Generative AI tools in healthcare education and research

Given the rapid development and accessibility of these tools, it has become clear that Generative AI has multiple uses for teaching, learning and research. This workshop will provide best practices, in a hands-on experience, of the most relevant Generative AI tools for healthcare educators and students, with the aim of understanding the mechanisms that drive AI and the usefulness of it.N/

Why Advice on Task Selection May Hamper Learning in On-Demand Education

Taminiau, E. M. C., Kester, L., Corbalan, G., Alessi, S. M., Moxnes, E., Gijselaers, W. H., Kirschner, P. A., & Van Merriënboer, J. J. G. (2013). Why advice on task selection may hamper learning in on-demand education. Computers in Human Behavior, 29, 145-154. doi: 10.1016/j.chb.2012.07.028In on-demand education, learners are required to plan their own learning trajectory by selecting suitable learning tasks. A positive effect on learning is expected when learners select tasks that help them fulfil their individual learning needs. However, the selection of suitable tasks is a difficult process for learners with little domain knowledge and suboptimal task-selection skills. A common solution for helping learners deal with on-demand education and develop domain-specific skills is to give them advice on task selection. In a randomized experiment, learners (N = 30) worked on learning tasks in the domain of system dynamics and received either advice or no advice on the selection of new learning tasks. Surprisingly, the no-advice group outperformed the advice group on a post-test measuring domain-specific skills. It is concluded that giving advice on task selection prevents learners from thinking about how the process of task selection works. The advice seems to supplant rather than support their considerations why they should perform the advised task, which results in negative effects on learning. Implications for future research on giving advice in on-demand education are discussed

The role of 3-phosphoinositide-dependent protein kinase 1 in activating AGC kinases defined in embryonic stem cells

AbstractBackground: Protein kinase B (PKB), and the p70 and p90 ribosomal S6 kinases (p70 S6 kinase and p90 Rsk, respectively), are activated by phosphorylation of two residues, one in the ‘T-loop’ of the kinase domain and, the other, in the hydrophobic motif carboxy terminal to the kinase domain. The 3-phosphoinositide-dependent protein kinase 1 (PDK1) activates many AGC kinases in vitro by phosphorylating the T-loop residue, but whether PDK1 also phosphorylates the hydrophobic motif and whether all other AGC kinases are substrates for PDK1 is unknown.Results: Mouse embryonic stem (ES) cells in which both copies of the PDK1 gene were disrupted were viable. In PDK1−/− ES cells, PKB, p70 S6 kinase and p90 Rsk were not activated by stimuli that induced strong activation in PDK1+/+ cells. Other AGC kinases — namely, protein kinase A (PKA), the mitogen- and stress-activated protein kinase 1 (MSK1) and the AMP-activated protein kinase (AMPK) — had normal activity or were activated normally in PDK1−/− cells. The insulin-like growth factor 1 (IGF1) induced PKB phosphorylation at its hydrophobic motif, but not at its T-loop residue, in PDK1−/− cells. IGF1 did not induce phosphorylation of p70 S6 kinase at its hydrophobic motif in PDK1−/− cells.Conclusions: PDK1 mediates activation of PKB, p70 S6 kinase and p90 Rsk in vivo, but is not rate-limiting for activation of PKA, MSK1 and AMPK. Another kinase phosphorylates PKB at its hydrophobic motif in PDK1−/− cells. PDK1 phosphorylates the hydrophobic motif of p70 S6 kinase either directly or by activation of another kinase

Functional implications of assigned, assumed and assembled PKC structures

The empirical derivation of PKC (protein kinase C) domain structures and those modelled by homology or imputed from protein behaviour have been extraordinarily valuable both in the elucidation of PKC pathway mechanisms and in the general lessons that extrapolate to other signalling pathways. For PKC family members, there are many domain/subdomain structures and models, covering all of the known domains, variably present in this family of protein serine/threonine kinases (C1, C2, PB1, HR1, kinase domains). In addition to these structures, there are a limited number of complexes defined, including the structure of the PKC epsilon V3-14-3-3 complex. In the context of structure-driven insights into PKC pathways, there are several broadly applicable principles and mechanisms relevant to the operation of and intervention in signalling pathways. These principles have an impact in unexpected ways, from the regulation of membrane targeting, through strategies for pharmacological intervention, to biomarkers.</p

Dependence on plasma shape and plasma fueling for small edge-localized mode regimes in TCV and ASDEX Upgrade

\u3cp\u3eWithin the EUROfusion MST1 work package, a series of experiments has been conducted on AUG and TCV devices to disentangle the role of plasma fueling and plasma shape for the onset of small ELM regimes. On both devices, small ELM regimes with high confinement are achieved if and only if two conditions are fulfilled at the same time. Firstly, the plasma density at the separatrix must be large enough (n\u3csub\u3ee,sep\u3c/sub\u3e/n\u3csub\u3eG\u3c/sub\u3e ∼ 0.3), leading to a pressure profile flattening at the separatrix, which stabilizes type-I ELMs. Secondly, the magnetic configuration has to be close to a double null (DN), leading to a reduction of the magnetic shear in the extreme vicinity of the separatrix. As a consequence, its stabilizing effect on ballooning modes is weakened.\u3c/p\u3