A convenient method for the relative and absolute quantification of lipid components in liposomes by 1H- and 31P NMR-spectroscopy.

OBJECTIVE: Liposomes are promising delivery systems for pharmaceutical applications and have been used in medicine in the recent past. Preparation of liposomes requires reliable characterization and quantification of the phospholipid components for which the traditional cumbersome molybdate method is used frequently. The objective was to improve relative and absolute quantification of lipid components from liposomes. METHODS: A reliable method for quantification of lipid composition in liposome formulations in the 1-10 µmol range with 1H- and 31P NMR spectroscopy at 600 MHz has been developed. The method is based on three crystalline small-molecule standards (Ph3PO4, (Tol)3PO4, and Ph3PO) in CDCl3. RESULTS: Excellent calibration linearity and chemical stability of the standards was observed. The method was tested in blind fashion on liposomes containing POPC, PEG-ceramide and a pH-sensitive trans-aminocyclohexanol-based amphiphile (TACH).1 Relative quantification (percentage of components) as well as determination of absolute lipid amount was possible with excellent reproducibility with an average error of 5%. Quantification (triplicate) was accomplished in 15 min based on 1H NMR and in 1 h based on 31P NMR. Very little change in mixture composition was observed over multiple preparative steps. CONCLUSION: Liposome preparations containing POPC, POPE, DOPC, DPPC, TACH, and PEG-ceramide can be reliably characterized and quantified by 1H NMR and 31P NMR spectroscopy at 600 MHz in the µmol range.

The C-terminal Region of D-DT Regulates Molecular Recognition for Protein-Ligand Complexes.

Systematic analysis of molecular recognition is critical for understanding the biological function of macromolecules. For the immunomodulatory protein D-dopachrome tautomerase (D-DT), the mechanism of protein-ligand interactions is poorly understood. Here, 17 carefully designed protein variants and wild type (WT) D-DT were interrogated with an array of complementary techniques to elucidate the structural basis of ligand recognition. Utilization of a substrate and two selective inhibitors with distinct binding profiles offered previously unseen mechanistic insights into D-DT-ligand interactions. Our results demonstrate that the C-terminal region serves a key role in molecular recognition via regulation of the active site opening, protein-ligand interactions, and conformational flexibility of the pocket's environment. While our study is the first comprehensive analysis of molecular recognition for D-DT, the findings reported herein promote the understanding of protein functionality and enable the design of new structure-based drug discovery projects.

The development of tissue handling skills is sufficient and comparable after training in virtual reality or on a surgical robotic system: a prospective randomized trial.

BACKGROUND: Virtual reality is a frequently chosen method for learning the basics of robotic surgery. However, it is unclear whether tissue handling is adequately trained in VR training compared to training on a real robotic system. METHODS: In this randomized controlled trial, participants were split into two groups for "Fundamentals of Robotic Surgery (FRS)" training on either a DaVinci VR simulator (VR group) or a DaVinci robotic system (Robot group). All participants completed four tasks on the DaVinci robotic system before training (Baseline test), after proficiency in three FRS tasks (Midterm test), and after proficiency in all FRS tasks (Final test). Primary endpoints were forces applied across tests. RESULTS: This trial included 87 robotic novices, of which 43 and 44 participants received FRS training in VR group and Robot group, respectively. The Baseline test showed no significant differences in force application between the groups indicating a sufficient randomization. In the Midterm and Final test, the force application was not different between groups. Both groups displayed sufficient learning curves with significant improvement of force application. However, the Robot group needed significantly less repetitions in the three FRS tasks Ring tower (Robot: 2.48 vs. VR: 5.45; p < 0.001), Knot Tying (Robot: 5.34 vs. VR: 8.13; p = 0.006), and Vessel Energy Dissection (Robot: 2 vs. VR: 2.38; p = 0.001) until reaching proficiency. CONCLUSION: Robotic tissue handling skills improve significantly and comparably after both VR training and training on a real robotic system, but training on a VR simulator might be less efficient.