Glycosidase inhibitory phenolic compounds from the seed of Psoralea corylifolia

The seeds of Psoralea corylifolia were extracted into five different polar solvents: chloroform, 50% ethanol in water, ethanol, methanol and water. All extracts were evaluated for glycosidase inhibitory activity. The chloroform extract (CE) showed the lowest IC₅₀ values against α-glucosidase (82.9 μg/ml) and α-mannosidase (132 μg/ml). Chromatography of CE yielded nine phenolic compounds which were identified as isovabachalcone (1), 4′-O-methylbavachalcone (2), isobavachromene (3), corylifolin (4), bavachinin (5), psoralidin (6), neobavaisoflavone (7), corylifol A (8), and bakuchiol (9). All isolated compounds, apart from compound 5, possessed α-glucosidase inhibitory activities. Among them, compounds 6–8 exhibited potent inhibition with IC₅₀s of 13.7, 27.7 and 11.3 μM, respectively. Furthermore, compounds 2 and 6 showed α-mannosidase inhibitory activity. Mechanistic analysis of their inhibition modes against α-glucosidase showed that compounds (6 and 7) were noncompetitive, whereas compound 8 was mixed. Furthermore, the most active glycosidase inhibitors (2, 6–8) were proven to be present in the native seed in high quantities by an HPLC chromatogram.     

Science's Response to CoVID-19

CoVID-19 is a multi-symptomatic disease which has made a global impact due to its ability to spread rapidly, and its relatively high mortality rate. Beyond the heroic efforts to develop vaccines, which we do not discuss herein, the response of scientists and clinicians to this complex problem has reflected the need to detect CoVID-19 rapidly, to diagnose patients likely to show adverse symptoms, and to treat severe and critical CoVID-19. Here we aim to encapsulate these varied and sometimes conflicting approaches and the resulting data in terms of chemistry and biology. In the process we highlight emerging concepts, and potential future applications that may arise out of this immense effort.     

Toward methods for supporting the anticipation-feedback loop in user interface design

Recent research has compared different usability evaluation methods with respect to their effectiveness and efficiency. The paper analyses the impact of different usability evaluation methods on design problem-solving processes of individual designers and evaluators. It is proposed that usability evaluation methods have to be divided into two categories according to their fundamentally different way of supporting the design for usability: (1) guideline-based methods and (2) methods based on the mental generation of scenarios and anticipation of user goals. We present data from an experimental study that shows that these two types of methods entail differences in the perspective-taking processes. Furthermore, the results indicate that the methods have a differential impact on the general problem-solving strategy, i.e. whether to use a top-down, breadth-first or a depth-first approach. Possible implications for the development of techniques that support the design of usable systems are discussed.     

Unconstrained model predictive control and suboptimality estimates for nonlinear continuous-time systems

This paper presents a continuous-time version of recent results on unconstrained nonlinear model predictive control (MPC) schemes. Based on a controllability assumption and a corresponding infinite-dimensional optimization problem, performance estimates and stability conditions are derived in terms of the prediction horizon and the sampling time of the MPC controller. Moreover, improved estimates for small sampling times are discussed and a comparison to the application of the discrete-time results in a sampled-data context is provided.