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Objetivo: reflexionar sobre la manera en la que los docentes de la carrera de grado de Enfermería experimentan las actividades de su proceso de trabajo en el contexto de la pandemia de COVID-19. Método: estudio cualitativo y reflexivo, del tipo investigación acción-participante, fundamentado en los supuestos de Paulo Freire. Se contó con la participación de 20 docentes de la carrera de grado de Enfermería de universidades públicas y privadas del sur de Brasil. Se recorrió el Itinerario de Investigación de Paulo Freire pasando por la Investigación Temática, la Codificación, la Decodificación y el Desvelamiento Crítico, en un Círculo de Cultura Virtual realizado en agosto de 2020. Resultados: los docentes de Enfermería dialogaron sobre las repercusiones de la enseñanza no presencial sobre su propia salud. Reflexionaron acerca de sus sentimientos al enfrentar esta modalidad de enseñanza y cómo la desarrollan en el contexto de la pandemia. Conclusión: los resultados contribuyen a la práctica basada en evidencias de los enfermeros, fortaleciendo así el proceso de toma de decisiones en relación al proceso de trabajo docente en el contexto de la pandemia de COVID-19. Objetivo: refletir sobre como os docentes de graduação em Enfermagem vivenciam as atividades do seu processo de trabalho no contexto da pandemia de COVID-19. Método: estudo qualitativo, reflexivo, do tipo pesquisa ação- participante, fundamentado nos pressupostos de Paulo Freire. Contou-se com a participação de 20 docentes de graduação em Enfermagem de universidades públicas e privadas do Sul do Brasil. O Itinerário de Pesquisa Freireano foi percorrido perpassando pela Investigação Temática, Codificação, Descodificação e Desvelamento Crítico, em um Círculo de Cultura Virtual realizado em agosto de 2020. Resultados: os docentes de Enfermagem dialogaram sobre as repercussões do ensino não presencial na sua saúde. Refletiram acerca dos seus sentimentos no enfrentamento dessa modalidade de ensino e como o desenvolvem no contexto pandêmico. Conclusão: os resultados contribuem para a prática baseada em evidências de enfermeiros, fortalecendo a tomada de decisões quanto ao processo de trabalho docente no contexto da pandemia de COVID-19.  Objective: to reflect on how undergraduate Nursing teachers experience the activities of their work process in the COVID-19 pandemic context. Method: a qualitative and reflection study of the action-participant research type, grounded on Paulo Freire’s assumptions. The participants were 20 undergraduate Nursing teachers from public and private universities in southern Brazil. Paulo Freire’s Research Itinerary was carried out through Thematic Research, Coding, Decoding, and Critical Unveiling, in a Virtual Culture Circle held in August 2020. Results: the Nursing teachers discussed about the repercussions of remote teaching on their health. They reflected on their feelings in facing this teaching modality and on how they develop in the pandemic context. Conclusion: the results contribute to the nurses’ evidence-based practice, strengthening decision-making regarding the teachers’ work process in the COVID-19 pandemic context.

From March 2020, the Covid-19 pandemic revealed the inherent vulnerability of our modern society to emerging infectious diseases. Globalisation of products and high travel frequency contributed to the rapid spread of infection, and particularly in densely populated urban areas.

This thesis presents new methods for the analysis of high-throughput data from modern sources in the context of complex human diseases, at the example of a bioinformatics analysis workflow. New measurement techniques improve the resolution with which cellular and molecular processes can be monitored. While RNA sequencing (RNA-seq) measures mRNA expression, single-cell RNA-seq (scRNA-seq) resolves this on a per-cell basis. Long-read sequencing is increasingly used in genomics. With imaging mass spectrometry (IMS) the protein level in tissues is measured spatially resolved. All these techniques induce specific challenges, which need to be addressed with new computational methods. Collecting knowledge with contextual annotations is important for integrative data analyses. Such knowledge is available through large literature repositories, from which information, such as miRNA-gene interactions, can be extracted using text mining methods. After aggregating this information in new databases, specific questions can be answered with traceable evidence. The combination of experimental data with these databases offers new possibilities for data integrative methods and for answering questions relevant for complex human diseases. Several data sources are made available, such as literature for text mining miRNA-gene interactions (Chapter 2), next- and third-generation sequencing data for genomics and transcriptomics (Chapters 4.1, 5), and IMS for spatially resolved proteomics (Chapter 4.4). For these data sources new methods for information extraction and pre-processing are developed. For instance, third-generation sequencing runs can be monitored and evaluated using the poreSTAT and sequ-into methods. The integrative (down-stream) analyses make use of these (heterogeneous) data sources. The cPred method (Chapter 4.2) for cell type prediction from scRNA-seq data was successfully applied in the context of the SARS-CoV-2 pandemic. The robust differential expression (DE) analysis pipeline RoDE (Chapter 6.1) contains a large set of methods for (differential) data analysis, reporting and visualization of RNA-seq data. Topics of accessibility of bioinformatics software are discussed along practical applications (Chapter 3). The developed miRNA-gene interaction database gives valuable insights into atherosclerosis-relevant processes and serves as regulatory network for the prediction of active miRNA regulators in RoDE (Chapter 6.1). The cPred predictions, RoDE results, scRNA-seq and IMS data are unified as input for the 3D-index Aorta3D (Chapter 6.2), which makes atherosclerosis related datasets browsable. Finally, the scRNA-seq analysis with subsequent cPred cell type prediction, and the robust analysis of bulk-RNA-seq datasets, led to novel insights into COVID-19. Taken all discussed methods together, the integrative analysis methods for complex human disease contexts have been improved at essential positions. Die Dissertation beschreibt Methoden zur Prozessierung von aktuellen Hochdurchsatzdaten, sowie Verfahren zu deren weiterer integrativen Analyse. Diese findet Anwendung vor allem im Kontext von komplexen menschlichen Krankheiten. Neue Messtechniken erlauben eine detailliertere Beobachtung biomedizinischer Prozesse. Mit RNA-Sequenzierung (RNA-seq) wird mRNA-Expression gemessen, mit Hilfe von moderner single-cell-RNA-seq (scRNA-seq) sogar für (sehr viele) einzelne Zellen. Long-Read-Sequenzierung wird zunehmend zur Sequenzierung ganzer Genome eingesetzt. Mittels bildgebender Massenspektrometrie (IMS) können Proteine in Geweben räumlich aufgelöst quantifiziert werden. Diese Techniken bringen spezifische Herausforderungen mit sich, die mit neuen bioinformatischen Methoden angegangen werden müssen. Für die integrative Datenanalyse ist auch die Gewinnung von geeignetem Kontextwissen wichtig. Wissenschaftliche Erkenntnisse werden in Artikeln veröffentlicht, die über große Literaturdatenbanken zugänglich sind. Mittels Textmining können daraus Informationen extrahiert werden, z.B. miRNA-Gen-Interaktionen, die in eigenen Datenbank aggregiert werden um spezifische Fragen mit nachvollziehbaren Belegen zu beantworten. In Kombination mit experimentellen Daten bieten sich so neue Möglichkeiten für integrative Methoden. Durch die Extraktion von Rohdaten und deren Vorprozessierung werden mehrere Datenquellen erschlossen, wie z.B. Literatur für Textmining von miRNA-Gen-Interaktionen (Kapitel 2), Long-Read- und RNA-seq-Daten für Genomics und Transcriptomics (Kapitel 4.2, 5) und IMS für Protein-Messungen (Kapitel 4.4). So dienen z.B. die poreSTAT und sequ-into Methoden der Vorprozessierung und Auswertung von Long-Read-Sequenzierungen. In der integrativen (down-stream) Analyse werden diese (heterogenen) Datenquellen verwendet. Für die Bestimmung von Zelltypen in scRNA-seq-Experimenten wurde die cPred-Methode (Kapitel 4.2) erfolgreich im Kontext der SARS-CoV-2-Pandemie eingesetzt. Auch die robuste Pipeline RoDE fand dort Anwendung, die viele Methoden zur (differentiellen) Datenanalyse, zum Reporting und zur Visualisierung bereitstellt (Kapitel 6.1). Themen der Benutzbarkeit von (bioinformatischer) Software werden an Hand von praktischen Anwendungen diskutiert (Kapitel 3). Die entwickelte miRNA-Gen-Interaktionsdatenbank gibt wertvolle Einblicke in Atherosklerose-relevante Prozesse und dient als regulatorisches Netzwerk für die Vorhersage von aktiven miRNA-Regulatoren in RoDE (Kapitel 6.1). Die cPred-Methode, RoDE-Ergebnisse, scRNA-seq- und IMS-Daten werden im 3D-Index Aorta3D (Kapitel 6.2) zusammengeführt, der relevante Datensätze durchsuchbar macht. Die diskutierten Methoden führen zu erheblichen Verbesserungen für die integrative Datenanalyse in komplexen menschlichen Krankheitskontexten.

This document is about the druggability and genetic variability of the ADP-bound pocket of SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) NiRAN domain across coronaviruses and SARS-CoV-2 samples. This report also accompanies this post on https://openlabnotebooks.org/.

This paper analyzes the moderation effect of government responses on the impact of the COVID-19 pandemic, proxied by the daily growth in COVID-19 cases and deaths, on the capital market, i.e., the S&P 500 firm’s daily returns. Using the Oxford COVID-19 Government Response Tracker, we monitor 16 daily indicators for government actions across the fields of containment and closure, economic support, and health for 180 countries in the period from January 1, 2020 to March 15, 2021. We find that government responses mitigate the negative stock market impact and that investors’ sentiment is sensitive to a firm’s country-specific revenue exposure to COVID-19. Our findings indicate that the mitigation effect is stronger for firms that are highly exposed to COVID-19 on the sales side. In more detail, containment and closure policies and economic support mitigate negative stock market impacts, while health system policies support further declines. For firms with high revenue exposure to COVID-19, the mitigation effect is stronger for government economic support and health system initiatives. Containment and closure policies do not mitigate stock price declines due to growing COVID-19 case numbers. Our results hold even after estimating the spread of the pandemic with an epidemiological standard model, namely, the susceptible-infectious-recovered model.

Summary Background COVID-19 pandemic has developed rapidly and the ability to stratify the most vulnerable patients is vital. However, routinely used severity scoring systems are often low on diagnosis, even in non-survivors. Therefore, clinical prediction models for mortality are urgently required. Methods We developed and internally validated a multivariable logistic regression model to predict inpatient mortality in COVID-19 positive patients using data collected retrospectively from Tongji Hospital, Wuhan (299 patients). External validation was conducted using a retrospective cohort from Jinyintan Hospital, Wuhan (145 patients). Nine variables commonly measured in these acute settings were considered for model development, including age, biomarkers and comorbidities. Backwards stepwise selection and bootstrap resampling were used for model development and internal validation. We assessed discrimination via the C statistic, and calibration using calibration-in-the-large, calibration slopes and plots. Findings The final model included age, lymphocyte count, lactate dehydrogenase and SpO 2 as independent predictors of mortality. Discrimination of the model was excellent in both internal (c=0·89) and external (c=0·98) validation. Internal calibration was excellent (calibration slope=1). External validation showed some over-prediction of risk in low-risk individuals and under-prediction of risk in high-risk individuals prior to recalibration. Recalibration of the intercept and slope led to excellent performance of the model in independent data. Interpretation COVID-19 is a new disease and behaves differently from common critical illnesses. This study provides a new prediction model to identify patients with lethal COVID-19. Its practical reliance on commonly available parameters should improve usage of limited healthcare resources and patient survival rate. Funding This study was supported by following funding: Key Research and Development Plan of Jiangsu Province (BE2018743 and BE2019749), National Institute for Health Research (NIHR) (PDF-2018-11-ST2-006), British Heart Foundation (BHF) (PG/16/65/32313) and Liverpool University Hospitals NHS Foundation Trust in UK. Research in context Evidence before this study Since the outbreak of COVID-19, there has been a pressing need for development of a prognostic tool that is easy for clinicians to use. Recently, a Lancet publication showed that in a cohort of 191 patients with COVID-19, age, SOFA score and D-dimer measurements were associated with mortality. No other publication involving prognostic factors or models has been identified to date. Added value of this study In our cohorts of 444 patients from two hospitals, SOFA scores were low in the majority of patients on admission. The relevance of D-dimer could not be verified, as it is not included in routine laboratory tests. In this study, we have established a multivariable clinical prediction model using a development cohort of 299 patients from one hospital. After backwards selection, four variables, including age, lymphocyte count, lactate dehydrogenase and SpO 2 remained in the model to predict mortality. This has been validated internally and externally with a cohort of 145 patients from a different hospital. Discrimination of the model was excellent in both internal (c=0·89) and external (c=0·98) validation. Calibration plots showed excellent agreement between predicted and observed probabilities of mortality after recalibration of the model to account for underlying differences in the risk profile of the datasets. This demonstrated that the model is able to make reliable predictions in patients from different hospitals. In addition, these variables agree with pathological mechanisms and the model is easy to use in all types of clinical settings. Implication of all the available evidence After further external validation in different countries the model will enable better risk stratification and more targeted management of patients with COVID-19. With the nomogram, this model that is based on readily available parameters can help clinicians to stratify COVID-19 patients on diagnosis to use limited healthcare resources effectively and improve patient outcome.

Brochure with easy-to-understand information for migrants about the Corona vaccination in English language. Redaktionsschluss: 15.02.2022

Mobile devices are present in people s lives. With the spread of smartphones, conflicts and annoyances arise due to interruptions and intrusions of devices during social interactions, a phenomenon called technoference by McDaniel and Coyne (2016). This research sought to investigate the influence of the use of smartphones on the relationship between parents and children and, thus, to understand how the presence of technology interferes in the family context. Thirty caregivers of 8 and 9 year old children from the states of Rio de Janeiro, Minas Gerais, Curitiba and Goiás, from different economic backgrounds participated in the study. Semi-structured interviews were conducted with participants via video calling using WhatsApp during the Covid-19 pandemic period. The data were analyzed using the ATLAS.ti software, within a qualitative and quantitative approach. Among the main results, different impacts stand out, such as the use of parents; smartphone during interactions with their children. Associations were noticed between technoference - cell phone invasions during interactions between parents and their children - and conflicts in family life. The interviews point to parents; worrying about their own use of the technology, and about the use of other family members, generating dissatisfaction. On the other hand, parents also highlighted the shared use of touch screen technology as an ally resource in interactions with their children. The present research provides indications about the need for future discussions regarding the benefits and harms of the use of smartphones by parents and children in the family environment. Os dispositivos móveis estão amplamente presentes no cotidiano das pessoas. Com a difusão dos smartphones, surgem conflitos e incômodos por conta das interrupções e intrusões dos aparelhos durante interações sociais, fenômeno denominado como tecnoferência por McDaniel e Coyne (2016). Esta pesquisa buscou investigar a influência do uso de smartphones na relação entre pais e filhos e entender deque forma a presença da tecnologia interfere no contexto familiar. Participaram do estudo 30 responsáveis de crianças de 8 e 9 anos de idade provindos dos estados do Rio de Janeiro, Minas Gerais, Curitiba e Goiás, de diferentes faixas econômicas. Foram realizadas entrevistas semiestruturadas com os participantes por vídeo chamada via WhatsApp durante o período da pandemia de Covid-19. Os dados foram analisados com o software ATLAS.ti, sendo adotada a abordagem quali-quantitativa. Dentre os principais resultados, destacam-se diferentes impactos da utilização do smartphone pelos pais nas interações com seus filhos. Foram percebidas associações entre tecnoferência – invasões do celular durante interações de pais com seus filhos – e conflitos no convívio familiar. As entrevistas apontam para incômodos dos responsáveis sobre seu próprio uso e sobre o uso dos outros membros da família gerando insatisfação e descontentamento. Em contraste, os responsáveis destacaram a utilização compartilhada da tecnologia touch screen como recurso aliado nas interações com os filhos. O presente trabalho traz indicações sobre a necessidade de discussões futuras dos benefícios e malefícios do uso de smartphones por pais e crianças no ambiente familiar. CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO PROGRAMA DE EXCELENCIA ACADEMICA

The COVID-19 pandemic affected regular health care for patients with chronic diseases. However, the impact of the pandemic on primary care for patients with coronary artery disease (CAD) who are enrolled in a structured disease management program (DMP) in Germany is not clear. We investigated whether the pandemic affected primary care and health outcomes of DMP-CAD patients (n = 750) by using a questionnaire assessing patients’ utilization of medical care, CAD symptoms, as well as health behavior and mental health since March 2020. We found that out of concern about getting infected with COVID-19, 9.1% of the patients did not consult a medical practitioner despite having CAD symptoms. Perceived own influence on infection risk was lower and anxiety was higher in these patients compared to symptomatic CAD patients who consulted a physician. Among the patients who reported chest pain lasting longer than 30 min, one third did not consult a medical practitioner subsequently. These patients were generally more worried about COVID-19. Patients with at least one worsening CAD symptom (chest pain, dyspnea, perspiration, or nausea without apparent reason) since the pandemic showed more depressive symptoms, higher anxiety scores, and were less likely to consult a doctor despite having CAD symptoms out of fear of infection. Our results provide evidence that the majority of patients received sufficient medical care during the COVID-19 pandemic in Germany. However, one in ten patients could be considered particularly at risk for medical undersupply and adverse health outcomes. The perceived infection risk with COVID-19 might have facilitated the decision not to consult a medical doctor.

The papain-like protease (PLpro) of SARS-CoV-2 is essential for viral propagation and, additionally, dysregulation of the host innate immune system. Using a library of 40 potential metal-chelating compounds we performed an X-ray crystallographic screening against PLpro. As outcome we identified six compounds binding to the target protein. Here we describe the interaction of one hydrazone (H1) and five thiosemicarbazone (T1-T5) compounds with the two distinct natural substrate binding sites of PLpro for ubiquitin and ISG15. H1 binds to a polar groove at the S1 binding site by forming several hydrogen bonds with PLpro. T1-T5 bind into a deep pocket close to the polyubiquitin and ISG15 binding site S2. Their interactions are mainly mediated by multiple hydrogen bonds and further hydrophobic interactions. In particular compound H1 interferes with natural substrate binding by sterical hindrance and induces conformational changes in protein residues involved in substrate binding, while compounds T1-T5 could have a more indirect effect. Fluorescence based enzyme activity assay and complementary thermal stability analysis reveal only weak inhibition properties in the high micromolar range thereby indicating the need for compound optimization. Nevertheless, the unique binding properties involving strong hydrogen bonding and the various options for structural optimization make the compounds ideal lead structures. In combination with the inexpensive and undemanding synthesis, the reported hydrazone and thiosemicarbazones represent an attractive scaffold for further structure-based development of novel PLpro inhibitors by interrupting protein-protein interactions at the S1 and S2 site.