential comprehensively across the rural-urban continuum and among diverse communities through long-term studies of measurable health impact and mixed-method studies investigating implementation best practices. This trial was registered at PROSPERO as CRD42020206532.

Hub overload and failure as a final common pathway in neurological brain network disorders.

Understanding the concept of network hubs and their role in brain disease is now rapidly becoming important for clinical neurology. Hub nodes in brain networks are areas highly connected to the rest of the brain, which handle a large part of all the network traffic. They also show high levels of neural activity and metabolism, which makes them vulnerable to many different types of pathology. The present review examines recent evidence for the prevalence and nature of hub involvement in a variety of neurological disorders, emphasizing common themes across different types of pathology. In focal epilepsy, pathological hubs may play a role in spreading of seizure activity, and removal of such hub nodes is associated with improved outcome. In stroke, damage to hubs is associated with impaired cognitive recovery. Breakdown of optimal brain network organization in multiple sclerosis is accompanied by cognitive dysfunction. In Alzheimer's disease, hyperactive hub nodes are directly associated with amyloid-beta and tau pathology. Early and reliable detection of hub pathology and disturbed connectivity in Alzheimer's disease with imaging and neurophysiological techniques opens up opportunities to detect patients with a network hyperexcitability profile, who could benefit from treatment with anti-epileptic drugs.

Soil prokaryotic and fungal biome structures associated with crop disease status across the Japan Archipelago.

Archaea, bacteria, and fungi in the soil are increasingly recognized as determinants of agricultural productivity and sustainability. A crucial step for exploring soil microbiomes with important ecosystem functions is to perform statistical analyses on the potential relationship between microbiome structure and functions based on comparisons of hundreds or thousands of environmental samples collected across broad geographic ranges. In this study, we integrated agricultural field metadata with microbial community analyses by targeting 2,903 bulk soil samples collected along a latitudinal gradient from cool-temperate to subtropical regions in Japan (26.1-42.8 °N). The data involving 632 archaeal, 26,868 bacterial, and 4,889 fungal operational taxonomic units detected across the fields of 19 crop plant species allowed us to conduct statistical analyses (permutational analyses of variance, generalized linear mixed models, randomization analyses, and network analyses) on the relationship among edaphic factors, microbiome compositions, and crop disease prevalence. We then examined whether the diverse microbes form species sets varying in potential ecological impacts on crop plants. A network analysis suggested that the observed prokaryotes and fungi were classified into several species sets (network modules), which differed substantially in association with crop disease prevalence. Within the network of microbe-to-microbe coexistence, ecologically diverse microbes, such as an ammonium-oxidizing archaeon, an antibiotics-producing bacterium, and a potentially mycoparasitic fungus, were inferred to play key roles in shifts between crop-disease-promotive and crop-disease-suppressive states of soil microbiomes. The bird's-eye view of soil microbiome structure will provide a basis for designing and managing agroecosystems with high disease-suppressive functions.IMPORTANCEUnderstanding how microbiome structure and functions are organized in soil ecosystems is one of the major challenges in both basic ecology and applied microbiology. Given the ongoing worldwide degradation of agroecosystems, building frameworks for exploring structural diversity and functional profiles of soil microbiomes is an essential task. Our study provides an overview of cropland microbiome states in light of potential crop-disease-suppressive functions. The large data set allowed us to explore highly functional species sets that may be stably managed in agroecosystems. Furthermore, an analysis of network architecture highlighted species that are potentially used to cause shifts from disease-prevalent states of agroecosystems to disease-suppressive states. By extending the approach of comparative analyses toward broader geographic ranges and diverse agricultural practices, agroecosystem with maximized biological functions will be further explored.