Structural Features of Hydrolyzable Tannins Determine Their Ability to Form Insoluble Complexes with Bovine Serum Albumin.

The ability of 32 purified and characterized hydrolyzable tannins to form insoluble complexes with model protein bovine serum albumin was investigated with a turbidimetric 96-well plate reader method. The results showed a clear relationship between the hydrolyzable tannin structure and the intensity of haze that formed during the tannin-protein complexation. In addition to molecular weight, structural features such as number of galloyl groups, degree of oxidative coupling between the galloyls, positional isomerism, and cyclic vs acyclic glucose core were the major structural features that affected the ability of the monomeric hydrolyzable tannins to form insoluble complexes with bovine serum albumin. While oligomers were superior to monomers in their capability to precipitate the model protein, their activity depended less on the functional groups, but mostly on their size and overall flexibility. These results allowed us to construct an equation that predicted the protein precipitation capacity of the studied hydrolyzable tannins with high accuracy.

Simple variables predict miserable outcome after intravenous thrombolysis.

BACKGROUND AND PURPOSE: To test the predictability of miserable outcome amongst ischaemic stroke patients receiving intravenous thrombolysis (IVT) based on a simple variables model (SVM) and to compare the model's predictive performance with that of an existing score which includes imaging and laboratory parameters (DRAGON). METHODS: The SVM consists of the parameters age, independence before stroke, normal Glasgow coma verbal score, able to lift arms and able to walk. In a derivation cohort (n = 1346) and a validation cohort (n = 638) of consecutive IVT-treated stroke patients, the probability estimated by SVM and the observed occurrence of miserable 3-month outcome (modified Rankin score 5-6) were compared. The performances of SVM and the DRAGON score were compared. The area under the receiver operating curve (AUC) (95% confidence interval, CI) and the bootstrapping approach were used to compare the predictive performance. RESULTS: The AUCs to predict miserable outcome in the derivation cohort were 0.807 (95% CI 0.774-0.838) using the SVM and 0.822 (0.790-0.850) using the DRAGON score (P = 0.3). For the validation cohort, AUCs were 0.786 (0.742-0.829) for the SVM and 0.809 (0.774-0.845) for the DRAGON score (P = 0.23). Only one patient with an SVM probability of >70% for miserable outcome in either cohort had a good outcome whilst 83% had a miserable outcome. An online SVM calculator to estimate the probability of miserable outcome for individual patients is available under http://www.unispital-basel.ch/SVM-Tool. CONCLUSION: The SVM was similar in accuracy to the DRAGON score for predicting miserable outcome after IVT. As these simple variables are available already at the pre-hospital stage, the SVM may facilitate and accelerate pre-hospital triage of patients at high risk for miserable outcome after IVT towards endovascular treatment.