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.     

A high‐throughput capillary isoelectric focusing immunoassay for fingerprinting protein sialylation

The serum half‐life, biological activity, and solubility of many recombinant glycoproteins depend on their sialylation. Monitoring glycoprotein sialylation during cell culture manufacturing is, therefore, critical to ensure product efficacy and safety. Here a high‐throughput method for semi‐quantitative fingerprinting of glycoprotein sialylation using capillary isoelectric focusing immunoassay on NanoPro (Protein Simple) platform was developed. The method was specific, sensitive, precise, and robust. It could analyze 2 μL of crude cell culture samples without protein purification, and could automatically analyze from 8 samples in 4 h to 96 samples in 14 h without analyst supervision. Furthermore, its capability to detect various changes in sialylation fingerprints during cell culture manufacturing process was indispensable to ensure process robustness and consistency. Moreover, the changes in the sialylation fingerprints analyzed by this method showed strong correlations with intact mass analysis using liquid chromatography and mass spectrometry. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 32:235–241, 2016     

Association of β<Subscript>2</Subscript>-microglobulin with the α<Subscript>3</Subscript> domain of H-2D<Superscript>b</Superscript> heavy chain

MHC class I molecules are heterotrimeric complexes composed of heavy chain, ₂-microglobulin (₂m) and short peptide. This trimeric complex is generated in the endoplasmic reticulum (ER), where a peptide loading complex (PLC) facilitates transport from the cytosol and binding of the peptide to the preassembled ER resident heavy chain/₂m dimers. Association of mouse MHC class I heavy chain with ₂m is characterized by allelic differences in the number and/or positions of amino acid interactions. It is unclear, however, whether all alleles follow common binding patterns with minimal contributions by allele-specific contacts, or whether essential contacts with ₂m are different for each allele. While searching for the PLC binding site in the ₃ domain of the mouse MHC class I molecule H-2D^b, we unexpectedly discovered a site critical for binding mouse, but not human, ₂m. Interestingly, amino acids in the corresponding region of another MHC class I heavy chain allele do not make contacts with the mouse ₂m. Thus, there are allelic differences in the modes of binding of ₂m to the heavy chain of MHC class I.     

Protein flexibility and intrinsic disorder

Comparisons were made among four categories of protein flexibility: (1) low-B-factor ordered regions, (2) high-B-factor ordered regions, (3) short disordered regions, and (4) long disordered regions. Amino acid compositions of the four categories were found to be significantly different from each other, with high-B-factor ordered and short disordered regions being the most similar pair. The high-B-factor (flexible) ordered regions are characterized by a higher average flexibility index, higher average hydrophilicity, higher average absolute net charge, and higher total charge than disordered regions. The low-B-factor regions are significantly enriched in hydrophobic residues and depleted in the total number of charged residues compared to the other three categories. We examined the predictability of the high-B-factor regions and developed a predictor that discriminates between regions of low and high B-factors. This predictor achieved an accuracy of 70% and a correlation of 0.43 with experimental data, outperforming the 64% accuracy and 0.32 correlation of predictors based solely on flexibility indices. To further clarify the differences between short disordered regions and ordered regions, a predictor of short disordered regions was developed. Its relatively high accuracy of 81% indicates considerable differences between ordered and disordered regions. The distinctive amino acid biases of high-B-factor ordered regions, short disordered regions, and long disordered regions indicate that the sequence determinants for these flexibility categories differ from one another, whereas the significantly-greater-than-chance predictability of these categories from sequence suggest that flexible ordered regions, short disorder, and long disorder are, to a significant degree, encoded at the primary structure level.     

Slow rate during AF improves ventricular performance by reducing sensitivity to cycle length irregularity

Atrial fibrillation (AF) is characterized by short and irregular ventricular cycle lengths (VCL). While the beneficial effects of heart rate slowing (i.e., the prolongation of VCL) in AF are well recognized, little is known about the impact of irregularity. In 10 anesthetized dogs, R-R intervals, left ventricular (LV) pressure, and aortic flow were collected for >500 beats during fast AF and when the average VCL was prolonged to 75%, 100%, and 125% of the intrinsic sinus cycle length by selective atrioventricular (AV) nodal vagal stimulation. We used the ratio of the preceding and prepreceding R-R intervals (RR(p)/RR(pp)) as an index of cycle length irregularity and assessed its effects on the maximum LV power, the minimum of the first derivative of LV pressure, and the time constant of relaxation by using nonlinear fitting with monoexponential functions. During prolongation of VCL, there was a pronounced decrease in curvature with the formation of a plateau, indicating a lesser dependence on RR(p)/RR(pp). We conclude that prolongation of the VCL during AF reduces the sensitivity of the LV performance parameters to irregularity.