Aufgrund SARS-CoV-2 ist eine Rechtsvorlesung für Betriebswirte im Bachelorstudiengang an zwei verschiedenen Standorten der Hochschule Bonn-Rhein-Sieg mit über 300 Studierenden unter Anwendung des Inverted Classroom Ansatzes zum Sommersemester 2020 vollständig digitalisiert worden. Durch die von außen vorgegebene Lernstrategie mit wöchentlichen Arbeitspaketen und die Nutzung einer asynchronen Kommunikationsplattform auf Basis eines Instant Messengers mit adressatenadäquater Ansprache gelang es, Synchronformate auf ein notwendiges Minimum zu reduzieren. Die Ergebnisse der empirischen Begleitung zeigen, dass das neue didaktische Konzept für eine digitale Lehre die unterschiedlichsten Bedürfnisse der Studierenden befriedigte. Insbesondere konnte eine »digitale Lernatmosphäre« geschaffen werden, die von den Studierenden als sehr förderlich für ihren Lernprozess erachtet wurde. Die induzierte Lernstrategie führte zu signifikanten Leistungsverbesserungen. Es wird diskutiert, welche Maßnahmen sich auch für postpandemische Lehre empfehlen.
The COVID-19 pandemic has disrupted everyday living and social practices, prompting questions of whether more sustainable consumption patterns are emerging and the likelihood of their long-term retention. To examine these questions, we apply a practice-based approach to a quantitative study of COVID-driven practice changes in the domains of food, material consumption, housing, and mobility conducted in four global North countries (Germany, Italy, Japan, and the United States). We discuss the trends emerging from our analysis from a sustainability perspective and address the role of social practice elements – materials, meanings, competences – in the establishment and discontinuation of sustainable consumption practices. Observed sustainability gains in specific practices and domains (such as a decrease in material consumption and more sustainable food practices and diets), may be offset by other practices, particularly a renewed desire for air travel and larger housing. The uptake and lock-in of sustainable practices are driven by a combination of meaning and material-related practice elements such as the alignment with interests and personal values; the availability of labor, energy, or time; and the ability to routinize practices. However, new policies to support emerging lifestyle shifts, as well as the development of businesses catering to and encouraging low-impact practices, may ultimately determine the formation of a more sustainable “new normal.” We also reflect on the strengths and limitations of using quantitative research methods in studies of sustainable consumption informed by social practice theories.
AbstractBackgroundThe outbreak of coronavirus disease 2019 (COVID-19) has become a global pandemic acute infectious disease, especially with the features of possible asymptomatic carriers and high contagiousness. It causes acute respiratory distress syndrome and results in a high mortality rate if pneumonia is involved. Currently, it is difficult to quickly identify asymptomatic cases or COVID-19 patients with pneumonia due to limited access to reverse transcription-polymerase chain reaction (RT-PCR) nucleic acid tests and CT scans, which facilitates the spread of the disease at the community level, and contributes to the overwhelming of medical resources in intensive care units.GoalThis study aimed to develop a scientific and rigorous clinical diagnostic tool for the rapid prediction of COVID-19 cases based on a COVID-19 clinical case database in China, and to assist global frontline doctors to efficiently and precisely diagnose asymptomatic COVID-19 patients and cases who had a false-negative RT-PCR test result.MethodsWith online consent, and the approval of the ethics committee of Zhongshan Hospital Fudan Unversity (approval number B2020-032R) to ensure that patient privacy is protected, clinical information has been uploaded in real-time through the New Coronavirus Intelligent Auto-diagnostic Assistant Application of cloud plus terminal (nCapp) by doctors from different cities (Wuhan, Shanghai, Harbin, Dalian, Wuxi, Qingdao, Rizhao, and Bengbu) during the COVID-19 outbreak in China. By quality control and data anonymization on the platform, a total of 3,249 cases from COVID-19 high-risk groups were collected. These patients had SARS-CoV-2 RT-PCR test results and chest CT scans, both of which were used as the gold standard for the diagnosis of COVID-19 and COVID-19 pneumonia. In particular, the dataset included 137 indeterminate cases who initially did not have RT-PCR tests and subsequently had positive RT-PCR results, 62 suspected cases who initially had false-negative RT-PCR test results and subsequently had positive RT-PCR results, and 122 asymptomatic cases who had positive RT-PCR test results, amongst whom 31 cases were diagnosed. We also integrated the function of a survey in nCapp to collect user feedback from frontline doctors.FindingsWe applied the statistical method of a multi-factor regression model to the training dataset (1,624 cases) and developed a prediction model for COVID-19 with 9 clinical indicators that are fast and accessible: ‘Residing or visiting history in epidemic regions’, ‘Exposure history to COVID-19 patient’, ‘Dry cough’, ‘Fatigue’, ‘Breathlessness’, ‘No body temperature decrease after antibiotic treatment’, ‘Fingertip blood oxygen saturation ≤93%’, ‘Lymphopenia’, and ‘C-reactive protein (CRP) increased’. The area under the receiver operating characteristic (ROC) curve (AUC) for the model was 0.88 (95% CI: 0.86, 0.89) in the training dataset and 0.84 (95% CI: 0.82, 0.86) in the validation dataset (1,625 cases). To ensure the sensitivity of the model, we used a cutoff value of 0.09. The sensitivity and specificity of the model were 98.0% (95% CI: 96.9%, 99.1%) and 17.3% (95% CI: 15.0%, 19.6%), respectively, in the training dataset, and 96.5% (95% CI: 95.1%, 98.0%) and 18.8% (95% CI: 16.4%, 21.2%), respectively, in the validation dataset. In the subset of the 137 indeterminate cases who initially did not have RT-PCR tests and subsequently had positive RT-PCR results, the model predicted 132 cases, accounting for 96.4% (95% CI: 91.7%, 98.8%) of the cases. In the subset of the 62 suspected cases who initially had false-negative RT-PCR test results and subsequently had positive RT-PCR results, the model predicted 59 cases, accounting for 95.2% (95% CI: 86.5%, 99.0%) of the cases. Considering the specificity of the model, we used a cutoff value of 0.32. The sensitivity and specificity of the model were 83.5% (95% CI: 80.5%, 86.4%) and 83.2% (95% CI: 80.9%, 85.5%), respectively, in the training dataset, and 79.6% (95% CI: 76.4%, 82.8%) and 81.3% (95% CI: 78.9%, 83.7%), respectively, in the validation dataset, which is very close to the published AI model.The results of the online survey ‘Questionnaire Star’ showed that 90.9% of nCapp users in WeChat mini programs were ‘satisfied’ or ‘very satisfied’ with the tool. The WeChat mini program received a significantly higher satisfaction rate than other platforms, especially for ‘availability and sharing convenience of the App’ and ‘fast speed of log-in and data entry’.DiscussionWith the assistance of nCapp, a mobile-based diagnostic tool developed from a large database that we collected from COVID-19 high-risk groups in China, frontline doctors can rapidly identify asymptomatic patients and avoid misdiagnoses of cases with false-negative RT-PCR results. These patients require timely isolation or close medical supervision. By applying the model, medical resources can be allocated more reasonably, and missed diagnoses can be reduced. In addition, further education and interaction among medical professionals can improve the diagnostic efficiency for COVID-19, thus avoiding the transmission of the disease from asymptomatic patients at the community level.
Coronavirus disease 2019 (COVID-19) caused by the emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has set off a global pandemic. There is an urgent unmet need for safe, affordable, and effective therapeutics against COVID-19. In this regard, drug repurposing is considered as a promising approach. We assessed the compounds that affect the endosomal acidic environment by applying human angiotensin-converting enzyme 2 (hACE2)- expressing cells infected with a SARS-CoV-2 spike (S) protein-pseudotyped HIV reporter virus and identified that obatoclax resulted in the strongest inhibition of S protein-mediated virus entry. The potent antiviral activity of obatoclax at nanomolar concentrations was confirmed in different human lung and intestinal cells infected with the SARS-CoV-2 pseudotype system as well as clinical virus isolates. Furthermore, we uncovered that obatoclax executes a double-strike against SARS-CoV-2. It prevented SARS-CoV-2 entry by blocking endocytosis of virions through diminished endosomal acidification and the corresponding inhibition of the enzymatic activity of the endosomal cysteine protease cathepsin L. Additionally, obatoclax impaired the SARS-CoV-2 S-mediated membrane fusion by targeting the MCL-1 protein and reducing furin protease activity. In accordance with these overarching mechanisms, obatoclax blocked the virus entry mediated by different S proteins derived from several SARS-CoV-2 variants of concern such as, Alpha (B.1.1.7), Beta (B.1.351), and Delta (B.1.617.2). Taken together, our results identified obatoclax as a novel effective antiviral compound that keeps SARS-CoV-2 at bay by blocking both endocytosis and membrane fusion. Our data suggested that obatoclax should be further explored as a clinical drug for the treatment of COVID-19. CA Huang und CA Trilling
Marine pollution with personal protective equipment (PPE) has recently gained major attention. Multiple studies reported the release of microplastics (MPs) and chemical contaminants from face masks, the most used PPE type. However, not much is known concerning the release of phthalate esters (PAEs) in aquatic media, as well as the hazard posed by other types of PPE. In the present study, we investigated the release of MPs and PAEs from face masks and gloves recovered from the environment. The results indicated that both PPEs release MPs comparable to the literature, but higher concentrations were presented by face masks. In turn, the total concentration of six PAEs was higher in gloves than in face masks. The release of these contaminants is exacerbated over time. The present study allows researchers to understand the contribution of PPE to marine pollution while accounting for gloves, a generally overlooked source of contaminants.
The sudden and dramatic advent of the COVID-19 pandemic led to urgent demands for timely, relevant, yet rigorous research. This paper discusses the origin, design, and execution of the SolPan research commons, a large-scale, international, comparative, qualitative research project that sought to respond to the need for knowledge among researchers and policymakers in times of crisis. The form of organization as a research commons is characterized by an underlying solidaristic attitude of its members and its intrinsic organizational features in which research data and knowledge in the study is shared and jointly owned. As such, the project is peer-governed, rooted in (idealist) social values of academia, and aims at providing tools and benefits for its members. In this paper, we discuss challenges and solutions for qualitative studies that seek to operate as research commons. ispartof: SSM - Qualitative Research in Health vol:2 ispartof: location:England status: published
The COVID-19 pandemic has had a major impact on everyday travel and, by extension, everyday commuting. During the pandemic, some people were able to work from home while others continued commuting. This study examines how commuting behavior changed between 2019 and 2020. In this study, we analyze panel data of the German Mobility Panel, a national household travel survey. We paint a broad picture of the characteristics and behavior of those who commuted during the pandemic. The analyses focus on the intra- and interpersonal differences and are presented in a mostly descriptive way. The results show that people with low income and a low level of education are primarily those who cannot work from home and do not have flexible working hours. The results further show that especially public transport has lost importance in daily commuting. However, those who commuted in 2019 and 2020 did not significantly change their commuting behavior regarding commuting time and commuting mode.
Mobility behavior changes due to the COVID-19 pandemic have opened a window of opportunity for an accelerated transition towards sustainable mobility. Many European cities installed temporary cycling infrastructure which can be considered a niche innovation in the Multi-Level-Perspective of transitions (Geels, 2002). We empirically assess the effects of such temporary infrastructure in terms of air quality, behaviour, and acceptance, with a focus on the city of Berlin, Germany. The numerous pop-up bike lanes installed serve as an inter- and transdisciplinary case study to systematically capture these effects. We conducted a survey among Berlin citizens (n= 1,661), analysed cycling usage data, and measured the exposure of cyclists to air quality before and after the implementation of one pop-up bike lane during the first wave of COVID-19. Results show that pop-up bike lanes receive high levels of acceptance, increase cycling usage on the respective street, and reduce cyclists’ exposure to nitrogen dioxide. Their implementation fosters an innovative mind-set of transport planning: to temporarily try out new street designs, learn from these practical experiences, improve the designs, and then permanently implement the ones best proven in practice. We conclude that PUBL can accelerate the regime shift from car-oriented to bicycle-friendly cities because of its many demonstrated positive impacts.