Background This study reviewed Twitter status updates mentioning “antibiotic(s)” to determine overarching categories and explore evidence of misunderstanding or misuse of antibiotics. Methods One thousand Twitter status updates mentioning antibiotic(s) were randomly selected for content analysis and categorization. To explore cases of potential misunderstanding or misuse, these status updates were mined for co-occurrence of the following terms: “cold + antibiotic(s),” “extra antibiotic(s),” “flu + antibiotic(s),” “leftover antibiotic(s),” and “share antibiotic(s)” and reviewed to confirm evidence of misuse or misunderstanding. Results Of the 1,000 status updates, 971 were categorized into 11 groups: General Use (n=289), Advice/Information (n=157), Side Effects/Negative Reactions (n=113), Diagnosis (n=102), Resistance (n=92), Misunderstanding and/or Misuse (n=55), Positive Reactions (n=48), Animals (n=46), Other (n=42), Wanting/Needing (n=19), and Cost (n=8). Cases of misunderstanding or abuse were identified for the following combinations: “flu + antibiotic(s)” (n=345), “cold + antibiotic(s)” (n=302), “leftover antibiotic(s)” (n=23), “share antibiotic(s)” (n=10), and “extra antibiotic(s)” (n=7). Conclusions Social media sites offer means of health information sharing. Further study is warranted to explore how such networks may provide a venue to identify misuse or misunderstanding of antibiotics, promote positive behavior change, disseminate valid information, and explore how such tools can be used to gather real-time health data.

Infection with the malaria parasite Plasmodium falciparum leads to widely different clinical conditions in children, ranging from mild flu-like symptoms to coma and death. Despite the immense medical implications, the genetic and molecular basis of this diversity remains largely unknown. Studies of in vitro gene expression have found few transcriptional differences between different parasite strains. Here we present a large study of in vivo expression profiles of parasites derived directly from blood samples from infected patients. The in vivo expression profiles define three distinct transcriptional states. The biological basis of these states can be interpreted by comparison with an extensive compendium of expression data in the yeast Saccharomyces cerevisiae. The three states in vivo closely resemble, first, active growth based on glycolytic metabolism, second, a starvation response accompanied by metabolism of alternative carbon sources, and third, an environmental stress response. The glycolytic state is highly similar to the known profile of the ring stage in vitro, but the other states have not been observed in vitro. The results reveal a previously unknown physiological diversity in the in vivo biology of the malaria parasite, in particular evidence for a functional mitochondrion in the asexual-stage parasite, and indicate in vivo and in vitro studies to determine how this variation may affect disease manifestations and treatment.

Gene expression analysis has identified biologically relevant subclasses of breast cancer. However, most classification schemes do not robustly cluster all HER2+ breast cancers, in part due to limitations and bias of clustering techniques used. In this article, we propose an alternative approach that first separates the HER2+ tumors using a gene amplification signal for Her2/neu amplicon genes and then applies consensus ensemble clustering separately to the HER2+ and HER2À clusters to look for further substructure. We applied this procedure to a microarray data set of 286 early-stage breast cancers treated only with surgery and radiation and identified two basal and four luminal subtypes in the HER2À tumors, as well as two novel and robust HER2+ subtypes. HER2+ subtypes had median distant metastasis-free survival of 99 months [95% confidence interval (95% CI), 83-118 months] and 33 months (95% CI, 11-54 months), respectively, and recurrence rates of 11% and 58%, respectively. The low recurrence subtype had a strong relative overexpression of lymphocyte-associated genes and was also associated with a prominent lymphocytic infiltration on histologic analysis. These data suggest that early-stage HER2+ cancers associated with lymphocytic infiltration are a biologically distinct subtype with an improved natural history. [Cancer Res 2007;67(22):10669-76]