Functional strengthening through synaptic scaling upon connectivity disruption in neuronal cultures

An elusive phenomenon in network neuroscience is the extent of neuronal activity remodeling upon damage. Here, we investigate the action of gradual synaptic blockade on the effective connectivity in cortical networks in vitro. We use two neuronal cultures configurations—one formed by about 130 neuronal aggregates and another one formed by about 600 individual neurons—and monitor their spontaneous activity upon progressive weakening of excitatory connectivity. We report that the effective connectivity in all cultures exhibits a first phase of transient strengthening followed by a second phase of steady deterioration. We quantify these phases by measuring GEFF, the global efficiency in processing network information. We term hyperefficiency the sudden strengthening of GEFF upon network deterioration, which increases by 20–50% depending on culture type. Relying on numerical simulations we reveal the role of synaptic scaling, an activity–dependent mechanism for synaptic plasticity, in counteracting the perturbative action, neatly reproducing the observed hyperefficiency. Our results demonstrate the importance of synaptic scaling as resilience mechanism. Author Summary Neuronal circuits exhibit homeostatic plasticity mechanisms to cope with perturbations or damage. A central mechanism is ‘synaptic scaling,’ a self-organized response in which the strength of neurons’ excitatory synapses is adjusted to compensate for activity variations. Here we present experiments in which the excitatory connectivity of in vitro cortical networks is progressively weakened through chemical action. The spontaneous activity and effective connectivity of the whole network is monitored as degradation progresses, and the capacity of the network for broad information communication is quantified through the global efficiency. We observed that the network responded to the perturbation by strengthening the effective connectivity, reaching a hyperefficient state for moderate perturbations. The study proves the importance of ‘synaptic scaling’ as a driver for functional reorganization and network-wide resilience

GEO-C:Enabling open cities and the open city toolkit

The GEO-C doctoral programme, entitled “Geoinformatics: Enabling Open Cities”, is funded by the EU Marie Skłodowska-Curie actions (International Training Networks (ITN), European Joint Doctorates) until December 2018, and is managed by three European universities in Germany, Portugal and Spain. 15 doctoral grantholders (Early Stage Researchers) were selected to work on specific three-year projects, all contributing to improving the notion of open cities, and specifically to an Open City Toolkit of methodologies, code, and best practice examples. Contributions include volunteered geographic information (VGI), public information displays, mobility apps to encourage green living, providing open data to immigrant populations, reducing the second-order digital divide, sensing of quality of life, proximity based privacy protection, and spatio-temporal online social media analysis. All doctoral students conducted long-term visits and were embedded in city governments and businesses, to gain experience from multiple perspectives in addition to the researcher and users’ perspective. The projects are situated within three areas: transparency, participation, and collaboration. They took mostly a bottom-up (citizen-centric) approach to (smart) open cities, rather than relying on large IT companies to create smart open cities in a top-down manner. This paper discusses the various contributions to enabling open cities, explains in some detail the Open City Toolkit, and its possible uses and impact on stakeholders. A follow-up doctoral program has been solicited and, if successful, will continue this line of research and will strengthen aspects of privacy, data provenance, and trust, in an effort to improve relations between data (e.g. news) publishers and consumers

Geospatial information infrastructures

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Geospatial information infrastructures (GIIs) provide the technological, semantic,organizationalandlegalstructurethatallowforthediscovery,sharing,and use of geospatial information (GI). In this chapter, we introduce the overall concept and surrounding notions such as geographic information systems (GIS) and spatial datainfrastructures(SDI).WeoutlinethehistoryofGIIsintermsoftheorganizational andtechnologicaldevelopmentsaswellasthecurrentstate-of-art,andreflectonsome of the central challenges and possible future trajectories. We focus on the tension betweenincreasedneedsforstandardizationandtheever-acceleratingtechnological changes. We conclude that GIIs evolved as a strong underpinning contribution to implementation of the Digital Earth vision. In the future, these infrastructures are challengedtobecomeflexibleandrobustenoughtoabsorbandembracetechnological transformationsandtheaccompanyingsocietalandorganizationalimplications.With this contribution, we present the reader a comprehensive overview of the field and a solid basis for reflections about future developments

Modeling the Spatiotemporal Epidemic Spreading of COVID-19 and the Impact of Mobility and Social Distancing Interventions

On 31 December, 2019, an outbreak of a novel coronavirus, SARS-CoV-2, that causes the COVID-19 disease, was first reported in Hubei, mainland China. This epidemics'' health threat is probably one of the biggest challenges faced by our interconnected modern societies. According to the epidemiological reports, the large basic reproduction number R0~3.0, together with a huge fraction of asymptomatic infections, paved the way for a major crisis of the national health capacity systems. Here, we develop an age-stratified mobility-based metapopulation model that encapsulates the main particularities of the spreading of COVID-19 regarding (i) its transmission among individuals, (ii) the specificities of certain demographic groups with respect to the impact of COVID-19, and (iii) the human mobility patterns inside and among regions. The full dynamics of the epidemic is formalized in terms of a microscopic Markov chain approach that incorporates the former elements and the possibility of implementing containment measures based on social distancing and confinement. With this model, we study the evolution of the effective reproduction number R(t), the key epidemiological parameter to track the evolution of the transmissibility and the effects of containment measures, as it quantifies the number of secondary infections generated by an infected individual. The suppression of the epidemic is directly related to this value and is attained when R<1. We find an analytical expression connecting R with nonpharmacological interventions, and its phase diagram is presented. We apply this model at the municipality level in Spain, successfully forecasting the observed incidence and the number of fatalities in the country at each of its regions. The expression for R should assist policymakers to evaluate the epidemics'' response to actions, such as enforcing or relaxing confinement and social distancing

Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks

In this era of advanced distribution automation technologies, demand response is becoming an important tool for electricity network management. The available flexible loads can efficiently help in alleviating the network constraints and achieving demand-supply balance. Therefore, this forms the rationale behind this paper, which aims to implement a multi-agent system framework in order to achieve flexible price-based demand response. A genetic algorithm-based multi-objective optimization technique is applied to determine the optimal locations and the amount of required demand reduction in order to keep the network within statutory limits. The methodology is based on probabilistic estimation of the granularity of total available flexible demand from shiftable home appliances in each low-voltage feeder. Moreover, an optimal decision making for the start time of appliances upon receiving a real-time price signal is proposed. This is accomplished by considering the willingness to participate as well as price demand elasticity of the different clusters of customers. To fully demonstrate the feasibility and effectiveness of the proposed framework, a modified IEEE 69 bus distribution network comprising 1824 low voltage residential customers has been implemented and analyzed

The physics of spreading processes in multilayer networks

The study of networks plays a crucial role in investigating the structure, dynamics, and function of a wide variety of complex systems in myriad disciplines. Despite the success of traditional network analysis, standard networks provide a limited representation of complex systems, which often include different types of relationships (i.e., "multiplexity") among their constituent components and/or multiple interacting subsystems. Such structural complexity has a significant effect on both dynamics and function. Throwing away or aggregating available structural information can generate misleading results and be a major obstacle towards attempts to understand complex systems. The recent "multilayer" approach for modeling networked systems explicitly allows the incorporation of multiplexity and other features of realistic systems. On one hand, it allows one to couple different structural relationships by encoding them in a convenient mathematical object. On the other hand, it also allows one to couple different dynamical processes on top of such interconnected structures. The resulting framework plays a crucial role in helping achieve a thorough, accurate understanding of complex systems. The study of multilayer networks has also revealed new physical phenomena that remain hidden when using ordinary graphs, the traditional network representation. Here we survey progress towards attaining a deeper understanding of spreading processes on multilayer networks, and we highlight some of the physical phenomena related to spreading processes that emerge from multilayer structure.Comment: 25 pages, 4 figure

Integrating Concepts of Artificial Intelligence in the EO4GEO Body of Knowledge

Ponència del XXIV ISPRS Congress (2022 edition), 6–11 June 2022, Nice, FranceThe EO4GEO Body of Knowledge (BoK) forms a structure of concepts and relationships between them, describing the domain of Earth Observation and Geo-Information (EO/GI). Each concept carries a short description, a list of key literature references and a set of associated skills which are used for job profiling and curriculum building. As the EO/GI domain is evolving continuously, the BoK needs regular updates with new concepts embodying new trends, and deprecating concepts which are not relevant anymore. This paper presents the inclusion of BoK concepts related to Artificial Intelligence. This broad field of knowledge has links to several applications in EO/GI. Its connection to concepts, already existing in the BoK, needs special attention. To perform a clean and structural integration of the cross-cutting domain of AI, first a separate cluster of AI concepts was created, which was then merged with the existing BoK. The paper provides examples of this integration with specific concepts and examples of training resources in which AI-related concepts are used. Although the presented structure already provides a good starting point, the positioning of AI within the EO/GI-focussed BoK needs to be further enhanced with the help of expert calls as part of the BoK update cycle

Early childhood wheezing phenotypes and determinants in a South African birth cohort: longitudinal analysis of the Drakenstein Child Health Study

BACKGROUND: Developmental trajectories of childhood wheezing in low-income and middle-income countries (LMICs) have not been well described. We aimed to derive longitudinal wheeze phenotypes from birth to 5 years in a South African birth cohort and compare those with phenotypes derived from a UK cohort. METHODS: We used data from the Drakenstein Child Health Study (DCHS), a longitudinal birth cohort study in a peri-urban area outside Cape Town, South Africa. Pregnant women (aged ≥18 years) were enrolled during their second trimester at two public health clinics. We followed up children from birth to 5 years to derive six multidimensional indicators of wheezing (including duration, temporal sequencing, persistence, and recurrence) and applied Partition Around Medoids clustering to derive wheeze phenotypes. We compared phenotypes with a UK cohort (the Avon Longitudinal Study of Parents and Children [ALSPAC]). We investigated associations of phenotypes with early-life exposures, including all-cause lower respiratory tract infection (LRTI) and virus-specific LRTI (respiratory syncytial virus, rhinovirus, adenovirus, influenza, and parainfluenza virus) up to age 5 years. We investigated the association of phenotypes with lung function at 6 weeks and 5 years. FINDINGS: Between March 5, 2012, and March 31, 2015, we enrolled 1137 mothers and there were 1143 livebirths. Four wheeze phenotypes were identified among 950 children with complete data: never (480 children [50%]), early transient (215 children [23%]), late onset (104 children [11%]), and recurrent (151 children [16%]). Multivariate adjusted analysis indicated that LRTI and respiratory syncytial virus-LRTI, but not other respiratory viruses, were associated with increased risk of recurrent wheeze (odds ratio [OR] 2·79 [95% CI 2·05-3·81] for all LTRIs; OR 2·59 [1·30-5·15] for respiratory syncytial virus-LRTIs). Maternal smoking (1·88 [1·12-3·02]), higher socioeconomic status (2·46 [1·23-4·91]), intimate partner violence (2·01 [1·23-3·29]), and male sex (2·47 [1·50-4·04]) were also associated with recurrent wheeze. LRTI and respiratory syncytial virus-LRTI were also associated with early transient and late onset clusters. Wheezing illness architecture differed between DCHS and ALSPAC; children included in ALSPAC in the early transient cluster wheezed for a longer period before remission and late-onset wheezing started at an older age, and no persistent phenotype was identified in DCHS. At 5 years, airway resistance was higher in children with early or recurrent wheeze compared with children who had never wheezed. Airway resistance increased from 6 weeks to 5 years among children with recurrent wheeze. INTERPRETATION: Effective strategies to reduce maternal smoking and psychosocial stressors and new preventive interventions for respiratory syncytial virus are urgently needed to optimise child health in LMICs. FUNDING: UK Medical Research Council; The Bill & Melinda Gates Foundation; National Institutes of Health Human Heredity and Health in Africa; South African Medical Research Council; Wellcome Trust

Prevalence, beliefs and impact of drug-drug interactions between antiretroviral therapy and illicit drugs among people living with HIV in Spain

Altres ajuts: ViiV Healthcare (grant 001/2016)Drug use implies important challenges related to HIV management, particularly due to an increased risk of potential interactions between antiretroviral therapy (ART) and illicit drugs (pDDIs). This study analyses the prevalence and severity of pDDIs among people living with HIV (PLHIV). It also explores their awareness of pDDIs and their beliefs about the toxicity that they may cause, as well as the impact of pDDIs on selected health variables. We conducted an on-line cross-sectional survey across 33 Spanish hospitals and NGOs to collect demographics and clinical data. pDDIs were checked against the Interaction Checker developed by Liverpool University. The sample of the present study was composed of 694 PLHIV who used illicit drugs. They represented 49.5% of the 1,401 PLHIV that participated in the survey. After excluding 38 participants due to lack of information on their ART or illicit drug use, 335 (51.1%) participants consuming drugs presented with some potentially significant pDDIs between their ART and illicit drugs, with a mean of 2.1±1.7 (1-10) pDDIs per patient. The drugs most frequently involved in pDDIs were cocaine, cannabis, MDMA and nitrates ("poppers"). The prevalence of pDDIs across ART regimens was: protease inhibitors (41.7%); integrase inhibitor-boosted regimens (32.1%), and non-nucleoside reverse transcriptase inhibitors (26.3%). An awareness of pDDIs and beliefs about their potential toxicity correlated positively with intentional non-adherence (p<0.0001). Participants with pDDIs exhibited a higher prevalence of intentional non-adherence (2.19±1.04 vs. 1.93±0.94; p = 0.001). The presence of pDDIs was not associated with poorer results in the clinical variables analysed. A significant proportion of PLHIV who use drugs experience pDDIs, thereby requiring close monitoring. pDDIs should be considered in the clinical management of HIV patients. Adequate information about pDDIs and indicators about how to manage ART when PLHIV use drugs could improve ART non-adherence

Associations of wheezing phenotypes in the first 6 years of life with atopy, lung function and airway responsiveness in mid-childhood

&lt;p&gt;Background: Patterns of wheezing during early childhood may indicate differences in aetiology and prognosis of respiratory illnesses. Improved characterisation of wheezing phenotypes could lead to the identification of environmental influences on the development of asthma and airway diseases in predisposed individuals.&lt;/p&gt; &lt;p&gt;Methods: Data collected on wheezing at seven time points from birth to 7 years from 6265 children in a longitudinal birth cohort (the ALSPAC study) were analysed. Latent class analysis was used to assign phenotypes based on patterns of wheezing. Measures of atopy, airway function (forced expiratory volume in 1 s (FEV1), mid forced expiratory flow (FEF25-75)) and bronchial responsiveness were made at 7–9 years of age.&lt;/p&gt; &lt;p&gt;Results: Six phenotypes were identified. The strongest associations with atopy and airway responsiveness were found for intermediate onset (18 months) wheezing (OR for atopy 8.36, 95% CI 5.2 to 13.4; mean difference in dose response to methacholine 1.76, 95% CI 1.41 to 2.12 %FEV1 per μmol, compared with infrequent/never wheeze phenotype). Late onset wheezing (after 42 months) was also associated with atopy (OR 6.6, 95% CI 4.7 to 9.4) and airway responsiveness (mean difference 1.61, 95% CI 1.37 to 1.85 %FEV1 per μmol). Transient and prolonged early wheeze were not associated with atopy but were weakly associated with increased airway responsiveness and persistent wheeze had intermediate associations with these outcomes.&lt;/p&gt; &lt;p&gt;Conclusions: The wheezing phenotypes most strongly associated with atopy and airway responsiveness were characterised by onset after age 18 months. This has potential implications for the timing of environmental influences on the initiation of atopic wheezing in early childhood.&lt;/p&gt