Search

Fibrosis is a common denominator of several pathological conditions. Over the last decade, Calreticulin has emerged as a critical player in the fibrotic processes in many tissues and organs. Here we review the recent advances in our understanding of the regulatory roles of Calreticulin in renal fibrosis. In particular, a proteomic screen that we performed more than 15 years ago, for the identification of novel components involved in the mechanisms of renal fibrosis, led to the observation that Calreticulin is associated with the initiation and progression of kidney fibrosis in a rodent model. We also showed that altered expression levels of Calreticulin in vitro and in vivo are significantly affecting the fibrotic phenotype in cellular systems and animal models, respectively. We also identified an upstream regulatory mechanism that mediates the transcriptional control of Calreticulin expression during the progression of renal fibrosis, by showing that the druggable orphan nuclear receptor NR5A2 and its SUMOylation is involved in this action. These data provide novel targets for future pharmacological interventions against fibrosis. In addition, further proteomic analysis uncovered a correlation between the up-regulation of Calreticulin and that of 14-3-3σ protein. Collectively, our previous observations suggest that Calreticulin is a central node in a regulatory axis that controls the initiation and progression of renal fibrosis.

Presently, computational thinking (CT) is considered necessary for adapting to the future. Concurrently, the COVID-19 pandemic has accentuated the demand for strengthening Environmental Education as a means to improve sustainability and stimulate environmental protection and public health. Having in mind that CT does not concern only technocrats but also applies in solving everyday problems, we introduce the novel idea of the synergistic learning of CT and Environmental Study. Thus, our research aim is to explore the correlation between algorithmic thinking (AT), as a fundamental CT competency, and educational achievements in the Environmental Study course during the early primary school years. Towards this end, we implemented a quantitative research study, employing an innovative assessment framework we propose. The adoption of cluster sampling eventuated in a sample of 435 students. The exploitation of ordinal logistic regression analysis and machine learning method validated the correlation of the two fields and pointed out that AT levels constitute a predictive factor for performance in the Environmental Study course and vice versa. These results support the novel idea of concurrently cultivating environmental consciousness and CT and build a robust base for future studies that will focus on providing an ecological reflection on CT activities.

Cardiac valve calcification (CVC) is a predictor of cardiovascular disease and all-cause mortality in end stage kidney disease (ESKD) patients. Several risk factors are related to CVC in patients with ESKD including traditional ones as well as inflammation, bone mineral disease and malnutrition. Adiposity is associated with dyslipidemia and proinflammatory activity which could predispose for CVC. Sarcopenia or dynapenia is a state common in patients with ESKD. This study aimed to investigate the relationship of adiposity, sarcopenia and malnutrition-inflammation markers with CVC in patients on maintenance hemodialysis.CVC in aortic (AVC), mitral valves (MVC) and systolic and diastolic dysfunction (DD) were assessed by using two-dimensional echocardiography. Nutritional, adiposity and anthropometric assessments were made using several indices respectively. Creatinine index and muscle strength measurements were also performed. Biochemical parameters such as total proteins, albumin, calcium, phosphate, plasma lipoproteins, C-Reactive Protein and parathyroid hormone were also measured.Adiposity, nutritional, and sarcopenia parameters did not show any difference between patients with or without CVC. Age ≥ 65 years [PR: 1.47 p = 0.012], DD [PR: 2.31, p = 0.005], high CRP/albumin ratio [PR: 1.46, p = 0.01], mid arm circumference (MAC) 26 cm [PR: 1.37, p = 0.03] were associated with increased prevalence of AVC, while DD [PR: 1.97 p = 0.02], high CRP/albumin ratio [PR: 1.56, p = 0.02], and MAC26 cm [PR: 1.52, p = 0.01], showed positive correlation with MVC. Age ≥ 65 years [PR: 1.33, p = 0.028], DD [PR: 1.72, p = 0.01], high CRP/albumin ratio [PR: 1.53, p = 0.003], and MAC26 cm [PR: 1.4, p = 0.006], related to greater prevalence of calcification at any valve.Ageing, diastolic dysfunction, MAC and increased CRP/albumin ratio were powerful predictors of CVC in patients on hemodialysis.

International audience; This letter introduces the new European Settlement Map (ESM) production workflow, presents some indicatory results, and discusses the validation process. Unlike the previous ESM versions, the built-up (BU) extraction is realized through supervised learning (not only by means of image filtering and processing techniques) based on textural and morphological features. Input data are the Copernicus very-high-resolution image collection for the reference year 2015 coming from a variety of sensors. The workflow is fully automated, and it does not include any postprocessing. For the first time, a new layer containing nonresidential buildings was derived by using only remote sensing imagery and training data. The produced BU map is delivered at 2-m-pixel resolution (level-1 layer), while the residential/nonresidential layer (level 2) is delivered at 10-m spatial resolution. More than 46,000 scenes were processed, and around 6 million km² of the European territory was mapped. The workflow was executed on the JRC Big Data platform. The validation showed a balanced accuracy of 0.81 and 0.91 for level 1 and 2 layers, respectively, and 0.71 for only the nonresidential layer.

The present paper presents the planning, implementation, observation and analysis of both quantitative and qualitative data of a participatory action research, aiming to study the potential role, value and uses of MOOCs in secondary education. Within the context of this research, a computer programming hybrid MOOC (named PROG15) which combined aspects of both x- and c-MOOCs architecture and pedagogy was designed, implemented and openly provided to Greek Secondary Education students.The MOOC completion rate (xMOOC dimension) was relatively low, but similar to that of typical xMOOCs for adults, while the degree of collaboration with other students and contribution to the course content (the cMOOC dimension) was relatively average. Before their involvement in the MOOC, the participating students recorded particularly high learning expectations from the specific course and from the collaborative learning model it proposed and quite positive views regarding the impact of this new educational tool on secondary education. Their attitude towards these issues was even more positive after their involvement in the MOOC, while their overall experience was particularly positive.The above findings, although they resulted from a comparatively small sample of students for the measures of MOOCs and within a very specific educational context, they form a particularly promising background for the utilization of this new tool in secondary education in general and specifically for the preparation of students for higher education studies, in subjects related to computer programming. Of course, further research and investigation is required on the design, development and implementation of the next generation of MOOCs and the practical and theoretical research outcomes resulted from this research can be a quite valuable input.

Stenosis or obstruction of neck great veins represent a frequent and severe complication in hemodialysis patients. Endovascular treatment with percutaneous transluminal angioplasty and/or stenting of these veins is the gold standard to restore patency. However, the jugular vein is frequently overstented in these cases and this might lead to persistent symptomatology of those patients also losing an access for future catheter placement. Herein, we present the 6-months performance of a Y-shaped stenting of the brachiocephalic and internal jugular vein leading to complete resolution of the symptoms, and maintenance of the jugular vein access.

Although a consensus on the definition of computational thinking (CT) has yet to be achieved, teaching resources and associated reforms of curricula encapsulating CT are in use. As such, the assessment of these efforts is essential in order to successfully introduce CT into curricula. This chapter conducts a literature review of recent studies on CT assessment, presenting them in three categories based on their approach: (a) assessment using specific programming environments, (b) assessment using scales/psychometric tools, and (c) assessment using multiple forms/methods. We find that CT assessment faces unresolved issues, including the inability to cover all concepts and student age groups, the lack of scientific documentation and validation, and the dearth of tools to autonomously and efficiently assess CT. Findings also state a relation of CT with cognitive skills development. We propose that the use of multiple methods continues to be the most appropriate approach for CT assessment.

Computational thinking (CT) is an essential skill for students in the twenty-first century, constituting a set of universally applicable problem-solving strategies. While CT models emphasize the importance of testing and debugging as a fundamental CT practice, few studies have explicitly addressed its application for primary school students. This study aimed to investigate the effect of a CT instructional intervention on primary school students’ debugging (a) proficiency level and (b) strategy use. The 43 pairs of participants worked with Scratch, a block-based visual programming language. Data collection involved think-aloud protocols, prompted written descriptions of the students’ actions, semi-structured interviews, screen recordings, and a rubric. We measured students’ debugging proficiency level and strategy use on four learning units of the instructional intervention. The results of the analysis suggest that the sequence of CT activities we followed, and especially game debugging activities, can improve students’ debugging proficiency level and lead to the systematic application of debugging.

For critically ill patients with coronavirus disease 2019 (COVID-19) who require intensive care unit (ICU) admission, extremely high mortality rates (even 97%) have been reported. We hypothesized that overburdened hospital resources by the extent of the pandemic rather than the disease per se might play an important role on unfavorable prognosis. We sought to determine the outcome of such patients admitted to the general ICUs of a hospital with sufficient resources. We performed a prospective observational study of adult patients with COVID-19 consecutively admitted to COVID&mdash, designated ICUs at Evangelismos Hospital, Athens, Greece. Among 50 patients, ICU and hospital mortality was 32% (16/50). Median PaO2/FiO2 was 121 mmHg (interquartile range (IQR), 86&ndash, 171 mmHg) and most patients had moderate or severe acute respiratory distress syndrome (ARDS). Hospital resources may be an important aspect of mortality rates, since severely ill COVID-19 patients with moderate and severe ARDS may have understandable mortality, provided that they are admitted to general ICUs without limitations on hospital resources.

Background: For critically ill patients with coronavirus disease 2019 (COVID-19) who require intensive care unit (ICU) admission, mortality rates vary widely depending on many factors, among which hospital resources and clinical setting seem important. We sought to determine the outcome of critically ill patients admitted in the usual multidisciplinary ICUs of a big referral for COVID-19 tertiary-care hospital with adequate resources.Methods: We performed a prospective observational study of all adult patients with COVID-19 consecutively admitted to four COVID-designated ICUs at Evangelismos Hospital, Athens, Greece, from March 11 to April 27, 2020.Results: Among 50 critically ill patients, ICU and hospital mortality for the entire cohort was 32% (16/50), whereas 66% (33/50) of patients were discharged alive from the ICU and 2% (1/50) were still treated in the ICU until June 16, 2020. ICU and hospital mortality for those who received invasive mechanical ventilation was 39% (16/41). Patients who eventually died had already increased risk of death on ICU admission, as suggested by the high values of the Acute Physiology and Chronic Health Evaluation II and Sequential Organ Failure Assessment scores, the presence of current malignancy and occurrence of cardiac arrest in 44% (7/16) of patients, and the general need for circulatory support by noradrenaline. Median PaO2/FiO2 on ICU admission for the entire cohort was 121 mmHg [interquartile range (IQR), 86-171 mmHg] and most patients had moderate and severe acute respiratory distress syndrome (ARDS) according to the Berlin Definition. The primary cause of death of all patients was multi-organ failure, most commonly due to sepsis, whereas none died from refractory hypoxemia, neurologic dysfunction or withdrawal of life support. Hospital stay was long in patients who survived [median 24 days (IQR, 15-35 days)] and was frequently complicated by bacteremias [36% (12/33)].Conclusion: Severely ill COVID-19 patients with moderate and severe ARDS may have equal or even lower mortality rates compared to ARDS due to other causes, when they are admitted in general ICUs with experienced and adequate staff without limitations in hospital resources, where established ARDS therapies are used.

Large-scale land cover classification from satellite imagery is still a challenge due to the big volume of data to be processed, to persistent cloud-cover in cloud-prone areas as well as seasonal artefacts that affect spatial homogeneity. Sentinel-2 times series from Copernicus Earth Observation program offer a great potential for fine scale land cover mapping thanks to high spatial and temporal resolutions, with a decametric resolution and five-day repeat time. However, the selection of best available scenes, their download together with the requirements in terms of storage and computing resources pose restrictions for large-scale land cover mapping. The dataset presented in this paper corresponds to global cloud-free pixel based composite created from the Sentinel-2 data archive (Level L1C) available in Google Earth Engine for the period January 2017- December 2018. The methodology used for generating the image composite is described and the metadata associated with the 10 m resolution dataset is presented. The data with a total volume of 15 TB is stored on the Big Data platform of the Joint Research Centre. It can be downloaded per UTM grid zone, loaded into GIS clients and displayed easily thanks to pre-computed overviews.

Spatially consistent and up-to-date maps of human settlements are crucial for addressing policies related to urbanization and sustainability, especially in the era of an increasingly urbanized world.The availability of open and free Sentinel-2 data of the Copernicus Earth Observation program offers a new opportunity for wall-to-wall mapping of human settlements at a global scale.This paper presents a deep-learning-based framework for a fully automated extraction of built-up areas at a spatial resolution of 10 m from a global composite of Sentinel-2 imagery.A multi-neuro modeling methodology building on a simple Convolution Neural Networks architecture for pixel-wise image classification of built-up areas is developed.The core features of the proposed model are the image patch of size 5 x 5 pixels adequate for describing built-up areas from Sentinel-2 imagery and the lightweight topology with a total number of 1,448,578 trainable parameters and 4 2D convolutional layers and 2 flattened layers.The deployment of the model on the global Sentinel-2 image composite provides the most detailed and complete map reporting about built-up areas for reference year 2018. The validation of the results with an independent reference data-set of building footprints covering 277 sites across the world establishes the reliability of the built-up layer produced by the proposed framework and the model robustness., Comment: 51 pages including supplementary material, 13 Figures in the main manuscript, under review in Neural Computing and Applications journal

This chapter focuses on the “unplugged” approach for teaching computational thinking (CT), that is, teaching without the use of computers or digital equipment. After a short discussion of the different definitions of CT, the chapter presents the most well-known tools and methodologies of unplugged philosophy, with a connection to CT concepts. The chapter also summarizes the main advantages of the unplugged approach to CT education and furthermore, the most important design principles of unplugged, kinaesthetic activities. A separate section is dedicated to blended approaches of plugged and unplugged activities and the evaluation of unplugged approaches. While more large-scale implementations are still required to fully evaluate the benefits of unplugged approaches to CT education, existing studies report positive findings, especially in relation to the use of unplugged approaches for CT education. The majority of these resources are available for use by educators free of charge on the internet, which makes them very useful as a CT teaching approach.

Continuous global-scale mapping of human settlements in the service of international agreements calls for massive volume of multi-source, multi-temporal, and multi-scale earth observation data. In ...

The revised and enhanced version of the new European Settlement Map is presented together with the first results. An added-value to the previous versions is the improved automatic detection of buildings, automatic extraction of water, extraction of building typology and an information layer allowing to derive city indicators. The ESM workflow is fully automatic and runs on the Joint Research Centre Earth Observation Data and Processing Platform.

Geo-information on settlements from Earth Observation offers a base for objective and scalable monitoring of the evolution of cities and settlements, including their location, extent and other attr...

The main purpose of this study was to investigate and compare the attitudes of freshmen and senior students of the Department of Primary Education, University of Thessaly, Greece, towards Information and Communications Technology (ICT) in Education. Moreover, this study explored the possible existence of correlations between the variables of the attitudes and the influence of various factors related to their formation. The research project has adopted the characteristics of a comparative study. The survey results have showed that the freshmen students of the specific sample display a more positive attitude towards the computer as an essential teaching tool; they also recognize to a greater degree the necessity of consistent ICT use in contemporary education and are more willing to incorporate computer use in their future teaching assignments. Last, the most powerful factor that affects the attitudes of prospective teachers is the viewpoint of their university professors who teach ICT-related courses.

The Gerbode defect is characterized by a perimembranous ventricular septal defect between the left ventricle and the right atrium. This intracardiac shunt is a congenital defect but may be iatrogenic after valve surgery or atrioventricular node ablation, may be the result of endocarditis or may be traumatic. It is really rarely encountered as sequelae of non-penetrating heart trauma, and their clinical manifestations may often be unrecognized in the multi-injured patient. However, they are serious complications, and their diagnostic approach is not always feasible. We hereby present a case of a young man with the left ventricle to the right atrium communication after blunt thoracic trauma due to a car accident and concomitant rupture of the thoracic aorta. We present also the case and the ways of treatment according to the international bibliography.

Summary We report the life-saving administration of thrombolysis during cardiopulmonary resuscitation in a patient with recent intracerebral haemorrhage. A 53-year-old male with intracerebral haemorrhage was admitted to the intensive care unit. On the 24th day of treatment he suffered cardiac arrest with pulseless electrical activity. Transoesophageal echocardiography was performed during ongoing cardiopulmonary resuscitation. Thrombi in the right heart cavities with excessive right ventricular dysfunction confirmed the diagnosis of fulminant pulmonary embolism. Permanent restoration of a spontaneous rhythm was feasible only after administration of systemic thrombolysis with recombinant tissue plasminogen activator. Neurological examination and a computed tomogram of the brain did not show rebleeding. We conclude that under extreme circumstances absolute contraindications to thrombolysis should be weighed against the potential benefit.

The paper addresses built up information extraction from high resolution imagery from two satellites, ZY-1 02C and SPOT-5. The testing is part of a larger experiment that explores spectral, textural and morphological satellite image properties aiming to extract built up information for global built up mapping and characterization. In this work we test SPOT-5 and ZY-1 02C satellites for textural properties associated to built-up. The work is exploratory in nature. We compute image textures using a ”built-up presence index (Pantex)” algorithm. We then compare the texture values with a reference built-up map derived from building footprints map by computing the Receiver Operative Characteristics (ROC). We processed four bands: ZY-HR Panchromatic, ZY Panchromatic, and two “brightness” bands derived from the ZY Pan-sharpened, and SPOT Pan-sharpened. Pan-sharpened products combine both the panchromatic and the multispectral imagery. For each dataset we use two texture windows for a total of eight tests. The study is conducted on imagery covering the city of Firenze, Italy. The landscape is characterized by dense city centres as well as rural scattered settlement. The area is deemed suitable to benchmarking imagery for built up information related to human settlements of different densities. The test shows that the information from SPOT and ZY are generating similar result. However, spatial resolution of panchromatic bands show to have great importance over other factors in extracting built up information.