Introduction: Individual assessment disregards the team aspect of clinical work. Team assessment collapses the individual into the group. Neither is sufficient for medical education, where measures need to attend to the individual while also accounting for interactions with others. Valid and reliable measures of interdependence are critical within medical education given the collaborative manner in which patient care is provided. Medical education currently lacks a consistent approach to measuring the performance between individuals working together as part of larger healthcare team. This review's objective was to identify existing approaches to measuring this interdependence.Methods: Following Arksey & O'Malley's methodology, we conducted a scoping review in 2018 and updated it to 2020. A search strategy involving five databases located >12 000 citations. At least two reviewers independently screened titles and abstracts, screened full texts (n = 161) and performed data extraction on twentyseven included articles. Interviews were also conducted with key informants to check if any literature was missing and assess that our interpretations made sense.Results: Eighteen of the twenty-seven articles were empirical; nine conceptual with an empirical illustration. Eighteen were quantitative; nine used mixed methods. The articles spanned five disciplines and various application contexts, from online learning to sports performance. Only two of the included articles were from the field of Medical Education. The articles conceptualised interdependence of a group, using theoretical constructs such as collaboration synergy; of a network, using constructs such as degree centrality; and of a dyad, using constructs such as synchrony. Both descriptive (eg social network analysis) and inferential (eg multi-level modelling) approaches were described. Conclusion:Efforts to measure interdependence are scarce and scattered across disciplines. Multiple theoretical concepts and inconsistent terminology may be limiting programmatic work. This review motivates the need for further study of measurement techniques, particularly those combining multiple approaches, to capture interdependence in medical education.

Antibiotics are frequently introduced into agricultural soils with the application of sewage sludge or farm organic fertilizers. Repeated exposure of soils to a pollutant can enrich for microbial populations that metabolize the chemical, reducing its environmental persistence. In London, Canada, soils from a long-term field experiment have received different concentrations of antibiotics annually for several years. The purpose of the present study was to assess the bioavailability of sulfamethazine, erythromycin, or ciprofloxacin through aqueous extractions with borax or EDTA solutions and their biodegradation following different soil exposure scenarios. Control soils and soils treated annually in the field with 10 mg antibiotics per kg were sampled, supplemented in the laboratory with radiolabeled antibiotic either added directly or carried in dairy manure. Sulfamethazine and erythromycin were initially more bioavailable than ciprofloxacin, with aqueous extractabilities representing 60, 36, and 8%, respectively. Sulfamethazine and erythromycin were degraded in soils, with a larger fraction mineralized in the long-term exposed soil (20 and 65%, respectively) than in control soil (0.4 and 3%, respectively) after 7 days of incubation. In contrast, ciprofloxacin was not mineralized neither in control nor long-term exposed soils. The mineralized fractions were similar for antibiotics added directly to soil or carried in dairy manure.

One of the most common complications during pregnancy is gestational diabetes mellitus (GDM), hyperglycemia that occurs for the first time during pregnancy. The condition is multifactorial, caused by an interaction between genetic, epigenetic, and environmental factors. However, the underlying mechanisms responsible for its pathogenesis remain elusive. Moreover, in contrast to several common metabolic disorders, molecular research in GDM is lagging. It is important to recognize that GDM is still commonly diagnosed during the second trimester of pregnancy using the oral glucose tolerance test (OGGT), at a time when both a fetal and maternal pathophysiology is already present, demonstrating the increased blood glucose levels associated with exacerbated insulin resistance. Therefore, early detection of metabolic changes and associated epigenetic and genetic factors that can lead to an improved prediction of adverse pregnancy outcomes and future cardio-metabolic pathologies in GDM women and their children is imperative. Several genomic and epigenetic approaches have been used to identify the genes, genetic variants, metabolic pathways, and epigenetic modifications involved in GDM to determine its etiology. In this article, we explore these factors as well as how their functional effects may contribute to immediate and future pathologies in women with GDM and their offspring from birth to adulthood. We also discuss how these approaches contribute to the changes in different molecular pathways that contribute to the GDM pathogenesis, with a special focus on the development of insulin resistance.

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