Psychological Reactions during and after a Lockdown: Self-Efficacy as a Protective Factor of Mental Health

The aim of the present study was to investigate the effects of home confinement/social isolation (i.e., lockdown), imposed to reduce large-scale spread of a disease in the population, on the mental health of individuals. Through an online survey during the lockdown (DL) related to COVID-19 (1085 respondents, 627 females, agerange: 18-82) (Italy, 23 April-2 May 2020), we revealed that situational factors, i.e., the presence of children at home and female gender, and psychological factors, i.e., a greater sense of isolation, lower perception of safety outside the home and higher trait anxiety, predicted higher levels of state anxiety (R2 = 0.58). The same factors, but with young age instead of the presence of children, predicted higher levels of perceived stress (R2 = 0.63). Then, these data were compared with those collected after the lockdown (AL) (174 respondents, 128 females, agerange: 19-78) (Italy, 1 July-31 October 2021). The results showed that along with a reduced sense of isolation (DL = 2.90 vs. AL = 2.10) and an increased perception of safety outside the home (DL = 2.63 vs. AL = 3.05), a reduction in state anxiety (DL = 45.76 vs. AL= 40.88) and stress appeared (DL = 18.84 vs. AL = 17.63). However, the situation was better for men than for women. Perceived self-efficacy emerged as a protective factor for mental health (R2range: 0.03-0.27). The results are discussed in light of the evidence on the effects of lockdown on individuals worldwide. These results may be used to make more educated decisions on targeted help for individuals who may be most adversely affected by the adoption of lockdowns in the future

ICT architectures for TSO-DSO coordination and data exchange: a European perspective

The coordination between system operators is a key element for the decarbonization of the power system. Over the past few years, many EU-funded research projects have addressed the challenges of Transmission System Operators (TSO) and Distribution System Operators (DSO) coordination by implementing different data exchange architectures. This paper presents a review of the ICT architectures implemented for the main coordination schemes demonstrated in such projects. The main used technologies are analyzed, considering the type of data exchanged and the communication link. Finally, the paper presents the different gaps and challenges on TSO-DSO coordination related to ICT architectures that must still be faced, paying especial attention to the expected contribution of the EU-funded OneNet project on this topic. IEEECoordiNet H202

Viral Mimicry Response Is Associated With Clinical Outcome in Pleural Mesothelioma

Introduction The aim of this study was to investigate endogenous retrovirus (ERV) expression and type I interferon (IFN) activation in human pleural mesothelioma (PM) and their association with clinical outcome. Methods The expression of ERV was determined from PM cohorts and mesothelial precursor RNA sequencing data. The expression of ERV was confirmed by quantitative polymerase chain reaction (qPCR). Methylation of genomic DNA was assessed by quantitative methylation-specific PCR. DNA demethylation was induced in cells by demethylating agent 5-Aza-2’-deoxycytidine (5-Aza-CdR) treatment. To block type I IFN signaling, the cells were treated with ruxolitinib or MAVS silencing. The expression of IFN-stimulated genes (ISGs) was determined by qPCR and Western blot. Circulating ERVs were detected by qPCR. Results Long terminal repeats (LTRs) represent the most abundant transposable elements up-regulated in PM. Within the LTR, ERVmap_1248 and LTR7Y, which are specifically enriched in PM, were further analyzed. The 5-Aza-CdR treatment increased the levels of ERVmap_1248 expression and induced ERVmap_1248 promoter demethylation in mesothelial cells. In addition, ERVmap_1248 promoter was more demethylated in the mesothelioma tissue compared with nontumor tissue. The 5-Aza-CdR treatment of the mesothelial cells also increased the levels of ISGs. Basal ISG expression was higher in the mesothelioma cells compared with the mesothelial cells, and it was significantly decreased by ruxolitinib treatment or MAVS silencing. Furthermore, ISG expression was higher in the tumor tissue with high expression levels of ERVmap_1248. High expression of ERVmap_1248 was associated with longer overall survival and BAP1 mutations. ERVmap_1248 and LTR7Y can be detected in the PM plasma. Conclusions We provide clues for patient stratification especially for immunotherapy where best clinical responses are associated with an activated basal immune response

European (energy) data exchange reference architecture 3.0

This is the third version of Data Exchange Reference Architecture – DERA 3.0. BRIDGE report on energy data exchange reference architecture aims at contributing to the discussion and practical steps towards truly interoperable and business process agnostic data exchange arrangements on European scale both inside energy domain and across different domains.DERA 3.0Recommendations related to the implementation of DERA:A. Leverage Smart Grid Architecture Model (SGAM) usage by completing it with data governance requirements, specifically from end-customer perspective, and map it to the reference architectures of other sectors (similar to the RAMI4.0 for industry – Reference Architecture Model Industrie 4.0; and CREATE-IoT 3D RAM for health – Reference Architecture Model of CREATE-IoT project), incl. for basic interoperability vocabulary with non-energy sectors.B. Facilitate European strategy, regulation (harmonisation of national regulations) and practical tools for cross-sector exchange of any type of both private data and public data, e.g. through reference models for data space, common data governance and data interoperability implementing acts.C. Ensure cooperation between appropriate associations, countries and sector representatives to work on cross-sector and cross-border data management by establishing European data cooperation agency. This involves ongoing empowering/restructuring of the Data Management WG of the BRIDGE Initiative to engage other sectors and extend cooperation with projects that are not EU-funded and with European Standardisation Organisations (CEN-CENELEC-ETSI).D. Harmonise the development, content and accessibility of data exchange business use cases for cross-sector domain through BRIDGE use case repository. Track tools that identify common features on use cases, e.g. interfaces between sectors, and enable the alignment with any potential peer repositories for other domains. Also, the use case repository must rely on the HEMRM with additional roles created by some projects or roles coming from other associations (related to another sector than the electricity/energy sector).E. Use BRIDGE use case repository for aligning the role selection. Harmonise data roles across electricity and other energy domains by developing HERM – Harmonised Energy Role Model and ensure access to model files. Look for consistency with other domains outside energy based on this HERM – cross-sectoral roles. Harmonised EnergyData EndpointsData SpaceConnectorData ProcessingStandard CommunicationProtocols& FormatsData HarmonizationData PersistanceVocabularyProviderCredentialManagerIdentityManagerMonitoring& OrchestrationData DiscoveryData IndexerLocal AI/ML ServicesDigital TwinsMarketplace BackendStandard CommunicationProtocols& FormatsMarketplace FrontendFederatedUse Cases and Business needsLocal Use Cases and Business needsEnergy RegulationEU Re-gulationActorsBusinessFunctionInformationComp.CommsNon-personal dataSecurity/ResilienceUserAcceptanceSovereigntyOpen SourceInteroperabilityLocalFederatedInteroperabilityTrustData valueGovernance9DATA MANAGEMENT WORKING GROUPEuropean (energy) data exchange reference architecture 3.0Role Model shall have clear implications and connections with data (space) roles such as data provider/consumer, service provider etc.F. Define and harmonise functional data processes for cross-sector domain, using common vocabulary, template and repository for respective use cases’ descriptions. Harmonisation of functional data processes for cross-sector data ecosystems including Vocabulary provider, Federated catalogue, Data quality, Data accounting processes, Clearing process (audit, logging, etc.) and Data tracking and provenance.G. Define and maintain a common reference semantic data model, and ensure access to its model files facilitating cross-sector data exchange, by leveraging existing data models like Common Information Model (CIM) of International Electrotechnical Commission (IEC) and ontologies like Smart Appliances Reference Ontology (SAREF).H. Develop cross-sector data models and profiles, with specific focus on private data exchange. Enable open access to model files whenever possible.I. Ensure protocol agnostic approach to cross-sector data exchange by selecting standardised and open ones.J. Ensure data format agnostic approach to cross-sector data exchange. The work done by projects like TDX-ASSIST and EU-SysFlex (using IEC CIM), and PLATOON (using SAREF) must be shared and made known to consolidate the approach in order to reach semantic interoperability. Metadata must also be taken into account.K. Promote business process agnostic DEPs (Data Exchange Platforms) and make these interoperable by developing APIs (Application Programming Interfaces) which enable for data providers and data users easy connection to any European DEP but also create the possibility whereby connecting to one DEP ensures data exchange with any other stakeholder in Europe. DEPs shall explore the integration of data space connectors towards their connectivity with other DEPs including cross-sector ones.L. Develop universal data applications which can serve any domain. Develop open data driven services that promote also cross-sector integration collectively available in application repositories.Possible next steps (“sub-actions”) for 2023/2024:➢ Release BRIDGE Federated Service Catalogue tool and associated process.➢ Release DERA interactive visualisation tool.➢ Follow up the implementation of DERA 3.0 in BRIDGE projects (mapping to DERA)➢ Update recommendations to comply with DERA 3.0.➢ Develop / enhance the “data role model”

THE DESIGN OF WAITING AREAS TO OPTIMIZE THE STORAGE CAPACITY IN THE MARINE INTERMODAL TERMINALS

The appropriate sizing of storage areas to optimize the management of intermodal transport, the adoption of environment protection systems and the appropriate flow’s regulations inside manoeuvre’s zones can solve many problems encountered today in a intermodal marine terminal. For these reasons the “integrated design” of storage areas for vehicles and containers is considered essential to ensure efficiency and functionality for all harbour-system. So is here proposed a simulative model as a tool for a more correct design of waiting areas by considering the real stochastic conditions of the process of the arrivals. For the sizing of areas for containers in the harbours, it is necessary to report the storage capacity in terms of TEU that can be stored (and handled) in the unit of time, e.g. in one year, with the extension of sites for storage of boxes and furniture with the other specific operating parameters. The sizing of storage areas of the goods date constitutes a delicate problem the frequent shortage of the areas available. The ability to warehouse of the terminal is essentially determined from the interrelation between fixed and static parameters in the short period which the extension of the storage area, the height of the overlapping batteries of container (defined also like number of “shooting”), the means of movements and, at last, a series of parameters that can vary the efficiency’s degree according to of the operatives of the terminal. The optimal level of use is caught up when it is employed approximately the 60-65% of the maximum storage capacity; account is kept, therefore, of a sure tolerance necessary in order to make forehead to eventual peaks of traffic in the periods in which the volume of container in the terminal or advanced to that mean. By use of the Sartor expression (1997), it is possible to find out the capacity of traffic C of a terminal for container in a period of reference (generally one year) and this can be useful in order to define the requirements of areas to assign to the storage

The CDC2 I-G-T haplotype associated with the APOE epsilon4 allele increases the risk of sporadic Alzheimer's disease in Sicily.

The cell division cycle 2 (CDC2) gene is a candidate susceptibility gene for Alzheimer's disease (AD). We investigated the CDC2 genotype, and allele and haplotype frequencies in AD patients and matched controls, distinguishing between apolipoprotein E (APOE) epsilon4 allele carriers and non-carriers. APOE epsilon4 is an established predictor of AD risk. APOE and CDC2 genotypes were examined in 109 sporadic AD patients and in 110 healthy age- and sex-matched controls from Sicily. The epsilon4 allele of APOE was predictive of AD risk in our study group (odds ratio: 5.37, 95% CI 2.77-10.41; PA, Ex7-14 T>A) were not significantly different between AD patients and controls. However, a significant different distribution of a specific CDC2 haplotype (I-G-T) was found between AD patients and controls when analyzing APOE epsilon4-positive subjects (P=0.0288). Moreover, the combined presence of the I-G-T haplotype and the epsilon4 allele almost doubled the risk of AD (odds ratio: 10.09, 95% CI 3.88-26.25; P<0.0001) compared to carriers of epsilon4 alone. This study suggests that the I-G-T haplotype of the CDC2 gene increases the risk of AD in APOE epsilon4 carriers

Role of the Transforming-Growth-Factor-β1 Gene in Late-Onset Alzheimer's Disease: Implications for the Treatment.

Late-onset Alzheimer's disease (LOAD) is the most common form of dementia in the elderly. LOAD has a complex and largely unknown etiology with strong genetic determinants. Genetics of LOAD is known to involve several genetic risk factors among which the Apolipoprotein E (APOE) gene seems to be the major recognized genetic determinant. Recent efforts have been made to identify other genetic factors involved in the pathophysiology of LOAD such as genes associated with a deficit of neurotrophic factors in the AD brain. Genetic variations of neurotrophic factors, such as brain-derived neurotrophic factor (BDNF), and transforming-growth-factor-beta 1 (TGF-beta 1) are known to increase the risk to develop LOAD and have also been related to depression susceptibility in LOAD. Transforming-Growth-Factor-beta 1 (TGF-beta 1) is a neurotrophic factor that exerts neuroprotective effects against beta-amyloid-induced neurodegeneration. Recent evidence suggests that a specific impairment in the signaling of TGF-beta is an early event in the pathogenesis of AD. TGF-beta 1 protein levels are predominantly under genetic control, and the TGF-beta 1 gene, located on chromosome 19q13.1-3, contains several single nucleotide polymorphisms (SNPs) upstream and in the transcript region, such as the SNP at codon + 10 (T/C) and + 25 (G/C), which is known to influence the level of expression of TGF-beta 1. In the present review, we summarize the current literature on genetic risk factors for LOAD, focusing on the role of the TGF-beta 1 gene, finally discussing the possible implications of these genetic studies for the selection of patients eligible for neuroprotective strategies in AD.Late-onset Alzheimer's disease (LOAD) is the most common form of dementia in the elderly. LOAD has a complex and largely unknown etiology with strong genetic determinants. Genetics of LOAD is known to involve several genetic risk factors among which the Apolipoprotein E (APOE) gene seems to be the major recognized genetic determinant. Recent efforts have been made to identify other genetic factors involved in the pathophysiology of LOAD such as genes associated with a deficit of neurotrophic factors in the AD brain. Genetic variations of neurotrophic factors, such as brain-derived neurotrophic factor (BDNF), and transforming-growth-factor-β1 (TGF-β1) are known to increase the risk to develop LOAD and have also been related to depression susceptibility in LOAD. Transforming-Growth-Factor-β1 (TGF-β1) is a neurotrophic factor that exerts neuroprotective effects against ß-amyloid-induced neurodegeneration. Recent evidence suggests that a specific impairment in the signaling of TGF-β is a

TGF-beta1 protects against A beta-neurotoxicity via the phosphatidylinositol-3-kinase pathway.

beta-Amyloid (A beta) injection into the rat dorsal hippocampus had a small neurotoxic effect that was amplified by i.c.v. injection of SB431542, a selective inhibitor of transforming growth factor-beta (TGF-beta) receptor. This suggested that TGF-beta acts as a factor limiting A beta toxicity. We examined the neuroprotective activity of TGF-beta1 in pure cultures of rat cortical neurons challenged with A beta. Neuronal death triggered by A beta is known to proceed along an aberrant re-activation of the cell cycle, and involves late beta-catenin degradation and tau hyperphosphorylation. TGF-beta1 was equally protective when added either in combination with, or 6 h after A beta. Co-added TGF-beta1 prevented A beta-induced cell cycle reactivation, whereas lately added TGF-beta1 had no effect on the cell cycle, but rescued the late beta-catenin degradation and tau hyperphosphorylation. The phosphatidylinositol-3-kinase (PI-3-K) inhibitor, LY294402, abrogated all effects. Thus, TGF-beta1 blocks the whole cascade of events leading to A beta neurotoxicity by activating the PI-3-K pathway