Appreciative inquiry in medical education*

The practice of medicine, and also medical education, typically adopts a problem-solving approach to identify "what is going wrong" with a situation. However, an alternative is Appreciative Inquiry (AI), which adopts a positive and strengths-based approach to identify "what is going well" with a situation. The AI approach can be used for the development and enhancement of the potential of both individuals and organizations. An essential aspect of the AI approach is the generative process, in which a new situation is envisioned and both individual and collective strengths are mobilized to make changes to achieve the valued future situation. The AI approach has been widely used in the world of business and general education, but is has an exciting potential for medical education, including curriculum development, faculty development, supporting learners through academic advising and mentoring, but also for enhancing the teaching and learning of both individuals and groups. This AMEE Guide describes the core principles of AI and their practical application in medical education

Super-Resolution Fluorescence Optical Microscopy: Targeted and Stochastic Read-Out Approaches

This chapter is dedicated to a general overview of some of the emerging and well-established super-resolution techniques recently developed and known as optical nanoscopy and localization precision method. Due to the way of probing the sample, one can consider them as targeted and stochastic-based techniques, respectively. Here, we stress how super-resolution is obtained without violating any physical law, i.e., diffraction. The strong idea behind such approaches, operating in fluorescence contrast mode, is related to the ability of controlling the states, bright/dark or red/blue, of the fluorescent labels being used in order to circumvent the diffraction barrier. Super-resolution is achieved by precluding simultaneous emission of spectrally identical emission of adjacent (50 micron thickness) samples is discussed along with correlative microscopy approaches involving scanning probe methods. Examples are given within the neuroscience framework