The structure of a dendrimer exhibits a large number of internal and superficial cavities, which can be exploited, to capture and deliver small organic molecules, enabling their use in drug delivery. Structure-based modeling and quantum mechanical studies can be used to accurately understand the interactions between functionalized dendrimers and molecules of pharmaceutical and industrial interest. In this study, we implemented a Metropolis Monte Carlo algorithm to calculate the interaction energy of dendrimer–drug complexes, which can be used for in silico prediction of dendrimer–drug affinity. Initially, a large-scale sampling of different dendrimer–drug conformations were generated using Euler angles. Then, each conformation was distributed on different nodes of a GRID computational system; where its interaction energy was calculate by semi-empirical quantum mechanical methods. These energy calculations were performed for four different non-steroidal anti-inflammatory drugs, each showing different affinities for PAMAM–G4 dendrimer. The affinities were also characterized experimentally by using Cooks’ kinetic method to calculate PAMAM–drug dissociation constants. The quantitative structure–activity relationship between the interaction energies and dissociation constants showed statistical correlations with r2 > 0.9.

Herein, we present a new collaborative clinical simulation (CCS) model for the development of medical competencies by medical students. The model is a comprehensive compendium of published considerations and recommendations on clinical simulation (CS) and computer-supported collaborative learning (CSCL). Currently, there are no educational models combining CS and CSCL. The CCS model was designed for the acquisition and assessment of clinical competencies; working collaboratively and supported by technology, small groups of medical students independently design and perform simulated cases. The model includes four phases in which the learning objectives, short case scenarios, materials, indices, and the clinical simulation are designed, monitored, rated and debriefed.

After the progress made during the genomics era, bioinformatics was tasked with supporting the fl ow of information generated by nanobiotechnology efforts. This challenge requires adapting classical bioinformatic and computational chemistry tools to store, standardize, analyze, and visualize nanobiotechnological information. Thus, old and new bioinformatic and computational chemistry tools have been merged into a new sub-discipline: nanoinformatics. This review takes a second look at the development of this new and exciting area as seen from the perspective of the evolution of nanobiotechnology applied to the life sciences. The knowledge obtained at the nano-scale level implies answers to new questions and the development of new concepts in different fi elds. The rapid convergence of technologies around nanobiotechnologies has spun off collaborative networks and web platforms created for sharing and discussing the knowledge generated in nanobiotechnology. The implementation of new database schemes suitable for storage, processing and integrating physical, chemical, and biological properties of nanoparticles will be a key element in achieving the promises in this convergent fi eld. In this work, we will review some applications of nanobiotechnology to life sciences in generating new requirements for diverse scientifi c fi elds, such as bioinformatics and computational chemistry.

In health sciences and medicine, collaborative learning has an important role in the development of competences to solve clinical situations. Adequate cooperation, coordination and communication skills have a direct effect on patient safety. Computer Supported Collaborative Learning (CSCL) and Clinical Simulation (CS), separately, are effective and efficient educational methods to develop competences in undergraduate medical students. To our knowledge, educational models that combine both teaching methods, including a personalized attention of the student, educational infrastructure, materials, teaching techniques and assessment competencies, have not been proposed previously. This article describes the application of a combined model of CSCL and CS for teaching clinical competences to medical students. Since 2015, the collaborative clinical simulation model is part of the training agenda of the Universidad de Talca Medical School in Chile. During 2016 and 2017 it was also applied on students of the Universidad de Barcelona Faculty of Medicine in Spain. According to the experience acquired, implementation of this method is feasible with commonly used resources, although its real efficacy remains to be evaluated.

Background The collaborative clinical simulation (CCS) model is a structured method for the development and assessment of clinical competencies through small groups working collaboratively in simulated environments. From 2016 onward, the CCS model has been applied successfully among undergraduate and graduate medical students from the Universidad de Talca, Chile; the Universität de Barcelona, Spain; and the Universidad de Vic-Manresa, Spain. All the templates for building the clinical cases and the assessment instruments with CCS were printed on paper. Considering the large number of CCS sessions and the number of participating students that are required throughout the medical degree curriculum, it is impossible to keep an organized record when the instruments are printed on paper. Moreover, with the COVID-19 pandemic, web platforms have become important as safe training environments for students and medical faculties; this new educational environment should include the consolidation and adaptation of didactic sessions that create and use available virtual cases and use different web platforms. Objective The goal of this study is to describe the design and development of a web platform that was created to strengthen the CCS model. Methods The design of the web platform aimed to support each phase of the CCS by incorporating functional requirements (ie, features that the web platform will be able to perform) and nonfunctional requirements (ie, how the web platform should behave) that are needed to run collaborative sessions. The software was developed under the Model-View-Controller architecture to separate the views from the data model and the business logic. Results MOSAICO is a web platform used to design, perform, and assess collaborative clinical scenarios for medical students. MOSAICO has four modules: educational design, students’ collaborative design, collaborative simulation, and collaborative debriefing. The web platform has three different user profiles: academic simulation unit, teacher, and student. These users interact under different roles in collaborative simulations. MOSAICO enables a collaborative environment, which is connected via the internet, to design clinical scenarios guided by the teacher and enables the use of all data generated to be discussed in the debriefing session with the teacher as a guide. The web platform is running at the Universidad de Talca in Chile and is supporting collaborative simulation activities via the internet for two medical courses: (1) Semiology for third-year students (70 students in total) and (2) Medical Genetics for fifth-year students (30 students in total). Conclusions MOSAICO is applicable within the CCS model and is used frequently in different simulation sessions at the Universidad de Talca, where medical students can work collaboratively via the internet. MOSAICO simplifies the application and reuse of clinical simulation scenarios, allowing its use in multiple simulation centers. Moreover, its applications in different courses (ie, a large part of the medical curriculum) support the automatic tracking of simulation activities and their assessment.