Are students learning what was intended? Evaluating progress using student perception surveys

Student learning can be evaluated through performance in assessment tasks. With the final examination often being the most heavily weighted assessment, academics may not have the opportunity to evaluate whether students are learning what was intended until the completion of the course. Student perception of learning achievements can provide an alternative means for academics to receive timely evidence on student progress. In a first-year biology cohort (n=1300) with a large group of academic stakeholders, a survey was designed to assist lecturers in understanding the progress of students with their learning. At the end of each learning module, students were asked to complete a voluntary survey to rate their understanding on intended learning outcomes. The surveys used matrix questions, where, for each learning outcome, students indicated whether they were confident in their understanding, were neutral or required additional support. The outcomes from the surveys were used to direct students to learning resources and to inform academics of their own teaching practices. This approach provides a valuable tool in connecting academics with students in a large cohort, and has the potential to measure the impact of innovative teaching, support interventions and assessment changes

GDNF slows loss of motoneurons but not axonal degeneration or premature death of pmn/pmn mice.

Glial cell line-derived neurotrophic factor (GDNF), a member of the TG F-beta superfamily, has been shown to be a highly potent neurotrophic factor that enhances survival of various neuronal cell types including motoneurons. To assess its therapeutic potential in treating neurodegenerative diseases such as amyotrophic lateral sclerosis, we treated mutant mice displaying motoneuron degeneration (progressive motor neuropathy; pmn) with encapsulated GDNF-secreting cells. Effects of GDNF treatment on pmn/pmn mice were compared with previous results obtained with ciliary neurotrophic factor (CNTF) [Sagot Y, Tan SA, Baetge E, Schmalbruch H, Kato AC, Aebischer P (1995) Eur J Neurosci 7:1313-1322]. In contrast to CNTF, GDNF did not increase the lifespan of pmn/pmn mice. However, GDNF significantly reduced the loss of facial motoneurons by 50%, a value similar to what was observed when CNTF was administered to the pmn/pmn mice. Surprisingly, myelinated axon counts revealed that GDNF had no effect on nerve degeneration. Therefore, despite its potential in rescuing motoneuron cell bodies, the inability of GDNF to prevent nerve degeneration in pmn/pmn mice suggests that its usefulness in the treatment of motor neuron diseases may be restricted to cotreatment with other factors that act on the nerve process

Integrated visual analysis of protein structures, sequences, and feature data

© 2015 Stolte et al. Background: To understand the molecular mechanisms that give rise to a protein's function, biologists often need to (i) find and access all related atomic-resolution 3D structures, and (ii) map sequence-based features (e.g., domains, single-nucleotide polymorphisms, post-translational modifications) onto these structures. Results: To streamline these processes we recently developed Aquaria, a resource offering unprecedented access to protein structure information based on an all-against-all comparison of SwissProt and PDB sequences. In this work, we provide a requirements analysis for several frequently occuring tasks in molecular biology and describe how design choices in Aquaria meet these requirements. Finally, we show how the interface can be used to explore features of a protein and gain biologically meaningful insights in two case studies conducted by domain experts. Conclusions: The user interface design of Aquaria enables biologists to gain unprecedented access to molecular structures and simplifies the generation of insight. The tasks involved in mapping sequence features onto structures can be conducted easier and faster using Aquaria

Glial cell line-derived neurotrophic factor (GDNF), a new neurotrophic factor for motoneurones

Glial cell line-derived neurotrophic factor (GDNF) has been postulated to be a specific dopaminergic neurotrophic factor since it selectively enhances the survival of dopaminergic neurones in vitro. We report here that GDNF can also act as a neurotrophic factor for motoneurones. GDNF released by GDNF-transfected BHK cells increases the activity of choline acetyltransferase (ChAT) in cultures from embryonic rat ventral mesencephalon containing cholinergic neurones from cranial motor nuclei and in cultured spinal motoneurones. Furthermore, local application of polymer-encapsulated BHK cells releasing GDNF to transected facial nerve in newborn rats diminishes the death of motoneurones normally occurring after axotomy in the neonatal period. The present results indicate that GDNF may have a therapeutic potential in human motoneurone diseases such as amyotrophic lateral sclerosis

Glial cell line-derived neurotrophic factor (GDNF), a new neurotrophic factor for motoneurones

Glial cell line-derived neurotrophic factor (GDNF) has been postulated to be a specific dopaminergic neurotrophic factor since it selectively enhances the survival of dopaminergic neurones in vitro. We report here that GDNF can also act as a neurotrophic factor for motoneurones. GDNF released by GDNF-transfected BHK cells increases the activity of choline acetyltransferase (ChAT) in cultures from embryonic rat ventral mesencephalon containing cholinergic neurones from cranial motor nuclei and in cultured spinal motoneurones. Furthermore, local application of polymer-encapsulated BHK cells releasing GDNF to transected facial nerve in newborn rats diminishes the death of motoneurones normally occurring after axotomy in the neonatal period. The present results indicate that GDNF may have a therapeutic potential in human motoneurone diseases such as amyotrophic lateral sclerosis

Evaluating viewpoint entropy for ribbon representation of protein structure

While many measures of viewpoint goodness have been proposed in computer graphics, none have been evaluated for ribbon representations of protein secondary structure. To fill this gap, we conducted a user study on Amazon’s Mechanical Turk platform, collecting human viewpoint preferences from 65 participants for 4 representative su- perfamilies of protein domains. In particular, we evaluated viewpoint entropy, which was previously shown to be a good predictor for human viewpoint preference of other, mostly non-abstract objects. In a second study, we asked 7 molecular biology experts to find the best viewpoint of the same protein domains and compared their choices with viewpoint entropy.\ud \ud Our results show that viewpoint entropy overall is a significant predictor of human viewpoint preference for ribbon representations of protein secondary structure. However, the accuracy is highly dependent on the complexity of the structure: while most participants agree on good viewpoints for small, non-globular structures with few secondary structure elements, viewpoint preference varies considerably for complex structures. Finally, experts tend to choose viewpoints of both low and high viewpoint entropy to emphasize different aspects of the respective structure