Characterization of nanomedicines’ surface coverage using molecular probes and capillary electrophoresis

International audienceA faithful characterization of nanomedicine (NM) is needed for a better understanding of their in vivo outcomes. Size and surface charge are studied with well-established methods. However, other relevant parameters for the understanding of NM behavior in vivo remain largely inaccessible. For instance, the reactive surface of nanomedicines, which are often grafted with macromolecules to decrease their recognition by the immune system, is excluded from a systematic characterization. Yet, it is known that a subtle modification of NMs' surface characteristics (grafting density, molecular architecture and conformation of macromolecules) is at the root of major changes in the presence of biological components. In this work, a method that investigates the steric hindrance properties of the NMs’ surface coverage based on its capacity to exclude or allow adsorption of well-defined proteins was developed based on capillary electrophoresis. A series of proteins with different molecular weights (MW) were used as molecular probes to screen their adsorption behavior on nanoparticles bearing different molecular architectures at their surface. This novel strategy evaluating to some degree a functionality of NMs can bring additional information about their shell property and might allow for a better perception of their behavior in the presence of biological components. The developed method could discriminate nanoparticles with a high surface coverage excluding high MW proteins from nanoparticles with a low surface coverage that allowed high MW proteins to adsorb on their surface. The method has the potential for further standardization and automation for a routine use. It can be applied in quality control of NMs and to investigate interactions between proteins and NM in different situations

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability