Just-in-Time Teaching in der Software-Engineering-Ausbildung an Hochschulen

In software engineering (SE), high demands on professional knowledge, rapid technical changes and the preoccupation with ever-new order domains characterize professional practice. The ability to self-directed learning is considered helpful in meeting these challenges during your studies and in the later work. This article exemplifies Just-in-Time Teaching (JiTT) as a teaching-learning method designed to support self-directed learning processes. The didactic examination of JiTT is about an analysis of (already existing) learning strategies of students in the handling of this teaching-learning method and the possibilities of self-control within the framework of JiTT.Im Software Engineering (SE) prägen hohe Anforderungen an das fachliche Wissen, schnelle technische Veränderungen und die Beschäftigung mit immer neuen Auftragsdomänen die Berufspraxis. Zur Bewältigung dieser Herausforderungen während des Studiums und im späteren Arbeitsalltag wird die Fähigkeit zum selbstgesteuerten Lernen als hilfreich erachtet. Dieser Beitrag stellt beispielhaft Just-in-Time Teaching (JiTT) als Lehr-Lernmethode dar, die selbstgesteuerte Lernprozesse unterstützen soll. Bei der didaktischen Auseinandersetzung mit JiTT geht es um eine Untersuchung von (bereits vorhandenen) Lernstrategien von Studierenden im Umgang mit dieser Lehr-Lernmethode und einer Analyse der Möglichkeiten von Selbststeuerung im Rahmen von JiTT

Massive X-ray screening reveals two allosteric drug binding sites of SARS-CoV-2 main protease

The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous health problems and economical challenges for mankind. To date, no effective drug is available to directly treat the disease and prevent virus spreading. In a search for a drug against COVID-19, we have performed a massive X-ray crystallographic screen of repurposing drug libraries containing 5953 individual compounds against the SARS-CoV-2 main protease (Mpro), which is a potent drug target as it is essential for the virus replication. In contrast to commonly applied X-ray fragment screening experiments with molecules of low complexity, our screen tested already approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds binding to Mpro. In subsequent cell-based viral reduction assays, one peptidomimetic and five non-peptidic compounds showed antiviral activity at non-toxic concentrations. Interestingly, two compounds bind outside the active site to the native dimer interface in close proximity to the S1 binding pocket. Another compound binds in a cleft between the catalytic and dimerization domain of Mpro. Neither binding site is related to the enzymatic active site and both represent attractive targets for drug development against SARS-CoV-2. This X-ray screening approach thus has the potential to help deliver an approved drug on an accelerated time-scale for this and future pandemics

X-ray screening identifies active site and allosteric inhibitors of SARS-CoV-2 main protease

The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous human suffering. To date, no effective drug is available to directly treat the disease. In a search for a drug against COVID-19, we have performed a high-throughput X-ray crystallographic screen of two repurposing drug libraries against the SARS-CoV-2 main protease (M^(pro)), which is essential for viral replication. In contrast to commonly applied X-ray fragment screening experiments with molecules of low complexity, our screen tested already approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds that bind to M^(pro). In subsequent cell-based viral reduction assays, one peptidomimetic and six non-peptidic compounds showed antiviral activity at non-toxic concentrations. We identified two allosteric binding sites representing attractive targets for drug development against SARS-CoV-2

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements