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We have previously identified the PKC (protein kinase C)-anchoring protein RACK1 (receptor for activated C-kinase 1), as a specific binding partner for the cAMP-specific phosphodiesterase PDE4D5, suggesting a potential site for cross-talk between the PKC and cAMP signalling pathways. In the present study we found that elevation of intracellular cAMP, with the β2-adrenoceptor agonist isoproterenol (isoprenaline), led to activation of PDE4 enzymes in the particulate and soluble fractions of HEK (human embryonic kidney)-293 cells. In contrast activation of PDE4D5, with isoproterenol and the PKC activator PMA, was restricted to the particulate fraction, where it interacts with RACK1; however, RACK1 is dispensable for anchoring PDE4D5 to the particulate fraction. Kinetic studies demonstrated that RACK1 alters the conformation of particulate-associated PDE4D5 so that it more readily interacts with its substrate cAMP and with rolipram, a PDE4 inhibitor that specifically targets the active site of the enzyme. Interaction with RACK1 was also essential for PKC-dependent and ERK (extracellular-signal-regulated kinase)-independent phosphorylation (on Ser126), and activation of PDE4D5 in response to PMA and isoproterenol, both of which trigger the recruitment of PKCα to RACK1. Together these results reveal novel signalling cross-talk, whereby RACK1 mediates PKC-dependent activation of PDE4D5 in the particulate fraction of HEK-293 cells in response to elevations in intracellular cAMP.

Klinefelter's syndrome, the most common sex disorder associated with chromosomal aberrations, is characterized by a plethora of clinical features. Parameters for diagnosis of the syndrome are constantly expanding as new anatomical and hormonal abnormalities are noted, yet Klinefelter's remains underdiagnosed and underreported. This review outlines the key anatomical characteristics associated with the syndrome, which are currently used for clinical diagnosis, or may provide means for improving diagnosis in the future. Clin. Anat. 29:606-619, 2016. © 2016 Wiley Periodicals, Inc.

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In large class settings, individualized student–teacher interaction is difficult. However, teaching interactions (e.g., formative feedback) are central to encouraging deep approaches to learning. While there has been progress in automatic short‐answer grading, analysing student responses to support formative feedback at scale is arguably some way from being widely applied in practice. However, analysing student written responses can provide insights into student conceptions, thus directly informing teacher actions. Indeed, we argue that analysing student responses to provide feedback directly to teachers is as worthy a goal as providing individualized feedback to students and is achievable given the current state‐of‐the‐art in natural language processing. In this paper, we analyse student written responses to short‐answer questions posed in the context of a large first year health sciences course. Each question was designed to elicit deep responses. Our qualitative analysis illustrates the variability in student responses and reveals multiple relationships between these responses, course materials and the questions posed. Such information can be invaluable for teacher praxis. We conclude with a conceptual ‘dashboard’ that categorizes student responses and reveals relationships between responses, course resources and the questions. Such a dashboard could provide timely, actionable insights for teachers and help foster deep learning approaches for students.