Use of Mobile Learning by Resident Physicians in Botswana

With the growth of mobile health in recent years, learning through the use of mobile devices (mobile learning [mLearning]) has gained recognition as a potential method for increasing healthcare providers\u27 access to medical information and resources in resource-limited settings. In partnership with the University of Botswana School of Medicine (SOM), we have been exploring the role of smartphone-based mLearning with resident (physicians in specialty training) education. The SOM, which admitted its first class of medical students and residents in 2009, is committed to providing high-level on-site educational resources for resident physicians, even when practicing in remote locations. Seven residents were trained to use an Android-based myTouch 3G smartphone equipped with data-enabled subscriber identity module (SIM) cards and built-in camera. Phones contained locally loaded point-of-care and drug information applications, a telemedicine application that allows for the submission of cases to local mentors, and e-mail/Web access. Surveys were administered at 4 weeks and 8 weeks following distribution of phones. We found that smartphones loaded with point-of-care tools are effectively utilized by resident physicians in resource-limited settings, both for accessing point-of-care medical information at the bedside and engaging in self-directed learning at home

Prediction of Associations between microRNAs and Gene Expression in Glioma Biology

Despite progress in the determination of miR interactions, their regulatory role in cancer is only beginning to be unraveled. Utilizing gene expression data from 27 glioblastoma samples we found that the mere knowledge of physical interactions between specific mRNAs and miRs can be used to determine associated regulatory interactions, allowing us to identify 626 associated interactions, involving 128 miRs that putatively modulate the expression of 246 mRNAs. Experimentally determining the expression of miRs, we found an over-representation of over(under)-expressed miRs with various predicted mRNA target sequences. Such significantly associated miRs that putatively bind over-expressed genes strongly tend to have binding sites nearby the 3′UTR of the corresponding mRNAs, suggesting that the presence of the miRs near the translation stop site may be a factor in their regulatory ability. Our analysis predicted a significant association between miR-128 and the protein kinase WEE1, which we subsequently validated experimentally by showing that the over-expression of the naturally under-expressed miR-128 in glioma cells resulted in the inhibition of WEE1 in glioblastoma cells

MACVIA Clinical Decision Algorithm in Allergic Rhinitis in adolescents and adults

International audienceThe selection of pharmacotherapy for patients with allergic rhinitis depends on several factors, including age, prominent symptoms, symptom severity, control of allergic rhinitis, patient preferences and cost. Allergen exposure and resulting symptoms vary and treatment adjustment is required. Clinical decision support systems (CDSS) may be beneficial for the assessment of disease control. Clinical decision support systems should be based on the best evidence and algorithms to aid patients and health care professionals to jointly determine the treatment and its step-up or step-down strategy depending on AR control. MACVIA-LR (Fighting chronic diseases for active and healthy ageing) one of the reference sites of the European Innovation Partnership on Active and Healthy Ageing, has initiated an allergy sentinel network (MASK: MACVIA-ARIA Sentinel networK). A clinical decision support system is currently being developed to optimize allergic rhinitis control. An algorithm developed by consensus is presented in this paper. This algorithm should be confirmed by appropriate trials