Gonadotrophin‐releasing hormone (GnRH) neurone function is dependent upon gonadal steroid hormone feedback, which is communicated in large part through an afferent neuronal network. The classical neurotransmitters GABA and glutamate are important regulators of GnRH neurone activity and are implicated in mediating feedback signals. In the present study, we aimed to determine whether GABAergic or glutamatergic input to GnRH neurones differs between males and females and/or exhibits morphological plasticity in response to steroid hormone feedback in females. Tissue collected from GnRH‐green fluorescent protein (GFP) male and female mice in dioestrus underwent immunofluorescence labelling of GFP and either the vesicular GABA transporter (VGAT) or the vesicular glutamate transporter 2 (VGLUT2). No differences in the densities or absolute numbers of VGAT‐immunoreactive (‐IR) or VGLUT2‐IR puncta apposed to GnRH neurones were identified between males and females. The most significant input from either neurotransmitter was to the proximal dendritic region and 80% of VGAT‐IR puncta apposed to GnRH neurones co‐localised with synaptophysin. Putative inputs were also assessed in ovariectomised (OVX) female mice treated with negative (OVX+E) or positive (OVX+E+E) feedback levels of oestrogen, and OVX+E+E mice were killed during the expected GnRH/luteinising hormone surge. No differences in VGLUT2‐IR contacts to GnRH neurones were identified between animals under the negative‐feedback influence of oestrogen (OVX+E) or the positive influence of oestrogen (OVX+E+E), regardless of cFos activation status. By contrast, a significant elevation in putative GABAergic inputs to GnRH neurones at the time of the preovulatory surge was found in the cFos‐negative subset of GnRH neurones, both at the level of the soma and at the proximal dendrite. Taken together, these data suggest that, although GABAergic and glutamatergic innervation of GnRH neurones is not sexually differentiated, cyclic fluctuations in steroid hormone feedback over the female oestrous cycle result in plastic changes in GABAergic inputs to a subpopulation of GnRH neurones.

During embryonic development, gonadotrophin-releasing hormone (GnRH) neurones make an extraordinary migration out of the nose and into the brain where, in adulthood, they drive the pituitary regulation of gonadal function and fertility. Primary cilia are antennae-like, immotile organelles that project from the surface of nearly all cells, including GnRH neurones. Links between defects in primary cilia and a variety of human pathologies have been discovered that suggest a role for primary cilia in embryogenesis and reproductive function. The present study aimed to investigate whether GnRH neurone primary cilia are critical for their embryonic migration and the adult control of fertility. To achieve this, we used a Cre-loxP strategy to selectively disrupt primary cilia by deleting Kif3a, an intraflagellar transport protein family member essential for primary cilia assembly and function, specifically in GnRH neurones. Confocal analysis revealed that, in Kif3a(fl/fl) (WT-Kif3a) controls, all GnRH neurones possessed primary cilia, whereas, in GnRH-Cre(+/-) ;Kif3a(fl/fl) (GnRH-Kif3aKO) mice, 60% of GnRH neurones lacked any evidence of primary cilia and the remaining 40% possessed only stunted primary cilia (< 2 μm). Despite abolishing normal primary cilia assembly in GnRH neurones from embryogenesis, adult GnRH neurone distribution and reproductive function was remarkably normal. The total number of GnRH neurones was the same in GnRH-Kif3aKO and WT-Kif3a controls; however, a significant increase (25%) was identified in the number of GnRH neurones sampled through the midpoint of the rostral pre-optic area in GnRH-Kif3aKO mice (P < 0.05). The time to vaginal opening was not different in GnRH-Kif3aKO mice, although they displayed significantly advanced first oestrus (P < 0.05), and oestrous cycle length was increased (P < 0.05). However, females displayed normal basal levels of luteinising hormone, responded normally to oestrogen-induced negative- and positive-feedback, and displayed normal fecundity. Taken together, these data suggest that primary cilia and associated signal transduction pathways play a role in the topographical distribution and specific functions of GnRH neurones; however, they are not essential for fertility.

Background To realize the potential for mobile learning in clinical skills acquisition, medical students and their teachers should be able to evaluate the value of an app to support student learning of clinical skills. To our knowledge, there is currently no rubric for evaluation of quality or value that is specific for apps to support medical student learning. Such a rubric might assist students to be more confident in using apps to support their learning. Objective The objective of this study was to develop an instrument that can be used by health professional educators to rate the value of a mobile app to support health professional student learning. Methods Using the literature, we developed a list of potential criteria for the evaluation of educational app value, which were then refined with a student group using a modified nominal group technique. The refined list was organized into themes, and the initial rubric, Mobile App Rubric for Learning (MARuL, version 1), was developed. iOS and Android app stores were searched for clinical skills apps that met our inclusion criteria. After the 2 reviewers were trained and the item descriptions were refined (version 2), a random sample of 10 included apps, 5 for each mobile operating system, was reviewed. Interitem and interrater analyses and discussions with the reviewers resulted in refinement of MARuL to version 3. The reviewers completed a review of 41 clinical skills mobile apps, and a second round of interitem and interrater reliability testing was performed, leading to version 4 of the MARuL. Results Students identified 28 items (from an initial set of 144 possible items) during the nominal group phase, and these were then grouped into 4 themes: teaching and learning, user centered, professional, and usability. Testing and refinement with reviewers reduced the list to 26 items. Internal consistency for MARuL was excellent (α=.96), and the interrater reliability as measured by the intraclass correlation coefficient (ICC) was good (ICC=0.66). Conclusions MARuL offers a fast and user-friendly method for teachers to select valuable apps to enhance student learning.

Children can reliably indicate where they hurt after laparoscopic surgery. An electronic version could increase acceptability to children and usability by professionals.

Background Mobile apps are widely used in health professions, which increases the need for simple methods to determine the quality of apps. In particular, teachers need the ability to curate high-quality mobile apps for student learning. Objective This study aims to systematically search for and evaluate the quality of clinical skills mobile apps as learning tools. The quality of apps meeting the specified criteria was evaluated using two measures—the widely used Mobile App Rating Scale (MARS), which measures general app quality, and the Mobile App Rubric for Learning (MARuL), a recently developed instrument that measures the value of apps for student learning—to assess whether MARuL is more effective than MARS in identifying high-quality apps for learning. Methods Two mobile app stores were systematically searched using clinical skills terms commonly found in medical education and apps meeting the criteria identified using an approach based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A total of 9 apps were identified during the screening process. The apps were rated independently by 2 reviewers using MARS and MARuL. Results The intraclass correlation coefficients (ICCs) for the 2 raters using MARS and MARuL were the same (MARS ICC [two-way]=0.68; P<.001 and MARuL ICC [two-way]=0.68; P<.001). Of the 9 apps, Geeky Medics-OSCE revision (MARS Android=3.74; MARS iOS=3.68; MARuL Android=75; and MARuL iOS=73) and OSCE PASS: Medical Revision (MARS Android=3.79; MARS iOS=3.71; MARuL Android=69; and MARuL iOS=73) scored highly on both measures of app quality and for both Android and iOS. Both measures also showed agreement for the lowest rated app, Patient Education Institute (MARS Android=2.21; MARS iOS=2.11; MARuL Android=18; and MARuL iOS=21.5), which had the lowest scores in all categories except information (MARS) and professional (MARuL) in both operating systems. MARS and MARuL were both able to differentiate between the highest and lowest quality apps; however, MARuL was better able to differentiate apps based on teaching and learning quality. Conclusions This systematic search and rating of clinical skills apps for learning found that the quality of apps was highly variable. However, 2 apps—Geeky Medics-OSCE revision and OSCE PASS: Medical Revision—rated highly for both versions and with both quality measures. MARS and MARuL showed similar abilities to differentiate the quality of the 9 apps. However, MARuL’s incorporation of teaching and learning elements as part of a multidimensional measure of quality may make it more appropriate for use with apps focused on teaching and learning, whereas MARS’s more general rating of quality may be more appropriate for health apps targeting a general health audience. Ratings of the 9 apps by both measures also highlighted the variable quality of clinical skills mobile apps for learning.

BACKGROUND Mobile apps are widely used in health professions, which increases the need for simple methods to determine the quality of apps. In particular, teachers need the ability to curate high-quality mobile apps for student learning. OBJECTIVE This study aims to systematically search for and evaluate the quality of clinical skills mobile apps as learning tools. The quality of apps meeting the specified criteria was evaluated using two measures—the widely used Mobile App Rating Scale (MARS), which measures general app quality, and the Mobile App Rubric for Learning (MARuL), a recently developed instrument that measures the value of apps for student learning—to assess whether MARuL is more effective than MARS in identifying high-quality apps for learning. METHODS Two mobile app stores were systematically searched using clinical skills terms commonly found in medical education and apps meeting the criteria identified using an approach based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A total of 9 apps were identified during the screening process. The apps were rated independently by 2 reviewers using MARS and MARuL. RESULTS The intraclass correlation coefficients (ICCs) for the 2 raters using MARS and MARuL were the same (MARS ICC [two-way]=0.68; <i>P</i>&lt;.001 and MARuL ICC [two-way]=0.68; <i>P</i>&lt;.001). Of the 9 apps, Geeky Medics-OSCE revision (MARS Android=3.74; MARS iOS=3.68; MARuL Android=75; and MARuL iOS=73) and OSCE PASS: Medical Revision (MARS Android=3.79; MARS iOS=3.71; MARuL Android=69; and MARuL iOS=73) scored highly on both measures of app quality and for both Android and iOS. Both measures also showed agreement for the lowest rated app, Patient Education Institute (MARS Android=2.21; MARS iOS=2.11; MARuL Android=18; and MARuL iOS=21.5), which had the lowest scores in all categories except information (MARS) and professional (MARuL) in both operating systems. MARS and MARuL were both able to differentiate between the highest and lowest quality apps; however, MARuL was better able to differentiate apps based on teaching and learning quality. CONCLUSIONS This systematic search and rating of clinical skills apps for learning found that the quality of apps was highly variable. However, 2 apps—Geeky Medics-OSCE revision and OSCE PASS: Medical Revision—rated highly for both versions and with both quality measures. MARS and MARuL showed similar abilities to differentiate the quality of the 9 apps. However, MARuL’s incorporation of teaching and learning elements as part of a multidimensional measure of quality may make it more appropriate for use with apps focused on teaching and learning, whereas MARS’s more general rating of quality may be more appropriate for health apps targeting a general health audience. Ratings of the 9 apps by both measures also highlighted the variable quality of clinical skills mobile apps for learning. CLINICALTRIAL

During the 2020 COVID‐19 lockdown our rheumatology service provided follow up by phone. We reviewed clinic documents to compare patients serviced, and patient assessment and treatment outcomes. More patients received care during the lockdown but patient rheumatic disease was deemed active less frequently, more patients had no change to disease‐modifying anti‐rheumatic drugs and patients were less likely to have an intervention arranged. This suggests careful patient selection and appropriate infrastructure should be part of future rheumatology telemedicine.

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