BackgroundAs internet and social media use have skyrocketed, epidemiologists have begun to use online data such as Google query data and Twitter trends to track the activity levels of influenza and other infectious diseases. In China, Weibo is an extremely popular microblogging site that is equivalent to Twitter. Capitalizing on the wealth of public opinion data contained in posts on Weibo, this study used Weibo as a measure of the Chinese people’s reactions to two different outbreaks: the 2012 Middle East Respiratory Syndrome Coronavirus (MERS-CoV) outbreak, and the 2013 outbreak of human infection of avian influenza A(H7N9) in China.MethodsKeyword searches were performed in Weibo data collected by The University of Hong Kong’s Weiboscope project. Baseline values were determined for each keyword and reaction values per million posts in the days after outbreak information was released to the public.ResultsThe results show that the Chinese people reacted significantly to both outbreaks online, where their social media reaction was two orders of magnitude stronger to the H7N9 influenza outbreak that happened in China than the MERS-CoV outbreak that was far away from China.ConclusionsThese results demonstrate that social media could be a useful measure of public awareness and reaction to disease outbreak information released by health authorities.

Developing tools for efficiently measuring cognitive change specifically and brain health generally—whether for clinical use or as endpoints in clinical trials—is a major challenge, particularly for conditions such as Alzheimer's disease. Technology such as connected devices and advances in artificial intelligence offer the possibility of creating and deploying clinical-grade tools with high sensitivity, rapidly, cheaply, and non-intrusively. Starting from a widely-used paper and pencil cognitive status test—The Clock Drawing Test—we combined a digital input device to capture time-stamped drawing coordinates with a machine learning analysis of drawing behavior to create DCTclock™, an automated analysis of nuances in cognitive performance beyond successful task completion. Development and validation was conducted on a dataset of 1,833 presumed cognitively unimpaired and clinically diagnosed cognitively impaired individuals with varied neurological conditions. We benchmarked DCTclock against existing clock scoring systems and the Mini-Mental Status Examination, a widely-used but lengthier cognitive test, and showed that DCTclock offered a significant improvement in the detection of early cognitive impairment and the ability to characterize individuals along the Alzheimer's disease trajectory. This offers an example of a robust framework for creating digital biomarkers that can be used clinically and in research for assessing neurological function.

This study aimed to identify what information triggered social media users’ responses regarding infectious diseases. Chinese microblogs in 2012 regarding 42 infectious diseases were obtained through a keyword search in the Weiboscope database. Qualitative content analysis was performed for the posts pertinent to each keyword of the day of the year with the highest daily count. Similar posts were grouped and coded. We identified five categories of information that increased microblog traffic pertaining to infectious diseases: news of an outbreak or a case; health education / information; alternative health information / Traditional Chinese Medicine; commercial advertisement / entertainment; and social issues. News unrelated to the specified infectious diseases also led to elevated microblog traffic. Our study showcases the diverse contexts from which increased social media traffic occur. Our results will facilitate better health communication as causes underlying increased social media traffic are revealed.

Adjuvant pelvic radiation is associated with improved survival and decreased recurrence in this population of patients with penile cancer with positive PLNs.

Although the BRAF inhibitors dabrafenib and vemurafenib have both proven successful against BRAF‐mutant melanoma, there seem to be differences in their mechanisms of action. Here, we show that dabrafenib is more effective at inhibiting the growth of NRAS‐mutant and KRAS‐mutant cancer cell lines than vemurafenib. Using mass spectrometry‐based chemical proteomics, we identified NEK9 and CDK16 as unique targets of dabrafenib. Both NEK9 and CDK16 were highly expressed in specimens of advanced melanoma, with high expression of both proteins correlating with a worse overall survival. A role for NEK9 in the growth of NRAS‐ and KRAS‐mutant cell lines was suggested by siRNA studies in which silencing was associated with decreased proliferation, cell cycle arrest associated with increased p21 expression, inhibition of phospho‐CHK1, decreased CDK4 expression, and the initiation of a senescence response. Inhibition of CDK4 but not CHK1 recapitulated the effects of NEK9 silencing, indicating this to be the likely mechanism of growth inhibition. We next turned our attention to CDK16 and found that its knockdown inhibited the phosphorylation of the Rb protein at S780 and increased expression of p27. Both of these effects were phenocopied in NRAS‐ and KRAS‐mutant cancer cells by dabrafenib, but not vemurafenib. Combined silencing of NEK9 and CDK16 was associated with enhanced inhibition of melanoma cell proliferation. In summary, we have identified dabrafenib as a potent inhibitor of NEK9 and CDK16, and our studies suggest that inhibition of these kinases may have activity against cancers that do not harbor BRAF mutations.