Tissue factor as a novel diagnostic target for early detection of ovarian cancer using ultrasound microbubbles.

INTRODUCTION: Ovarian cancer (OC) is the deadliest gynecologic malignancy, with an overall 5-year survival rate of less than 30%. The existing paradigm for OC detection involves a serum marker, CA125, and ultrasound examination, neither of which is sufficiently specific for OC. This study addresses this deficiency through the use of a targeted ultrasound microbubble directed against tissue factor (TF). METHODS: TF expression was examined in both OC cell lines and patient-derived tumor samples via western blotting and IHC. In vivo microbubble ultrasound imaging was analyzed using high grade serous ovarian carcinoma orthotopic mouse models. RESULTS: While TF expression has previously been described on angiogenic, tumor-associated vascular endothelial cells (VECs) of several tumor types, this is first study to show TF expression on both murine and patient-derived ovarian tumor-associated VECs. Biotinylated anti-TF antibody was conjugated to streptavidin-coated microbubbles and in vitro binding assays were performed to assess the binding efficacy of these agents. TF-targeted microbubbles successfully bound to TF-expressing OC cells, as well as an in vitro model of angiogenic endothelium. In vivo, these microbubbles bound to the tumor-associated VECs of a clinically relevant orthotopic OC mouse model. CONCLUSION: Development of a TF-targeted microbubble capable of successfully detecting ovarian tumor neovasculature could have significant implications towards increasing the number of early-stage OC diagnoses. This preclinical study shows potential for translation to clinical use, which could ultimately help increase the number of early OC detections and decrease the mortality associated with this disease.

Development and assessment of an integrated anatomy mobile app.

Curricular hours for anatomical sub-disciplines (gross anatomy, embryology, histology, and neuroanatomy) continue to decline, while medical schools are simultaneously transitioning to systems-based, vertically integrated curricula. This requires students to learn and integrate all basic science content for a learning block prior to the summative assessment. Currently, no educational technology resource exists that integrates the four anatomical sub-disciplines into a single resource to supplement integrated curricula. The objective of this study was to assess a novel integrated anatomical sciences mobile app for medical students. The 4natomy mobile app was developed to integrate the four sub-disciplines for a single topic, the spinal cord. The app was distributed to first-year medical students during the neurological disorders learning. Following the learning block, assessment of the student acceptance and experience with the app was conducted through a technology acceptance model (TAM) framework survey. The results indicated that students found the app to be useful (p < 0.001) and easy to use (p < 0.05), predicting continued future usage of the app. Students requested expanded anatomy content for the entire learning block, as well as more clinical correlations, videos, and animations. The integrated anatomy mobile app developed in this study was useful and easy to use, indicating continued use within an integrated medical curriculum. This was the first study to utilize the TAM as a conceptual framework for technology assessment in medical education, suggesting that future studies that develop new technologies should adapt the TAM for user testing.

What type of learner are your students? Preferred learning styles of undergraduate gross anatomy students according to the index of learning styles questionnaire.

Students learn and process information in many different ways. Learning styles are useful as they allow instructors to learn more about students, as well as aid in the development and application of useful teaching approaches and techniques. At the undergraduate level there is a noticeable lack of research on learning style preferences of students enrolled in gross anatomy courses. The Index of Learning Styles (ILS) questionnaire was administered to students enrolled in a large enrollment undergraduate gross anatomy course with laboratory to determine their preferred learning styles. The predominant preferred learning styles of the students (n = 505) enrolled in the gross anatomy course were active (54.9%), sensing (85.1%), visual (81.2%), and sequential (74.4%). Preferred learning styles profiles of particular majors enrolled in the course were also constructed; analyses showed minor variation in the active/reflective dimension. An understanding of students' preferred learning styles can guide course design but it should not be implemented in isolation. It can be strengthened (or weakened) by concurrent use of other tools (e.g., flipped classroom course design). Based on the preferred learning styles of the majority of undergraduate students in this particular gross anatomy course, course activities can be hands on (i.e., active), grounded in concrete information (i.e., sensing), utilize visual representation such as images, figures, models, etc. (i.e., visual), and move in small incremental steps that build on each topic (i.e., sequential). Anat Sci Educ 11: 358-365. © 2017 American Association of Anatomists.