Undergraduate students’ critical online reasoning - process mining analysis

To successfully learn using open Internet resources, students must be able to critically search, evaluate and select online information, and verify sources. Defined as critical online reasoning (COR), this construct is operationalized on two levels in our study: (1) the student level using the newly developed Critical Online Reasoning Assessment (CORA), and (2) the online information processing level using event log data, including gaze durations and fixations. The written responses of 32 students for one CORA task were scored by three independent raters. The resulting score was operationalized as “task performance,” whereas the gaze fixations and durations were defined as indicators of “process performance.” Following a person-oriented approach, we conducted a process mining (PM) analysis, as well as a latent class analysis (LCA) to test whether—following the dual-process theory—the undergraduates could be distinguished into two groups based on both their process and task performance. Using PM, the process performance of all 32 students was visualized and compared, indicating two distinct response process patterns. One group of students (11), defined as “strategic information processers,” processed online information more comprehensively, as well as more efficiently, which was also reflected in their higher task scores. In contrast, the distributions of the process performance variables for the other group (21), defined as “avoidance information processers,” indicated a poorer process performance, which was also reflected in their lower task scores. In the LCA, where two student groups were empirically distinguished by combining the process performance indicators and the task score as a joint discriminant criterion, we confirmed these two COR profiles, which were reflected in high vs. low process and task performances. The estimated parameters indicated that high-performing students were significantly more efficient at conducting strategic information processing, as reflected in their higher process performance. These findings are so far based on quantitative analyses using event log data. To enable a more differentiated analysis of students’ visual attention dynamics, more in-depth qualitative research of the identified student profiles in terms of COR will be required

Interprofessional approach for teaching functional knee joint anatomy

AbstractProfound knowledge in functional and clinical anatomy is a prerequisite for efficient diagnosis in medical practice. However, anatomy teaching does not always consider functional and clinical aspects. Here we introduce a new interprofessional approach to effectively teach the anatomy of the knee joint. The presented teaching approach involves anatomists, orthopaedists and physical therapists to teach anatomy of the knee joint in small groups under functional and clinical aspects. The knee joint courses were implemented during early stages of the medical curriculum and medical students were grouped with students of physical therapy to sensitize students to the importance of interprofessional work. Evaluation results clearly demonstrate that medical students and physical therapy students appreciated this teaching approach. First evaluations of following curricular anatomy exams suggest a benefit of course participants in knee-related multiple choice questions. Together, the interprofessional approach presented here proves to be a suitable approach to teach functional and clinical anatomy of the knee joint and further trains interprofessional work between prospective physicians and physical therapists as a basis for successful healthcare management

Recombinant ncTom40 has a β-barrel structure. (a) Far UV CD spectra of ncTom40 in decylmaltoside. (b) Superposition of ¹³C-¹³C proton driven spin diffusion spectra of ncTom40 (red) and hVDAC1 (green; reproduced from [4]), both in DMPC liposomes. The mixing time was 15 ms.

<p>Recombinant ncTom40 has a β-barrel structure. (a) Far UV CD spectra of ncTom40 in decylmaltoside. (b) Superposition of ¹³C-¹³C proton driven spin diffusion spectra of ncTom40 (red) and hVDAC1 (green; reproduced from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112374#pone.0112374-Schneider1" target="_blank">[4]</a>), both in DMPC liposomes. The mixing time was 15 ms.</p

Scheme illustrating the H/D exchange strategy developed for membrane proteins (blue) reconstituted into liposomes (yellow).

<p>A white color indicates H₂O buffer, black color 100% D₂O buffer and grey color the dissolution buffer, which contains 4 M GdnSCN. During the incubation period in 100% D₂O solvent exposed residues will exchange amide protons against deuterium (lower row, middle panel). They will therefore not be visible in the denatured monomer (lower right panel).</p

Cα secondary chemical shifts (upper chart) and Cα secondary structure propensities (lower chart) of ncTom40 obtained from APSY experiments recorded at 295K.

<p>Secondary structure propensities were calculated using SSP <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112374#pone.0112374-Molday1" target="_blank">[42]</a>. The predicted topology of ncTom40 is shown on top with secondary structure elements highlighted in grey. Only assignments classified by MARS <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112374#pone.0112374-Hiller1" target="_blank">[27]</a> as reliable were used.</p

Structural characterization of liposome-embedded ncTom40 by H/D exchange coupled to solution-state NMR.

<p>(a) Enlarged spectral regions of [¹H, ¹⁵N]-HSQC spectra at increasing back-exchange times. To reduce signal overlap, ncTom40 was selectively ¹⁵N-labeled at ALA, HIS, ILE, MET, THR. Time points indicate the time after start of the first HSQC. The dissolution buffer contained 75% D₂O. Sequence-specific resonance assignments are indicated. (b) Sequence-specific signal intensities in the first HSQC after dissolution in 100% D₂O buffer. (c) NMR signal intensity change of residues in panel (a) during back-exchange in 75% D₂O. Intensity values were normalized on the basis of the noise level in the spectra. Error bars are based on signal-to-noise. (d) Protonation ratios for residues of Tom40 at the beginning of back exchange. (e) Protonation ratios shown in (d) were mapped onto the topology model of ncTom40, which was predicted on the basis of its homology to hVDAC1. Residues predicted to be in a β-strand or α-helix are boxed. Green-shaded (red-shaded) residues have protonation ratios larger (lower) than 0.3. Residues shown in white were not analyzed due to signal overlap, low signal-to-noise or missing resonance assignment.</p

APSY experiments recorded at different temperatures and assignments obtained for denatured ncTom40 (339 non-proline residues) by MARS [31].

<p>Assignments classified by MARS as low are not reliable and were excluded from further analysis.</p><p>APSY experiments recorded at different temperatures and assignments obtained for denatured ncTom40 (339 non-proline residues) by MARS <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0112374#pone.0112374-Panchal1" target="_blank">[31]</a>.</p

NMR-Based Detection of Hydrogen/Deuterium Exchange in Liposome-Embedded Membrane Proteins.

Membrane proteins play key roles in biology. Determination of their structure in a membrane environment, however, is highly challenging. To address this challenge, we developed an approach that couples hydrogen/deuterium exchange of membrane proteins to rapid unfolding and detection by solution-state NMR spectroscopy. We show that the method allows analysis of the solvent protection of single residues in liposome-embedded proteins such as the 349-residue Tom40, the major protein translocation pore in the outer mitochondrial membrane, which has resisted structural analysis for many years.peerReviewe