Schadenfreude: Malicious Joy in Social Media Interactions

The paper presents a model of Schadenfreude, pleasure at another’s misfortune, resulting in a typology of cases of this emotion. Four types are singled out: Compensation, Identification, Aversion, and Injustice Schadenfreude. The typology is first tested on a corpus of 472 comments drawn from three social media, Facebook, Twitter and Instagram. Then a specific corpus of comments is collected and analyzed concerning a specific case of Injustice Schadenfreude, the posts concerning Brexit, United Kingdom leaving the European Union. From the analysis, it emerges that spatial or factual closeness does not look necessary to feel Schadenfreude. Finally, a lexicometric automatic analysis is conducted on the general corpus of Italian comments collected using several hashtags and enriched by comments about the fire of Notre Dame, showing how even complex emotions like Schadenfreude can be automatically extracted from social media

The Heliophysics Feature Catalogue, a tool for the study of solar features

The behavior of filaments and prominences during the Solar Cycle is a signature of Sun's activity. It is therefore important to follow their evolution during the cycle, in order to be able to associate it with the various phases of the Solar Cycle as well as with other Solar features or events. The virtual observatory HELIO provides information that can be used for such studies, especially its Heliophysics Feature Catalogue gives a unique access to the description of various features during around one cycle. Features available are: filaments, prominences, photospheric and coronal active regions, coronal radio emission, type III radio bursts, coronal holes and sunspots. Web interfaces allow the user to query data for these features. Useful information can also be shared with other HELIO services, such as Heliophysics Event Catalogue, which provides access to dozens of tables of events such as flares, CME

Penetration of left and right atrial wall and aortic root by an Amplatzer atrial septal occluder in a nine year old boy with Marfan syndrome: Case report

<p>Abstract</p> <p>Background</p> <p>To describe complications associated with Amplatzer septal occluders in a patient with Marfan syndrome</p> <p>Case presentation</p> <p>A nine-year-old boy with Marfan syndrome and a 22 mm atrial septal defect (ASD) was treated successfully by interventional closure of his ASD by placing a 24 mm Amplatzer septal occluder. Follow up examinations showed a good result but an increasing enlargement of aortic root, so the patient was scheduled for operation. Intraoperative findings showed a perforation of the left atrial roof and the non-coronary sinus by penetration of the occluder device as well as penetration into the right atrial wall. The occluder was resected, the ASD was closed and the aortic sinus was reconstructed using a Dacron patch.</p> <p>Conclusion</p> <p>We describe the first case of a patient with Marfan syndrome and an interventional closure of an ASD. Due to alterations of the connective tissue, as it is typical for patients with Marfan syndrome, the Amplatzer occluder probably perforated adjacent structures more easily as in non-affected individuals. Amplatzer occluders should be used with caution and follow up examinations should be performed in short intervals.</p

Autophagy, Inflammation, and Metabolism (AIM) Center of Biomedical Research Excellence:Supporting the next generation of autophagy researchers and fostering international collaborations

Recently, NIH has funded a center for autophagy research named the Autophagy, Inflammation, and Metabolism (AIM) Center of Biomedical Research Excellence, located at the University of New Mexico Health Science Center (UNM HSC), with aspirations to promote autophagy research locally, nationally, and internationally. The center has 3 major missions: (i) to support junior faculty in their endeavors to develop investigations in this area and obtain independent funding; (ii) to develop and provide technological platforms to advance autophagy research with emphasis on cellular approaches for high quality reproducible research; and (iii) to foster international collaborations through the formation of an International Council of Affiliate Members and through hosting national and international workshops and symposia. Scientifically, the AIM center is focused on autophagy and its intersections with other processes, with emphasis on both fundamental discoveries and applied translational research.</p

Long-term patient-important outcomes after septic shock : A protocol for 1-year follow-up of the CLASSIC trial

BackgroundIn patients with septic shock, mortality is high, and survivors experience long-term physical, mental and social impairments. The ongoing Conservative vs Liberal Approach to fluid therapy of Septic Shock in Intensive Care (CLASSIC) trial assesses the benefits and harms of a restrictive vs standard-care intravenous (IV) fluid therapy. The hypothesis is that IV fluid restriction improves patient-important long-term outcomes. AimTo assess the predefined patient-important long-term outcomes in patients randomised into the CLASSIC trial. MethodsIn this pre-planned follow-up study of the CLASSIC trial, we will assess all-cause mortality, health-related quality of life (HRQoL) and cognitive function 1 year after randomisation in the two intervention groups. The 1-year mortality will be collected from electronic patient records or central national registries in most participating countries. We will contact survivors and assess EuroQol 5-Dimension, -5-Level (EQ-5D-5L) and EuroQol-Visual Analogue Scale and Montreal Cognitive Assessment 5-minute protocol score. We will analyse mortality by logistic regression and use general linear models to assess HRQoL and cognitive function. DiscussionWith this pre-planned follow-up study of the CLASSIC trial, we will provide patient-important data on long-term survival, HRQoL and cognitive function of restrictive vs standard-care IV fluid therapy in patients with septic shock.Peer reviewe

Conservative vs liberal fluid therapy in septic shock (CLASSIC) trial-Protocol and statistical analysis plan

Introduction Intravenous (IV) fluid is a key intervention in the management of septic shock. The benefits and harms of lower versus higher fluid volumes are unknown and thus clinical equipoise exists. We describe the protocol and detailed statistical analysis plan for the conservative versus liberal approach to fluid therapy of septic shock in the Intensive Care (CLASSIC) trial. The aim of the CLASSIC trial is to assess benefits and harms of IV fluid restriction versus standard care in adult intensive care unit (ICU) patients with septic shock. Methods CLASSIC trial is an investigator-initiated, international, randomised, stratified, and analyst-blinded trial. We will allocate 1554 adult patients with septic shock, who are planned to be or are admitted to an ICU, to IV fluid restriction versus standard care. The primary outcome is mortality at day 90. Secondary outcomes are serious adverse events (SAEs), serious adverse reactions (SARs), days alive at day 90 without life support, days alive and out of the hospital at day 90 and mortality, health-related quality of life (HRQoL), and cognitive function at 1 year. We will conduct the statistical analyses according to a pre-defined statistical analysis plan, including three interim analyses. For the primary analysis, we will use logistic regression adjusted for the stratification variables comparing the two interventions in the intention-to-treat (ITT) population. Discussion The CLASSIC trial results will provide important evidence to guide clinicians' choice regarding the IV fluid therapy in adults with septic shock.Peer reviewe

Noninvasive ventilation in COVID-19 patients aged ≥ 70 years—a prospective multicentre cohort study

Funding Information: COVIP study did not have any funding. Publication of this article was funded by the Priority Research Area qLife under the program “Excellence Initiative – Research University” at the Jagiellonian University in Krakow (06/IDUB/2019/94). Publisher Copyright: © 2022, The Author(s).Background: Noninvasive ventilation (NIV) is a promising alternative to invasive mechanical ventilation (IMV) with a particular importance amidst the shortage of intensive care unit (ICU) beds during the COVID-19 pandemic. We aimed to evaluate the use of NIV in Europe and factors associated with outcomes of patients treated with NIV. Methods: This is a substudy of COVIP study—an international prospective observational study enrolling patients aged ≥ 70 years with confirmed COVID-19 treated in ICU. We enrolled patients in 156 ICUs across 15 European countries between March 2020 and April 2021.The primary endpoint was 30-day mortality. Results: Cohort included 3074 patients, most of whom were male (2197/3074, 71.4%) at the mean age of 75.7 years (SD 4.6). NIV frequency was 25.7% and varied from 1.1 to 62.0% between participating countries. Primary NIV failure, defined as need for endotracheal intubation or death within 30 days since ICU admission, occurred in 470/629 (74.7%) of patients. Factors associated with increased NIV failure risk were higher Sequential Organ Failure Assessment (SOFA) score (OR 3.73, 95% CI 2.36–5.90) and Clinical Frailty Scale (CFS) on admission (OR 1.46, 95% CI 1.06–2.00). Patients initially treated with NIV (n = 630) lived for 1.36 fewer days (95% CI − 2.27 to − 0.46 days) compared to primary IMV group (n = 1876). Conclusions: Frequency of NIV use varies across European countries. Higher severity of illness and more severe frailty were associated with a risk of NIV failure among critically ill older adults with COVID-19. Primary IMV was associated with better outcomes than primary NIV. Clinical Trial RegistrationNCT04321265, registered 19 March 2020, https://clinicaltrials.gov.publishersversionpublishe

Autophagy, Inflammation, and Metabolism (AIM) Center of Biomedical Research Excellence: supporting the next generation of autophagy researchers and fostering international collaborations

Recently, NIH has funded a center for autophagy research named the Autophagy, Inflammation, and Metabolism (AIM) Center of Biomedical Research Excellence, located at the University of New Mexico Health Science Center (UNM HSC), with aspirations to promote autophagy research locally, nationally, and internationally. The center has 3 major missions: (i) to support junior faculty in their endeavors to develop investigations in this area and obtain independent funding; (ii) to develop and provide technological platforms to advance autophagy research with emphasis on cellular approaches for high quality reproducible research; and (iii) to foster international collaborations through the formation of an International Council of Affiliate Members and through hosting national and international workshops and symposia. Scientifically, the AIM center is focused on autophagy and its intersections with other processes, with emphasis on both fundamental discoveries and applied translational research

Disease-Course Adapting Machine Learning Prognostication Models in Elderly Patients Critically Ill With COVID-19: Multicenter Cohort Study With External Validation.

BACKGROUND: The COVID-19 pandemic caused by SARS-CoV-2 is challenging health care systems globally. The disease disproportionately affects the elderly population, both in terms of disease severity and mortality risk. OBJECTIVE: The aim of this study was to evaluate machine learning-based prognostication models for critically ill elderly COVID-19 patients, which dynamically incorporated multifaceted clinical information on evolution of the disease. METHODS: This multicenter cohort study (COVIP study) obtained patient data from 151 intensive care units (ICUs) from 26 countries. Different models based on the Sequential Organ Failure Assessment (SOFA) score, logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB) were derived as baseline models that included admission variables only. We subsequently included clinical events and time-to-event as additional variables to derive the final models using the same algorithms and compared their performance with that of the baseline group. Furthermore, we derived baseline and final models on a European patient cohort, which were externally validated on a non-European cohort that included Asian, African, and US patients. RESULTS: In total, 1432 elderly (≥70 years old) COVID-19-positive patients admitted to an ICU were included for analysis. Of these, 809 (56.49%) patients survived up to 30 days after admission. The average length of stay was 21.6 (SD 18.2) days. Final models that incorporated clinical events and time-to-event information provided superior performance (area under the receiver operating characteristic curve of 0.81; 95% CI 0.804-0.811), with respect to both the baseline models that used admission variables only and conventional ICU prediction models (SOFA score, P<.001). The average precision increased from 0.65 (95% CI 0.650-0.655) to 0.77 (95% CI 0.759-0.770). CONCLUSIONS: Integrating important clinical events and time-to-event information led to a superior accuracy of 30-day mortality prediction compared with models based on the admission information and conventional ICU prediction models. This study shows that machine-learning models provide additional information and may support complex decision-making in critically ill elderly COVID-19 patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT04321265; https://clinicaltrials.gov/ct2/show/NCT04321265