Endocytosis and lysosomal degradation of GluA2/3 AMPARs in response to oxygen/glucose deprivation in hippocampal but not cortical neurons

Abstract Global cerebral ischemia results in oxygen and glucose deprivation (OGD) and consequent delayed cell death of vulnerable neurons, with hippocampal CA1 neurons more vulnerable than cortical neurons. Most AMPA receptors (AMPARs) are heteromeric complexes of subunits GluA1/GluA2 or GluA2/GluA3, and the presence of GluA2 renders AMPARs Ca2+-impermeable. In hippocampal CA1 neurons, OGD causes the synaptic expression of GluA2-lacking Ca2+-permeable AMPARs, contributing to toxic Ca2+ influx. The loss of synaptic GluA2 is caused by rapid trafficking of GluA2-containing AMPARs from the cell surface, followed by a delayed reduction in GluA2 mRNA expression. We show here that OGD causes endocytosis, lysosomal targeting and consequent degradation of GluA2- and GluA3-containing AMPARs, and that PICK1 is required for both OGD-induced GluA2 endocytosis and lysosomal sorting. Our results further suggest that GluA1-containing AMPARs resist OGD-induced endocytosis. OGD does not cause GluA2 endocytosis in cortical neurons, and we show that PICK1 binding to the endocytic adaptor AP2 is enhanced by OGD in hippocampal, but not cortical neurons. We propose that endocytosis of GluA2/3, caused by a hippocampal-specific increase in PICK1-AP2 interactions, followed by PICK1-dependent lysosomal targeting, are critical events in determining changes in AMPAR subunit composition in the response to ischaemia

Improving Education in Medical Statistics: Implementing a Blended Learning Model in the Existing Curriculum.

BACKGROUND:Although recent studies report on the benefits of blended learning in improving medical student education, there is still no empirical evidence on the relative effectiveness of blended over traditional learning approaches in medical statistics. We implemented blended along with on-site (i.e. face-to-face) learning to further assess the potential value of web-based learning in medical statistics. METHODS:This was a prospective study conducted with third year medical undergraduate students attending the Faculty of Medicine, University of Belgrade, who passed (440 of 545) the final exam of the obligatory introductory statistics course during 2013-14. Student statistics achievements were stratified based on the two methods of education delivery: blended learning and on-site learning. Blended learning included a combination of face-to-face and distance learning methodologies integrated into a single course. RESULTS:Mean exam scores for the blended learning student group were higher than for the on-site student group for both final statistics score (89.36±6.60 vs. 86.06±8.48; p = 0.001) and knowledge test score (7.88±1.30 vs. 7.51±1.36; p = 0.023) with a medium effect size. There were no differences in sex or study duration between the groups. Current grade point average (GPA) was higher in the blended group. In a multivariable regression model, current GPA and knowledge test scores were associated with the final statistics score after adjusting for study duration and learning modality (p<0.001). CONCLUSION:This study provides empirical evidence to support educator decisions to implement different learning environments for teaching medical statistics to undergraduate medical students. Blended and on-site training formats led to similar knowledge acquisition; however, students with higher GPA preferred the technology assisted learning format. Implementation of blended learning approaches can be considered an attractive, cost-effective, and efficient alternative to traditional classroom training in medical statistics

Bridging the gap between informatics and medicine upon medical school entry: Implementing a course on the Applicative Use of ICT

<div><p>Education is undergoing profound changes due to permanent technological innovations. This paper reports the results of a pilot study aimed at developing, implementing and evaluating the course, "Applicative Use of Information and Communication Technologies (ICT) in Medicine," upon medical school entry. The Faculty of Medicine, University of Belgrade, introduced a curriculum reform in 2014 that included the implementation of the course, “Applicative Use of ICT in Medicine” for first year medical students. The course was designed using a blended learning format to introduce the concepts of Web-based learning environments. Data regarding student knowledge, use and attitudes towards ICT were prospectively collected for the classes of 2015/16 and 2016/17. The teaching approach was supported by multimedia didactic materials using Moodle LMS. The overall quality of the course was also assessed. The five level Likert scale was used to measure attitudes related to ICT. In total, 1110 students were assessed upon medical school entry. A small number of students (19%) had previous experience with e-learning. Students were largely in agreement that informatics is needed in medical education, and that it is also useful for doctors (4.1±1.0 and 4.1±0.9, respectively). Ability in informatics and use of the Internet in education in the adjusted multivariate regression model were significantly associated with positive student attitudes toward ICT. More than 80% of students stated that they had learned to evaluate medical information and would use the Internet to search medical literature as an additional source for education. The majority of students (77%) agreed that a blended learning approach facilitates access to learning materials and enables time independent learning (72%). Implementing the blended learning course, "Applicative Use of ICT in Medicine," may bridge the gap between medicine and informatics upon medical school entry. Students displayed positive attitudes towards using ICT and gained adequate skills necessary to function effectively in an information-rich environment.</p></div

Self-reported ability in informatics and computers for two student classes upon medical school entry.

<p>Self-reported ability in informatics and computers for two student classes upon medical school entry.</p

Evaluation of the course–both cohorts.

<p>Evaluation of the course–both cohorts.</p

Student demographic data and response rates per academic school year.

<p>Student demographic data and response rates per academic school year.</p

Descriptive statistics of students characteristics and learning outcomes.

<p>Descriptive statistics of students characteristics and learning outcomes.</p

Variables associated with student statistics achievement–knowledge test.

<p>Variables associated with student statistics achievement–knowledge test.</p

Variables associated with student statistics achievement–final statistics score.

<p>Variables associated with student statistics achievement–final statistics score.</p

Changes in student attitudes towards statistics after course completion (n = 90).

<p>Changes in student attitudes towards statistics after course completion (n = 90).</p