Waste paper derived three-dimensional carbon aerogel integrated with ceria/nitrogen-doped reduced graphene oxide as freestanding anode for high performance and durable microbial fuel cells

Bioprocess and Biosystems Engineering - Despite the green energy generation with low cost compared to conventional fuel cells, microbial fuel cells (MFCs) still suffer with anode related...     

Identification of a small molecule that modulates platelet glycoprotein Ib-von Willebrand factor interaction

The von Willebrand factor (VWF) A1-glycoprotein (GP) Ibα interaction is of major importance during thrombosis mainly at sites of high shear stress. Inhibitors of this interaction prevent platelet-dependent thrombus formation in vivo, without major bleeding complications. However, the size and/or protein nature of the inhibitors currently in development limit oral bioavailability and clinical development. We therefore aimed to search for a small molecule protein-protein interaction inhibitor interfering with the VWF-GPIbα binding. After determination of putative small molecule binding pockets on the surface of VWF-A1 and GPIbα using site-finding algorithms and molecular dynamics, high throughput molecular docking was performed on both binding partners. A selection of compounds showing good in silico docking scores into the predicted pockets was retained for testing their in vitro effect on VWF-GPIbα complex formation, by which we identified a compound that surprisingly stimulated the VWF-GPIbα binding in a ristocetin cofactor ELISA and increased platelet adhesion in whole blood to collagen under arterial shear rate but in contrast inhibited ristocetin-induced platelet aggregation. The selected compound adhering to the predicted binding partner GPIbα could be confirmed by saturation transfer difference NMR spectroscopy. We thus clearly identified a small molecule that modulates VWF-GPIbα binding and that will now serve as a starting point for further studies and chemical modifications to fully characterize the interaction and to manipulate specific activity of the compound.     

Estimation of distribution function in bivariate competing risk models

We consider lifetime data involving pairs of study individuals with more than one possible cause of failure for each individual. Non-parametric estimation of cause-specific distribution functions is considered under independent censoring. Properties of the estimators are discussed and an illustration of their application is given.