Showing papers by "University of Seville published in 2021"
Daniel J. Klionsky1, Amal Kamal Abdel-Aziz2, Sara Abdelfatah3, Mahmoud Abdellatif4 +2980 more•Institutions (777)
TL;DR: In this article, the authors present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes.
Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
1,129 citations
Université Paris-Saclay1, Autonomous University of Barcelona2, University of Cambridge3, National Institute for Occupational Safety and Health4, University of Bonn5, German Center for Neurodegenerative Diseases6, Harvard University7, University of Lausanne8, University of Padua9, National Research Council10, Heidelberg University11, Salk Institute for Biological Studies12, University of Minnesota13, Pasteur Institute14, Tel Aviv University15, Johns Hopkins University16, University of Portsmouth17, Katholieke Universiteit Leuven18, PSL Research University19, Trinity College, Dublin20, Baylor College of Medicine21, University College London22, University of Edinburgh23, Oregon Health & Science University24, National Institutes of Health25, Columbia University26, University of Rochester27, University of Copenhagen28, Ludwig Maximilian University of Munich29, University of Málaga30, Tufts University31, University of Freiburg32, Utrecht University33, Nihon University34, Max Delbrück Center for Molecular Medicine35, University of California, Los Angeles36, University of Yamanashi37, New York University38, University of British Columbia39, King Abdullah University of Science and Technology40, University of Wisconsin-Madison41, University of California, San Francisco42, McGill University43, University of Kentucky44, Kyushu University45, University of Bordeaux46, University of Minho47, Polytechnic Institute of Cávado and Ave48, University of Alabama at Birmingham49, University of Gothenburg50, University of Poitiers51, Cajal Institute52, King's College London53, University of Strasbourg54, Virginia Tech55, University of Düsseldorf56, Russian Academy of Sciences57, I.M. Sechenov First Moscow State Medical University58, University of Seville59, Georgia Institute of Technology60, University of Texas Health Science Center at Houston61, University of California, San Diego62, Universidade Federal do Rio Grande do Sul63, University of Ljubljana64, Ikerbasque65, University of Manchester66
TL;DR: In this article, the authors point out the shortcomings of binary divisions of reactive astrocytes into good-vs-bad, neurotoxic vs-neuroprotective or A1-vs.A2.
Abstract: Reactive astrocytes are astrocytes undergoing morphological, molecular, and functional remodeling in response to injury, disease, or infection of the CNS. Although this remodeling was first described over a century ago, uncertainties and controversies remain regarding the contribution of reactive astrocytes to CNS diseases, repair, and aging. It is also unclear whether fixed categories of reactive astrocytes exist and, if so, how to identify them. We point out the shortcomings of binary divisions of reactive astrocytes into good-vs-bad, neurotoxic-vs-neuroprotective or A1-vs-A2. We advocate, instead, that research on reactive astrocytes include assessment of multiple molecular and functional parameters-preferably in vivo-plus multivariate statistics and determination of impact on pathological hallmarks in relevant models. These guidelines may spur the discovery of astrocyte-based biomarkers as well as astrocyte-targeting therapies that abrogate detrimental actions of reactive astrocytes, potentiate their neuro- and glioprotective actions, and restore or augment their homeostatic, modulatory, and defensive functions.
797 citations
University of Barcelona1, Newcastle University2, Pontifical Catholic University of Chile3, University College London4, University of Paris5, University of Lisbon6, University of Florida7, University of Washington8, University of Antwerp9, University of Sydney10, Karolinska Institutet11, City University of New York12, King Fahd University Hospital13, University of California, San Diego14, University of California, Berkeley15, University Hospitals Birmingham NHS Foundation Trust16, College of Health Sciences, Bahrain17, Northwestern University18, The Graduate Center, CUNY19, University of Seville20, Royal Free Hospital21, University of Milan22, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico23, The Chinese University of Hong Kong24, Marmara University25, University of Haifa26
TL;DR: In this paper, a global Delphi study, a multidisciplinary group of experts developed consensus statements and recommendations, which a larger group of collaborators reviewed over three rounds until consensus was achieved.
Abstract: Non-alcoholic fatty liver disease (NAFLD) is a potentially serious liver disease that affects approximately one-quarter of the global adult population, causing a substantial burden of ill health with wide-ranging social and economic implications. It is a multisystem disease and is considered the hepatic component of metabolic syndrome. Unlike other highly prevalent conditions, NAFLD has received little attention from the global public health community. Health system and public health responses to NAFLD have been weak and fragmented, and, despite its pervasiveness, NAFLD is largely unknown outside hepatology and gastroenterology. There is only a nascent global public health movement addressing NAFLD, and the disease is absent from nearly all national and international strategies and policies for non-communicable diseases, including obesity. In this global Delphi study, a multidisciplinary group of experts developed consensus statements and recommendations, which a larger group of collaborators reviewed over three rounds until consensus was achieved. The resulting consensus statements and recommendations address a broad range of topics - from epidemiology, awareness, care and treatment to public health policies and leadership - that have general relevance for policy-makers, health-care practitioners, civil society groups, research institutions and affected populations. These recommendations should provide a strong foundation for a comprehensive public health response to NAFLD.
195 citations
German Cancer Research Center1, University Hospital Heidelberg2, Broad Institute3, Harvard University4, Ludwig Maximilian University of Munich5, Heidelberg University6, University of Münster7, Hannover Medical School8, University of Freiburg9, University Hospital of Basel10, Radboud University Nijmegen11, University of Duisburg-Essen12, University of Seville13, University of Navarra14, Boston Children's Hospital15, University of Hamburg16, New York University17, University of Cologne18, University of Amsterdam19, Erasmus University Rotterdam20, University College London Hospitals NHS Foundation Trust21, University College London22, UCL Institute of Neurology23, Dresden University of Technology24, Hospital Sant Joan de Déu Barcelona25, Carlos III Health Institute26, University of Barcelona27, Memorial Sloan Kettering Cancer Center28, Royal National Orthopaedic Hospital29, Charité30
TL;DR: In this paper, a machine learning classifier algorithm based on array-generated DNA methylation data was used for the classification of soft tissue and bone sarcoma. But the performance was validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the classifier.
Abstract: Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications.
171 citations
TL;DR: Among all studied models, the results show that long short-term memory and convolutional networks are the best alternatives, with LSTMs obtaining the most accurate forecasts and CNNs achieving comparable performance with less variability of results under different parameter configurations, while also being more efficient.
Abstract: In recent years, deep learning techniques have outperformed traditional models in many machine learning tasks. Deep neural networks have successfully been applied to address time series forecasting problems, which is a very important topic in data mining. They have proved to be an effective solution given their capacity to automatically learn the temporal dependencies present in time series. However, selecting the most convenient type of deep neural network and its parametrization is a complex task that requires considerable expertise. Therefore, there is a need for deeper studies on the suitability of all existing architectures for different forecasting tasks. In this work, we face two main challenges: a comprehensive review of the latest works using deep learning for time series forecasting and an experimental study comparing the performance of the most popular architectures. The comparison involves a thorough analysis of seven types of deep learning models in terms of accuracy and efficiency. We evaluate the rankings and distribution of results obtained with the proposed models under many different architecture configurations and training hyperparameters. The datasets used comprise more than 50,000 time series divided into 12 different forecasting problems. By training more than 38,000 models on these data, we provide the most extensive deep learning study for time series forecasting. Among all studied models, the results show that long short-term memory (LSTM) and convolutional networks (CNN) are the best alternatives, with LSTMs obtaining the most accurate forecasts. CNNs achieve comparable performance with less variability of results under different parameter configurations, while also being more efficient.
137 citations
TL;DR: A comprehensive overview of the available methodologies for the atroposelective transformation of (heterobiaryl)biary precursors toward the synthesis of enantiomerically enriched products and the conceptual aspects associated to each type of transformation can be found in this paper.
Abstract: This tutorial review provides a systematic overview of the available methodologies for the atroposelective transformation of (heterobiaryl)biaryl precursors toward the synthesis of enantiomerically enriched products and the conceptual aspects associated to each type of transformation. Depending on the presence or absence of symmetry in the starting material and the participation of racemization or dynamization events along the process, several strategies have been developed, including desymmetrization, classical kinetic resolution (KR), dynamic kinetic resolution (DKR) and dynamic kinetic asymmetric transformation (DYKAT). Seminal contributions and a handful of selected examples are discussed to illustrate the potential of these synthetic tools.
133 citations
TL;DR: During the coming decades, electrification is expected to reach further and deeper into the transportation, building, and industry sectors, mainly motivated by the energy transition to a zero-carbonemission-based economy to mitigate climate change.
Abstract: Electrification has been a key component of technological progress and economic development since the industrial revolution It has improved living conditions, spurred innovation, and increased efficiency across all sectors of our economy and all aspects of our lives During the coming decades, electrification is expected to reach further and deeper into the transportation, building, and industry sectors, mainly motivated by the energy transition to a zero-carbonemission-based economy to mitigate climate change
122 citations
TL;DR: In this article, a comprehensive review of the latest works using deep learning for time series forecasting and an experimental study comparing the performance of the most popular architectures was conducted. And the results show that long short-term memory (LSTM) and convolutional networks (CNN) are the best alternatives, with LSTMs obtaining the most accurate forecasts.
Abstract: In recent years, deep learning techniques have outperformed traditional models in many machine learning tasks. Deep neural networks have successfully been applied to address time series forecasting problems, which is a very important topic in data mining. They have proved to be an effective solution given their capacity to automatically learn the temporal dependencies present in time series. However, selecting the most convenient type of deep neural network and its parametrization is a complex task that requires considerable expertise. Therefore, there is a need for deeper studies on the suitability of all existing architectures for different forecasting tasks. In this work, we face two main challenges: a comprehensive review of the latest works using deep learning for time series forecasting; and an experimental study comparing the performance of the most popular architectures. The comparison involves a thorough analysis of seven types of deep learning models in terms of accuracy and efficiency. We evaluate the rankings and distribution of results obtained with the proposed models under many different architecture configurations and training hyperparameters. The datasets used comprise more than 50000 time series divided into 12 different forecasting problems. By training more than 38000 models on these data, we provide the most extensive deep learning study for time series forecasting. Among all studied models, the results show that long short-term memory (LSTM) and convolutional networks (CNN) are the best alternatives, with LSTMs obtaining the most accurate forecasts. CNNs achieve comparable performance with less variability of results under different parameter configurations, while also being more efficient.
121 citations
TL;DR: In this article, the authors used T1-weighted magnetic resonance images to determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia.
Abstract: Importance Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood.
Objective To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia.
Design, Setting, and Participants Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244.
Main Outcomes and Measures Interregional profiles of group difference in cortical thickness between cases and controls.
Results A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders.
Conclusions and Relevance In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.
108 citations
TL;DR: In this paper, a library of foldable origami shapes is created and then combined with a single fluidic pressure input to construct a rigid-walled deployable structure that can lock in place after deployment.
Abstract: From stadium covers to solar sails, we rely on deployability for the design of large-scale structures that can quickly compress to a fraction of their size1–4. Historically, two main strategies have been used to design deployable systems. The first and most frequently used approach involves mechanisms comprising interconnected bar elements, which can synchronously expand and retract5–7, occasionally locking in place through bistable elements8,9. The second strategy makes use of inflatable membranes that morph into target shapes by means of a single pressure input10–12. Neither strategy, however, can be readily used to provide an enclosed domain that is able to lock in place after deployment: the integration of a protective covering in linkage-based constructions is challenging and pneumatic systems require a constant applied pressure to keep their expanded shape13–15. Here we draw inspiration from origami—the Japanese art of paper folding—to design rigid-walled deployable structures that are multistable and inflatable. Guided by geometric analyses and experiments, we create a library of bistable origami shapes that can be deployed through a single fluidic pressure input. We then combine these units to build functional structures at the metre scale, such as arches and emergency shelters, providing a direct route for building large-scale inflatable systems that lock in place after deployment and offer a robust enclosure through their stiff faces. Origami-inspired multistable structures that can be inflated from flat to three dimensions have been designed; a library of foldable shapes is created and then combined to build metre-scale functional structures.
106 citations
TL;DR: In this article, the authors explore and describe the experiences and perceptions of nurses working in an ICU during the COVID-19 global pandemic, using an empirical approach and inductive content analysis techniques.
Abstract: Background Because of the COVID-19 pandemic, health care systems worldwide are working under challenging conditions. Patients, who are seriously ill, require intensive care admission. In fighting COVID-19, nurses are frontline health care workers and, as such, have a great responsibility providing needed specialized patient care in intensive care units (ICU). However, working conditions and emotional factors have an impact on the quality of the care provided. Aim The purpose of the present study was to explore and describe the experiences and perceptions of nurses working in an ICU during the COVID-19 global pandemic. Study design Qualitative research was undertaken, using an empirical approach and inductive content analysis techniques. Methods The selected population consisted of ICU nurses from a tertiary teaching hospital in Spain. Data were obtained via semi-structured videocall interviews from Apr 12th to Apr 30th, 2020. Subsequently, transcribed verbatims were analysed using the template analysis model of Brooks. Findings A total of 17 nurses comprised the final sample after data saturation. Four main themes emerged from the analysis and 13 subthemes: "providing nursing care," "psychosocial aspects and emotional lability," "resources management and safety" and "professional relationships and fellowship." Conclusion Providing health care by intensive care nursing professionals, during the COVID-19 pandemic, has shown both strong and weak points in the health care system. Nursing care has been influenced by fear and isolation, making it hard to maintain the humanization of the health care. Relevance to clinical practice Implications for practice include optimizing resource management (human and material), providing psychological support, and adequate training for ICU nurses, as well as high-quality protocols for future emergency situations.
TL;DR: Tocilizumab might be useful in COVID-19 patients with hyperinflammatory state and should be prioritized for randomized trials, according to clinical and laboratory parameters.
University of Oxford1, University of Amsterdam2, Nottingham University Hospitals NHS Trust3, University of Seville4, Sichuan University5, Pfizer6, Newcastle University7, Newcastle upon Tyne Hospitals NHS Foundation Trust8, University of Cambridge9, Örebro University10, University of Bern11, University of Turin12, Linköping University13, University of Helsinki14, National and Kapodistrian University of Athens15, University of Lisbon16, University of Milan17, University of Palermo18, Catholic University of the Sacred Heart19, RWTH Aachen University20, University of Nottingham21, University Hospitals Birmingham NHS Foundation Trust22, Boehringer Ingelheim23, Novo Nordisk24, Novartis25, Takeda Pharmaceutical Company26, AstraZeneca27, Bristol-Myers Squibb28
TL;DR: In this paper, the authors evaluated the diagnostic accuracy of non-invasive index tests against histology as the reference standard, in adult patients with non-alcoholic fatty liver disease (NAFLD).
TL;DR: COPD remains prevalent in Spain and frequently underdiagnosed, with significant social and clinical differences including living alone, previous respiratory diagnoses, more comorbidities measured with the Charlson index, greater BODE and COTE scores, cognitive impairment, and depression.
Abstract: Background: Two previous national epidemiological studies, IBERPOC in 1997 and EPISCAN in 2007, determined the COPD burden in Spain. Changes in demographics and exposure to risk factors demand the periodic update of COPD prevalence and its determinants. Methods: EPISCAN II aimed to estimate the prevalence of COPD in the general population aged 40 years or older in all 17 regions of Spain. A random population screening sample, requiring 600 participants per region performed a questionnaire plus post-bronchodilator (post-BD) spirometry. Results: A total of 12,825 subjects were initially contacted, and 9433 (73.6%) agreed to participate, of whom 9092 performed a valid spirometry. Baseline characteristics were: 52.6% women, mean ± SD age 60 ± 11 years, 19.8% current- and 34.2% former-smokers. The prevalence of COPD measured by post-BD fixed ratio FEV1/FVC < 0.7 was 11.8% (95% C.I. 11.2–12.5) with a high variability by region (2.4-fold). Prevalence was 14.6% (95% C.I. 13.5–15.7) in males and 9.4% (95% C.I. 8.6–10.2) in females; according to the lower limit of normal (LLN) was 6.0% (95% C.I. 5.5–6.5) overall, by sex being 7.1% (95% C.I. 6.4–8.0) in males and 4.9% (95% C.I. 4.3–5.6) in females. Underdiagnosis of COPD was 74.7%. Cases with COPD were a mean of seven years older, more frequently male, of lower attained education, and with more smokers than the non-COPD population (p < 0.001). However, the number of cigarettes and pack-years in non-COPD participants was substantial, as it was the reported use of e-cigarettes (7.0% vs. 5.5%) (p = 0.045). There were also significant social and clinical differences including living alone, previous respiratory diagnoses, more comorbidities measured with the Charlson index, greater BODE and COTE scores, cognitive impairment, and depression (all p < 0.001). Conclusions: COPD remains prevalent in Spain and frequently underdiagnosed.
TL;DR: In this paper, the efficacy of the combination of nivolumab (nivo) plus ipilimumab (ipi) as a first-line therapy with respect to the 12-month overall survival (OS) in patients with cancer was evaluated.
Abstract: PURPOSEThis study aimed to assess the efficacy of the combination of nivolumab (nivo) plus ipilimumab (ipi) as a first-line therapy with respect to the 12-month overall survival (OS) in patients wi...
University of Seville1, University of Novi Sad2, University of Jena3, University of Zagreb4, Technical University of Denmark5, Spanish National Research Council6, Instituto Nacional de Saúde Dr. Ricardo Jorge7, Slovak University of Agriculture8, University of Murcia9, University of Messina10, University of Milan11, Cyprus University of Technology12, University of Agricultural Sciences, Dharwad13, Teagasc14, Ghent University15, University College Cork16
TL;DR: Carotenoids are isoprenoids widely distributed in foods that have been always part of the diet of humans as mentioned in this paper, and they are also attracting interest in the context of nutricosmetics, as they have been shown to provide cosmetic benefits when ingested in appropriate amounts.
Abstract: Carotenoids are isoprenoids widely distributed in foods that have been always part of the diet of humans. Unlike the other so-called food bioactives, some carotenoids can be converted into retinoids exhibiting vitamin A activity, which is essential for humans. Furthermore, they are much more versatile as they are relevant in foods not only as sources of vitamin A, but also as natural pigments, antioxidants, and health-promoting compounds. Lately, they are also attracting interest in the context of nutricosmetics, as they have been shown to provide cosmetic benefits when ingested in appropriate amounts. In this work, resulting from the collaborative work of participants of the COST Action European network to advance carotenoid research and applications in agro-food and health (EUROCAROTEN, www.eurocaroten.eu, https://www.cost.eu/actions/CA15136/#tabs|Name:overview) research on carotenoids in foods and feeds is thoroughly reviewed covering aspects such as analysis, carotenoid food sources, carotenoid databases, effect of processing and storage conditions, new trends in carotenoid extraction, daily intakes, use as human, and feed additives are addressed. Furthermore, classical and recent patents regarding the obtaining and formulation of carotenoids for several purposes are pinpointed and briefly discussed. Lastly, emerging research lines as well as research needs are highlighted.
Sophia Frangou1, Amirhossein Modabbernia2, Steven Williams3, Efstathios Papachristou4 +208 more•Institutions (83)
TL;DR: In this paper, the authors used fractional polynomial regression to quantify the association between age and cortical thickness, and computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method.
Abstract: Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
Mississippi State University1, National Renewable Energy Laboratory2, Pacific Northwest National Laboratory3, Deakin University4, University of Seville5, Hydro-Québec6, Virginia Tech7, University of Manchester8, Georgia Institute of Technology9, Imperial College London10, University of Southampton11, Northeastern University12, North China Electric Power University13
TL;DR: In this paper, the authors discuss the advantages of dynamic state estimation (DSE) as compared to static state estimation, and the implementation differences between the two, including the measurement configuration, modeling framework and support software features.
Abstract: Power system dynamic state estimation (DSE) remains an active research area. This is driven by the absence of accurate models, the increasing availability of fast-sampled, time-synchronized measurements, and the advances in the capability, scalability, and affordability of computing and communications. This paper discusses the advantages of DSE as compared to static state estimation, and the implementation differences between the two, including the measurement configuration, modeling framework and support software features. The important roles of DSE are discussed from modeling, monitoring and operation aspects for today's synchronous machine dominated systems and the future power electronics-interfaced generation systems. Several examples are presented to demonstrate the benefits of DSE on enhancing the operational robustness and resilience of 21st century power system through time critical applications. Future research directions are identified and discussed, paving the way for developing the next generation of energy management systems and novel system monitoring, control and protection tools to achieve better reliability and resiliency.
TL;DR: In this paper, the full phenotypic expression of non-alcoholic fatty liver disease (NAFLD) in lean subjects is incompletely characterised and the long-term prognosis of Caucasian lean subjects with NAFLD is investigated.
Abstract: Objective The full phenotypic expression of non-alcoholic fatty liver disease (NAFLD) in lean subjects is incompletely characterised. We aimed to investigate prevalence, characteristics and long-term prognosis of Caucasian lean subjects with NAFLD. Design The study cohort comprises 1339 biopsy-proven NAFLD subjects from four countries (Italy, UK, Spain and Australia), stratified into lean and non-lean (body mass index (BMI) Results Lean patients represented 14.4% of the cohort and were predominantly of Italian origin (89%). They had less severe histological disease (lean vs non-lean: non-alcoholic steatohepatitis 54.1% vs 71.2% p 10 483 person-years), 4.7% of lean vs 7.7% of non-lean patients reported liver-related events (p=0.37). No difference in survival was observed compared with non-lean NAFLD (p=0.069). Conclusions Caucasian lean subjects with NAFLD may progress to advanced liver disease, develop metabolic comorbidities and experience cardiovascular disease (CVD) as well as liver-related mortality, independent of longitudinal progression to obesity and PNPLA3 genotype. These patients represent one end of a wide spectrum of phenotypic expression of NAFLD where the disease manifests at lower overall BMI thresholds. Lay summary NAFLD may affect and progress in both obese and lean individuals. Lean subjects are predominantly males, have a younger age at diagnosis and are more prevalent in some geographic areas. During the follow-up, lean subjects can develop hepatic and extrahepatic disease, including metabolic comorbidities, in the absence of weight gain. These patients represent one end of a wide spectrum of phenotypic expression of NAFLD.
University of the Basque Country1, University of Castilla–La Mancha2, University of Navarra3, Technical University of Madrid4, University of Las Palmas de Gran Canaria5, Universidad Miguel Hernández de Elche6, University of Cantabria7, University of Seville8, University of Cádiz9, University of Valencia10, University of León11, University of the Balearic Islands12, University of Extremadura13, University of Granada14, University of Zaragoza15
TL;DR: In this article, the authors analyse the changes in physical activity and sedentary behaviours in Spanish university students before and during the confinement by COVID-19 with special focus on gender.
Abstract: During the COVID-19 pandemic, entire populations were instructed to live in home-confinement to prevent the expansion of the disease. Spain was one of the countries with the strictest conditions, as outdoor physical activity was banned for nearly two months. This study aimed to analyse the changes in physical activity and sedentary behaviours in Spanish university students before and during the confinement by COVID-19 with special focus on gender. We also analysed enjoyment, the tools used and motivation and impediments for doing physical activity. An online questionnaire, which included the International Physical Activity Questionnaire Short Form and certain "ad hoc" questions, was designed. Students were recruited by distributing an invitation through the administrative channels of 16 universities and a total of 13,754 valid surveys were collected. Overall, university students reduced moderate (-29.5%) and vigorous (-18.3%) physical activity during the confinement and increased sedentary time (+52.7%). However, they spent more time on high intensity interval training (HIIT) (+18.2%) and mind-body activities (e.g., yoga) (+80.0%). Adaptation to the confinement, in terms of physical activity, was handled better by women than by men. These results will help design strategies for each gender to promote physical activity and reduce sedentary behaviour during confinement periods.
TL;DR: In this article, the evolution and current trends in aerial robotic manipulation, comprising helicopters, conventional underactuated multirotors, and multidirectional thrust platforms equipped with a wide variety of robotic manipulators capable of physically interacting with the environment, are analyzed.
Abstract: This article analyzes the evolution and current trends in aerial robotic manipulation, comprising helicopters, conventional underactuated multirotors, and multidirectional thrust platforms equipped with a wide variety of robotic manipulators capable of physically interacting with the environment. It also covers cooperative aerial manipulation and interconnected actuated multibody designs. The review is completed with developments in teleoperation, perception, and planning. Finally, a new generation of aerial robotic manipulators is presented with our vision of the future.
University of Wollongong1, Paul Sabatier University2, Delft University of Technology3, University of Seville4, University of Lausanne5, SLAC National Accelerator Laboratory6, University of California, San Francisco7, Radboud University Nijmegen8, University of Bordeaux9, Tomsk State University10, CERN11, Kurchatov Institute12, University of Ioannina13, Sapienza University of Rome14, University of Navarra15, Institut de radioprotection et de sûreté nucléaire16, National Physical Laboratory17, Lund University18, KEK19, Australian National University20
TL;DR: The tests included in G4-Med are described and the results derived from the benchmarking of Geant4 10.5 against reference data will aid users in tailoring physics lists to their particular application.
Abstract: Background: Geant4 is a Monte Carlo code extensively used in medical physics for a wide range of applications, such as dosimetry, micro- and nanodosimetry, imaging, radiation protection, and nuclear medicine. Geant4 is continuously evolving, so it is crucial to have a system that benchmarks this Monte Carlo code for medical physics against reference data and to perform regression testing. Aims: To respond to these needs, we developed G4-Med, a benchmarking and regression testing system of Geant4 for medical physics. Materials and Methods: G4-Med currently includes 18 tests. They range from the benchmarking of fundamental physics quantities to the testing of Monte Carlo simulation setups typical of medical physics applications. Both electromagnetic and hadronic physics processes and models within the prebuilt Geant4 physics lists are tested. The tests included in G4-Med are executed on the CERN computing infrastructure via the use of the geant-val web application, developed at CERN for Geant4 testing. The physical observables can be compared to reference data for benchmarking and to results of previous Geant4 versions for regression testing purposes. Results: This paper describes the tests included in G4-Med and shows the results derived from the benchmarking of Geant4 10.5 against reference data. Discussion: Our results indicate that the Geant4 electromagnetic physics constructor G4EmStandardPhysics_option4 gives a good agreement with the reference data for all the tests. The QGSP_BIC_HP physics list provided an overall adequate description of the physics involved in hadron therapy, including proton and carbon ion therapy. New tests should be included in the next stage of the project to extend the benchmarking to other physical quantities and application scenarios of interest for medical physics. Conclusion: The results presented and discussed in this paper will aid users in tailoring physics lists to their particular application. (Less)
TL;DR: A comprehensive review of HVDC CBs technologies, including recent significant attempts in the development of modern high voltage direct current CBs, is presented in this article, where the functional analysis of each technology is presented.
Abstract: High voltage direct current (HVDC) systems are now well integrated into AC systems in many jurisdictions. The integration of renewable energy sources (RESs) is a major focus and the role of HVDC systems is expanding. However, the protection of HVDC systems against DC faults is a challenging issue that can have negative impacts on the reliable and safe operation of power systems. Practical solutions to protect HVDC grids against DC faults without a widespread power outage include: 1) using DC circuit breakers (CBs) to isolate the faulty DC-link, 2) using a proper converter topology to interrupt the DC fault current, and/or 3) using high-power DC transformers and DC hubs at strategic points within DC grids. The application of HVDC CBs is identified as the best approach that satisfies both DC grids and connected AC grids’ requirements. This article reports a comprehensive review of HVDC CBs technologies, including recent significant attempts in the development of modern HVDC CBs. The functional analysis of each technology is presented. Additionally, different technologies based on information obtained from literature are compared. Finally, recommendations for the improvement of CBs are presented.
University of Bologna1, Başkent University2, University of Belgrade3, Koç University4, Medical University of Graz5, Ciba Specialty Chemicals6, Royal College of Physicians of Ireland7, University of Verona8, Semmelweis University9, National and Kapodistrian University of Athens10, Radboud University Nijmegen11, University of Seville12
TL;DR: The ESCMID COVID-19 guidelines task force was established by the ESCMIDs Executive Committee in 2019 and a small group was established, half appointed by the chair, and the remaining selected with an open call as discussed by the authors.
Newcastle University1, Boehringer Ingelheim2, University of Turin3, University of Palermo4, Catholic University of the Sacred Heart5, University of Milan6, University of Seville7, National and Kapodistrian University of Athens8, Minia University9, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico10, Newcastle upon Tyne Hospitals NHS Foundation Trust11
TL;DR: In this article, the most common non-invasive scoring systems (NFS, FIB-4, BARD, APRI) and the Hepamet fibrosis score (HFS) were assessed in 1,173 European patients with NAFLD from tertiary centres.
TL;DR: In this article, the authors reviewed the literature from 2000 to 2017 and analyzed the environmental conditions that have influenced the transitions towards becoming potential entrepreneurs, nascent/new entrepreneurs, and established/consolidated entrepreneurs in both developed and developing economies.
Abstract: Over the past 30 years, the academic literature has legitimised the significant impact of environmental conditions on entrepreneurial activity. In the past 5 years, in particular, the academic debate has focused on the elements that configure entrepreneurship ecosystems and their influence on the creation of high-growth ventures. Previous studies have also recognised the heterogeneity of environmental conditions (including policies, support programs, funding, culture, professional infrastructure, university support, labour market, R&D, and market dynamics) across regions/countries. Yet, an in-depth discussion is required to address how environmental conditions vary per entrepreneurial stage of enterprises within certain regions/countries, as well as how these conditions determine the technological factor of the entrepreneurial process. By reviewing the literature from 2000 to 2017, this paper analyses the environmental conditions that have influenced the transitions towards becoming potential entrepreneurs, nascent/new entrepreneurs, and established/consolidated entrepreneurs in both developed and developing economies. Our findings show why diversity in entrepreneurship and context is significant. Favourable conditions include professional support, incubators/accelerators, networking with multiple agents, and R&D investments. Less favourable conditions include a lack of funding sources, labour market conditions, and social norms. Our paper contributes by proposing a research agenda and implications for stakeholders.
TL;DR: This review will summarise the current state-of-the-art in PDT, with special focus on the different available photosensitizers, their chemistry, their incorporation into different nanostructures, and some of the current targeting strategies.
Abstract: The reactions of some structures to different external stimuli can be used for therapeutic purposes. In particular, in photodynamic therapy (PDT), a light-sensitive compound or structure, commonly named a photosensitizer (PS), is able to produce reactive oxygen species (ROS) after being irradiated with light in the presence of oxygen. Such ROS are effective in destroying cells and can be used as therapeutic agents to treat some skin and eye diseases, as well as certain types of cancer. This review will summarise the current state-of-the-art in PDT, with special focus on the different available photosensitizers, their chemistry, their incorporation into different nanostructures, and some of the current targeting strategies.
TL;DR: In this paper, the authors investigated the positive aspects associated with the COVID-19 pandemic and the possible health prevention and promotion strategies by analyzing the available scientific evidence, focusing on the constructs of resilience, coping strategies and posttraumatic growth (PTG).
Abstract: The COVID-19 pandemic represents a traumatic event that has profoundly changed working conditions with detrimental consequences for workers' health, in particular for the healthcare population directly involved in addressing the emergency. Nevertheless, previous research has demonstrated that traumatic experiences can also lead to positive reactions, stimulating resilience and feelings of growth. The aim of this narrative review is to investigate the positive aspects associated with the COVID-19 pandemic and the possible health prevention and promotion strategies by analyzing the available scientific evidence. In particular, we focus on the constructs of resilience, coping strategies and posttraumatic growth (PTG). A literature search was performed on the PubMed, EMBASE, Scopus, Web of Science, Google Scholar and Psycinfo databases. Forty-six articles were included in the literature synthesis. Psychological resilience is a fundamental variable for reducing and preventing the negative psychological effects of the pandemic and is associated with lower levels of depression, anxiety and burnout. At the individual and organizational level, resilience plays a crucial role in enhancing wellbeing in healthcare and non-healthcare workers. Connected to resilience, adaptive coping strategies are essential for managing the emergency and work-related stress. Several positive factors influencing resilience have been highlighted in the development of PTG. At the same time, high levels of resilience and positive coping strategies can enhance personal growth. Considering the possible long-term coexistence and consequences of COVID-19, organizational interventions should aim to improve workers' adaptive coping skills, resilience and PTG in order to promote wellbeing.
University of Wollongong1, University UCINF2, Indonesia University of Education3, Pennington Biomedical Research Center4, The Chinese University of Hong Kong5, Ibn Tofail University6, National University of Malaysia7, University of Southern Denmark8, Karolinska Institutet9, Georgia Regents University10, Pham Ngoc Thach University of Medicine11, University of Seville12, Linköping University13, University of Colombo14, University of the Witwatersrand15
TL;DR: PA and SST levels of children from LMICs have been less impacted by COVID-19 than in HICs, and Ensuring children can access an outdoor space, and supporting caregivers’ mental health are important prevention strategies.
Abstract: The restrictions associated with the 2020 COVID-19 pandemic has resulted in changes to young children’s daily routines and habits. The impact on their participation in movement behaviours (physical activity, sedentary screen time and sleep) is unknown. This international longitudinal study compared young children’s movement behaviours before and during the COVID-19 pandemic. Parents of children aged 3–5 years, from 14 countries (8 low- and middle-income countries, LMICs) completed surveys to assess changes in movement behaviours and how these changes were associated with the COVID-19 pandemic. Surveys were completed in the 12 months up to March 2020 and again between May and June 2020 (at the height of restrictions). Physical activity (PA), sedentary screen time (SST) and sleep were assessed via parent survey. At Time 2, COVID-19 factors including level of restriction, environmental conditions, and parental stress were measured. Compliance with the World Health Organizations (WHO) Global guidelines for PA (180 min/day [≥60 min moderate- vigorous PA]), SST (≤1 h/day) and sleep (10-13 h/day) for children under 5 years of age, was determined. Nine hundred- forty-eight parents completed the survey at both time points. Children from LMICs were more likely to meet the PA (Adjusted Odds Ratio [AdjOR] = 2.0, 95%Confidence Interval [CI] 1.0,3.8) and SST (AdjOR = 2.2, 95%CI 1.2,3.9) guidelines than their high-income country (HIC) counterparts. Children who could go outside during COVID-19 were more likely to meet all WHO Global guidelines (AdjOR = 3.3, 95%CI 1.1,9.8) than those who were not. Children of parents with higher compared to lower stress were less likely to meet all three guidelines (AdjOR = 0.5, 95%CI 0.3,0.9). PA and SST levels of children from LMICs have been less impacted by COVID-19 than in HICs. Ensuring children can access an outdoor space, and supporting parents’ mental health are important prerequisites for enabling pre-schoolers to practice healthy movement behaviours and meet the Global guidelines.
TL;DR: This is the first attempt to apply arithmetic operation SNPS to fuse multiple information and the effectiveness of the presented general arithmetic SNPS calculator is verified by means of several examples.
Abstract: Several variants of spiking neural P systems (SNPS) have been presented in the literature to perform arithmetic operations However, each of these variants was designed only for one specific arithm