Anki Flashcards for Radiology Education.

From online textbooks to educational social media posts, digital learning tools are transforming medical education. Spaced repetition programs are a popular tool, with 70% of first-year medical students reporting using the free, open-source flashcard application Anki.1 The Anki program pairs active recall and spaced repetition learning principles with a simple but versatile user interface.2 Spaced repetition flashcard programs such as Anki are uniquely suited to radiology education because they strengthen image-based recall, a necessary skill for radiology trainees to develop. In this review, we will describe the science behind active recall and spaced repetition programs, introduce the Anki platform, and describe future directions for its potential as an educational resource for radiology.

Multiomics profiling of paired primary and recurrent glioblastoma patient tissues.

BACKGROUND: Despite maximal therapy with surgery, chemotherapy, and radiotherapy, glioblastoma (GBM) patients have a median survival of only 15 months. Almost all patients inevitably experience symptomatic tumor recurrence. A hallmark of this tumor type is the large heterogeneity between patients and within tumors itself which relates to the failure of standardized tumor treatment. In this study, tissue samples of paired primary and recurrent GBM tumors were investigated to identify individual factors related to tumor progression. METHODS: Paired primary and recurrent GBM tumor tissues from 8 patients were investigated with a multiomics approach using transcriptomics, proteomics, and phosphoproteomics. RESULTS: In the studied patient cohort, large variations between and within patients are observed for all omics analyses. A few pathways affected at the different omics levels partly overlapped if patients are analyzed at the individual level, such as synaptogenesis (containing the SNARE complex) and cholesterol metabolism. Phosphoproteomics revealed increased STMN1(S38) phosphorylation as part of ERBB4 signaling. A pathway tool has been developed to visualize and compare different omics datasets per patient and showed potential therapeutic drugs, such as abobotulinumtoxinA (synaptogenesis) and afatinib (ERBB4 signaling). Afatinib is currently in clinical trials for GBM. CONCLUSIONS: A large variation on all omics levels exists between and within GBM patients. Therefore, it will be rather unlikely to find a drug treatment that would fit all patients. Instead, a multiomics approach offers the potential to identify affected pathways on the individual patient level and select treatment options.

Epac1 inhibition ameliorates pathological angiogenesis through coordinated activation of Notch and suppression of VEGF signaling.

In this study, we investigated the roles of Epac1 in pathological angiogenesis and its potential as a novel therapeutic target for the treatment of vasoproliferative diseases. Genetic deletion of Epac1 ameliorated pathological angiogenesis in mouse models of oxygen-induced retinopathy (OIR) and carotid artery ligation. Moreover, genetic deletion or pharmacological inhibition of Epac1 suppressed microvessel sprouting from ex vivo aortic ring explants. Mechanistic studies revealed that Epac1 acted as a previously unidentified inhibitor of the γ-secretase/Notch signaling pathway via interacting with γ-secretase and regulating its intracellular trafficking while enhancing vascular endothelial growth factor signaling to promote pathological angiogenesis. Pharmacological administration of an Epac-specific inhibitor suppressed OIR-induced neovascularization in wild-type mice, recapitulating the phenotype of genetic Epac1 knockout. Our results demonstrate that Epac1 signaling is critical for the progression of pathological angiogenesis but not for physiological angiogenesis and that the newly developed Epac-specific inhibitors are effective in combating proliferative retinopathy.

"What Will I Experience in My College STEM Courses?" An Investigation of Student Predictions about Instructional Practices in Introductory Courses.

The instructional practices used in introductory college courses often differ dramatically from those used in high school courses, and dissatisfaction with these practices is cited by students as a prominent reason for leaving science, technology, engineering, and mathematics (STEM) majors. To better characterize the transition to college course work, we investigated the extent to which incoming expectations of course activities differ based on student demographic characteristics, as well as how these expectations align with what students will experience. We surveyed more than 1500 undergraduate students in large introductory STEM courses at three research-intensive institutions during the first week of classes about their expectations regarding how class time would be spent in their courses. We found that first-generation and first-semester students predict less lecture than their peers and that class size had the largest effect on student predictions. We also collected classroom observation data from the courses and found that students generally underpredicted the amount of lecture observed in class. This misalignment between student predictions and experiences, especially for first-generation and first-semester college students and students enrolled in large- and medium-size classes, has implications for instructors and universities as they design curricula for introductory STEM courses with explicit retention goals.