Alignment between learning needs and learning goals of Mini-CEX in clerkships

Background: Defining learning goals (LG) in alignment with learning needs (LN) is one of the key purposes of formative workplace-based assessment, but studies about this topic are scarce. Summary of Work: We analysed quantitatively and qualitatively how often trainer-student pairs identified the same LN during Mini Clinical Evaluation Exercises (Mini-CEX) in clerkships and to what degree those LNs were in line with the recorded LGs. Multilevel logistic regression models were used to predict LGs by identified LNs, controlling for context variables. Summary of Results: 512 trainers and 165 students conducted 1783 Mini-CEX (98% completion rate). Concordantly, trainer-student pairs most often identified LNs in the domains ‘clinical reasoning’ (23% of 1167 complete forms), ‘organisation / efficiency’ (20%) and ‘physical examination’ (20%). At least one ‘defined’ LG was noted on 313 student forms (18% of 1710), with a total of 446 LGs. Of these, the most frequent LGs were ‘physical examination’ (49% of 446 LGs) and ‘history taking’ (21%); corresponding LNs as well as context variables (e.g. clinic size) were found to be predictors of these LGs. Discussion and Conclusions: Although trainer-student pairs often agreed in their identified LNs, many assessments did not result in an aligned LG or a LG at all. Interventions are needed to enhance the proportion of (aligned) LGs in Mini-CEX in order to tap into its full potential not only as a ‘diagnostic’ but also as an ‘educational tool’. Take-home messages: The sparseness of LGs, their dependency on context variables and their partial non-alignment with students’ LNs raise the question of how the effectiveness of Mini-CEX can be further enhanced.

A component of the mitochondrial outer membrane proteome of T. brucei probably contains covalent bound fatty acids

A subclass of eukaryotic proteins is subject to modification with fatty acids, the most common of which are palmitic and myristic acid. Protein acylation allows association with cellular membranes in the absence of transmembrane domains. Here we examine POMP39, a protein previously described to be present in the outer mitochondrial membrane proteome (POMP) of the protozoan parasite Trypanosoma brucei. POMP39 lacks canonical transmembrane domains, but is likely both myristoylated and palmitoylated on its N-terminus. Interestingly, the protein is also dually localized on the surface of the mitochondrion as well as in the flagellum of both insect-stage and the bloodstream form of the parasites. Upon abolishing of global protein acylation or mutation of the myristoylation site, POMP39 relocates to the cytosol. RNAi-mediated ablation of the protein neither causes a growth phenotype in insect-stage nor bloodstream form trypanosomes.

Time of emergence of trends in ocean biogeochemistry

For the detection of climate change, not only the magnitude of a trend signal is of significance. An essential issue is the time period required by the trend to be detectable in the first place. An illustrative measure for this is time of emergence (ToE), that is, the point in time when a signal finally emerges from the background noise of natural variability. We investigate the ToE of trend signals in different biogeochemical and physical surface variables utilizing a multi-model ensemble comprising simulations of 17 Earth system models (ESMs). We find that signals in ocean biogeochemical variables emerge on much shorter timescales than the physical variable sea surface temperature (SST). The ToE patterns of pCO2 and pH are spatially very similar to DIC (dissolved inorganic carbon), yet the trends emerge much faster – after roughly 12 yr for the majority of the global ocean area, compared to between 10 and 30 yr for DIC. ToE of 45–90 yr are even larger for SST. In general, the background noise is of higher importance in determining ToE than the strength of the trend signal. In areas with high natural variability, even strong trends both in the physical climate and carbon cycle system are masked by variability over decadal timescales. In contrast to the trend, natural variability is affected by the seasonal cycle. This has important implications for observations, since it implies that intra-annual variability could question the representativeness of irregularly sampled seasonal measurements for the entire year and, thus, the interpretation of observed trends.