Public health of people and individuals is the most important resource in the modern world. The sugar epidemic and cardiovascular diseases are linked to the obesity epidemic. As obesity appears at younger and younger ages, it is to be expected that the proportion of people who have been obese for the number of years will increase and that those practicing a "sedentary lifestyle" will move less and less. Diabetes mellitus type 2 (DMT2) and cardiovascular diseases (CD) are among the top ten causes of death in the world. It is observed that the association between DMT2 and CD risk is not the same for both sexes, with the cardiovascular risk associated with DMT2 being greater in women. Among the different strategies for the prevention and treatment of DMT2 and risk factors for CD, physical exercise has been largely recommended because of its positive effects on glycemic control, body mass, blood pressure, and lipid profile. A higher level of daily physical activity significantly reduces the risk of contracting numerous diseases such as: diabetes, diseases of the heart and blood vessels, certain forms of malignant diseases, obesity, asthma, osteoporosis and others.  Article visualizations:

The classification of biological neuron types and networks poses challenges to the full understanding of the human brain’s organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal morphology and electrical types and their networks, based on the attributes of neuronal communication using supervised machine learning solutions. This presents advantages compared to the existing approaches in neuroinformatics since the data related to mutual information or delay between neurons obtained from spike trains are more abundant than conventional morphological data. We constructed two open-access computational platforms of various neuronal circuits from the Blue Brain Project realistic models, named Neurpy and Neurgen. Then, we investigated how we could perform network tomography with cortical neuronal circuits for the morphological, topological and electrical classification of neurons. We extracted the simulated data of 10,000 network topology combinations with five layers, 25 morphological type (m-type) cells, and 14 electrical type (e-type) cells. We applied the data to several different classifiers (including Support Vector Machine (SVM), Decision Trees, Random Forest, and Artificial Neural Networks). We achieved accuracies of up to 70%, and the inference of biological network structures using network tomography reached up to 65% of accuracy. Objective classification of biological networks can be achieved with cascaded machine learning methods using neuron communication data. SVM methods seem to perform better amongst used techniques. Our research not only contributes to existing classification efforts but sets the road-map for future usage of brain–machine interfaces towards an in vivo objective classification of neurons as a sensing mechanism of the brain’s structure.

Conflict of interest: COI declared see note COI notes: The authors declare no competing financial interests. MB is a consultant for Oxford Immunotech. AS is a consultant for Gritstone Bio, Flow Pharma, Arcturus Therapeutics, ImmunoScape, CellCarta, Avalia, Moderna, Fortress and Repertoire. LJI has filed for patent protection for various aspects of T cell epitope and vaccine design work. Preprint server: No; Author contributions and disclosures: LB, LH, AÖ, GB, MSC, HGL and MB contributed to conceptualization, funding acquisition and discussion of data. YG, KH and SM and DW performed experiments and analyzed data. LB, HMIS, CK, LH and AÖ recruited study participants, conducted management of participants during the study and analyzed data. AG and AS provided peptide pools to measure the spike-specific T cell responses. LB, DW, AÖ, LH, HGL and MB wrote the original draft of the manuscript. All authors reviewed and edited revisions of the manuscript and had final responsibility for the decision to submit for publication. Non-author contributions and disclosures: No; Agreement to Share Publication-Related Data and Data Sharing Statement: Emails to the corresponding author Clinical trial registration information (if any):

The development of blockchain has allowed for the development of new concepts and ideas. A completely immutable ledger might not be appropriate for all new applications that are being envisaged for the blockchain. One of them is self-sovereign identity. The aim of this paper is to analyze the possible use cases for blockchain redaction in SSI. Main concepts of redaction and a summary of the current research progress are given. Use cases for redaction in SSI are categorized and described alongside their existing solutions. Detailed proposal for possible use cases is given and comparison is drawn between this solution and existing solution. Future challenges are introduced.

Among numerous causative agents recognized as oncogenic drivers, 13% of total cancer cases occur as a result of viral infections. The intricacy and diversity of carcinogenic processes, however, raise significant concerns about the mechanistic function of viruses in cancer. All tumor-associated viruses have been shown to encode viral oncogenes with a potential for cell transformation and the development of malignancies, including diffuse large B-cell lymphoma (DLBCL). Given the difficulties in identifying single mechanistic explanations, it is necessary to combine ideas from systems biology and viral evolution to comprehend the processes driving viral cancer. The potential for more efficient and acceptable therapies lies in targeted medicines that aim at viral proteins or trigger immune responses to either avoid infection or eliminate infected or cancerous cells. In this review, we aim to describe the role of viral infections and their mechanistic approaches in DLBCL tumorigenesis. To the best of our knowledge, this is the first review summarizing the oncogenic potential of numerous viral agents in DLBCL development.

A large-scale transformation of the energy system, which climate mitigation entails, is a global and highly politicized problem. This thematic issue brings together scholars who work with Integrated Assessment Models (IAMs)—which are used for Intergovernmental Panel on Climate Change (IPCC) reports and other key analyses of future climate trajectories—and social scientists working on climate and energy issues to highlight how the two strands of research could benefit from combining insights across different disciplines and methods. One of the key messages across almost all contributions is that the more technical perspectives could benefit from adjusting their assumptions to reflect the patterns observed in quantitative and qualitative social science. Combining different disciplines is methodologically challenging but promising to ensure that the mitigation strategies developed are considered technically and politically feasible, as well as just.

Abstract The main objective of this paper is to investigate determinants of non-performing loans in the Middle East and North Africa region by exploring the role of bank-specific and macroeconomic factors, particularly in the period of the global financial crisis, as well as the COVID-19 pandemic, as a health crisis that translates to an economic crisis. This study includes 74 banks belonging to 11 MENA countries over the period 2005–2020 and uses the two-stage system generalized method of moment estimator. To conduct a comparative analysis, the whole sample is divided into two sub-samples. The first one is related to the Middle East countries and the second one covers North African countries. The empirical findings indicate that the level of non-performing loans is more sensitive to bank specifics than macroeconomic factors. When it comes to macroeconomic factors, macroeconomic environment and institutional quality significantly affect the level of NPLs. However, no significant effect has been detected regarding the impact of the COVID-19 pandemic.

Various methods are nowadays available to design observers for broad classes of systems. Nevertheless, the question of the tuning of the observer to achieve satisfactory estimation performance remains largely open. This paper presents a general supervisory design framework for online tuning of the observer gains with the aim of achieving various trade-offs between robustness and speed of convergence. We assume that a robust nominal observer has been designed for a general nonlinear system and the goal is to improve its performance. We present for this purpose a novel hybrid multi-observer, which consists of the nominal one and a bank of additional observer-like systems, that are collectively referred to as modes and that differ from the nominal observer only in their output injection gains. We then evaluate on-line the estimation cost of each mode of the multi-observer and, based on these costs, we select one of them at each time instant. Two different strategies are proposed. In the first one, initial conditions of the modes are reset each time the algorithm switches between different modes. In the second one, the initial conditions are not reset. We prove a convergence property for the hybrid estimation scheme and we illustrate the efficiency of the approach in improving the performance of a given nominal high-gain observer on a numerical example.

Posttraumatic stress disorder (PTSD) is a heritable (h2 = 24–71%) psychiatric illness. Copy number variation (CNV) is a form of rare genetic variation that has been implicated in the etiology of psychiatric disorders, but no large-scale investigation of CNV in PTSD has been performed. We present an association study of CNV burden and PTSD symptoms in a sample of 114,383 participants (13,036 cases and 101,347 controls) of European ancestry. CNVs were called using two calling algorithms and intersected to a consensus set. Quality control was performed to remove strong outlier samples. CNVs were examined for association with PTSD within each cohort using linear or logistic regression analysis adjusted for population structure and CNV quality metrics, then inverse variance weighted meta-analyzed across cohorts. We examined the genome-wide total span of CNVs, enrichment of CNVs within specified gene-sets, and CNVs overlapping individual genes and implicated neurodevelopmental regions. The total distance covered by deletions crossing over known neurodevelopmental CNV regions was significant (beta = 0.029, SE = 0.005, P = 6.3 × 10−8). The genome-wide neurodevelopmental CNV burden identified explains 0.034% of the variation in PTSD symptoms. The 15q11.2 BP1-BP2 microdeletion region was significantly associated with PTSD (beta = 0.0206, SE = 0.0056, P = 0.0002). No individual significant genes interrupted by CNV were identified. 22 gene pathways related to the function of the nervous system and brain were significant in pathway analysis (FDR q < 0.05), but these associations were not significant once NDD regions were removed. A larger sample size, better detection methods, and annotated resources of CNV are needed to explore this relationship further.

Purpose of review Autoimmune and inflammatory complications have been shown to arise in all age groups and across the spectrum of inborn errors of immunity (IEI). This review aims to highlight recent ground-breaking research and its impact on our understanding of IEI. Recent findings Three registry-based studies of unprecedented size revealed the high prevalence of autoimmune, inflammatory and malignant complications in IEI. Two novel IEI were discovered: an autoinflammatory relopathy, cleavage-resistant RIPK1-induced autoinflammatory syndrome, as well as an inheritable phenocopy of PD-1 blockade-associated complication (as seen in cancer therapy) manifesting with multiorgan autoimmunity and Mycobacterium tuberculosis infection. A study examining patients with partial RAG deficiency pinpointed the specific defects leading to the failure of central and peripheral tolerance resulting in wide-ranging autoimmunity. A novel variant of Immunodeficiency Polyendocrinopathy Enteropathy X-linked syndrome was described, associated with preferential expression of a FOXP3 isoform lacking exon 2, linking exon-specific functions and the phenotypes corresponding to their absence. Lastly, we touch on recent findings pertaining actinopathies, the prototypical IEI with autoimmune, inflammatory and atopic complications. Summary Dysregulated immunity has been associated with IEI since their discovery. Recently, large concerted efforts have shown how common these complications actually are while providing insight into normal and dysregulated molecular mechanisms, as well as describing novel diseases.

The global increase in temperature and associated meteorological disruptions, such as the earlier onset of high temperatures and disruptions in precipitation, are becoming severely limiting factors in crop cultivation. Chickpea, as a cool season crop, is under the direct influence of heat and drought stress that is not only affecting this crop in its podding stage but, with current climate trends, the drought and heat are now also affecting earlier stages, such as flowering. The deteriorating effects of heat and droughts include reduced flowering, abortion of flowers and absence of podding; thus, this is severely affecting crop yield. Further research has been conducted to identify the genes correlated to higher stress tolerance and to utilize them in developing more tolerant varieties. Different alleviation approaches have been also tested and it has been determined that some positive effects can be seen in supplementation with Zn through melioration of water relations, seed priming and some transgenic and genome editing approaches. Breeding strategies for future chickpea varieties have been focused on the identification of varieties with more tolerant traits for an improved yield under stressed conditions. In this review, we have reviewed recent strategies and biotechnological approaches that have been used with chickpea crops to address the two major abiotic stresses (heat and drought) linked to future climate change.

Ash is a by-product of wood biomass combustion that must be removed daily from stoves or fireplaces. Therefore, operators or owners are exposed to the potential impact of ash. The goal of this study was to determine whether heavy metal present in wood pellet ash posed a health concern to stove operators/owners. The risk assessment procedure was carried out in several steps, including exposure evaluation, toxicity evaluation, and risk categorisation. The hazard coefficient (HQ) and non-carcino genic hazard index (HI) were calculated for Cd, Cr, Cu, Ni, Pb, and Zn. HQ had the highest value for the ingestion pathway (3.62 ∙ 10 −6 ), and the value for non-carcinogenic HI was 3.70 ∙ 10 −6 . The value HI < 1 suggests that there is no risk to operator health related to heavy metals in analysed wood pellets ash. The carcinogenic risk (CR) was calculated for Ni, Pb, Cr, and Cd, and the values were within the permitted limits. The risk assessment based on HI and CR indicators proved that there was no significant health concern regarding exposure to the analysed ashes.