Characterizing the Discussion of Antibiotics in the Twittersphere: What is the Bigger Picture?

Background

User content posted through Twitter has been used for biosurveillance, to characterize public perception of health-related topics, and as a means of distributing information to the general public. Most of the existing work surrounding Twitter and health care has shown Twitter to be an effective medium for these problems but more could be done to provide finer and more efficient access to all pertinent data. Given the diversity of user-generated content, small samples or summary presentations of the data arguably omit a large part of the virtual discussion taking place in the Twittersphere. Still, managing, processing, and querying large amounts of Twitter data is not a trivial task. This work describes tools and techniques capable of handling larger sets of Twitter data and demonstrates their use with the issue of antibiotics.

Objective

This work has two principle objectives: (1) to provide an open-source means to efficiently explore all collected tweets and query health-related topics on Twitter, specifically, questions such as what users are saying and how messages are spread, and (2) to characterize the larger discourse taking place on Twitter with respect to antibiotics.

Methods

Open-source software suites Hadoop, Flume, and Hive were used to collect and query a large number of Twitter posts. To classify tweets by topic, a deep network classifier was trained using a limited number of manually classified tweets. The particular machine learning approach used also allowed the use of a large number of unclassified tweets to increase performance.

Results

Query-based analysis of the collected tweets revealed that a large number of users contributed to the online discussion and that a frequent topic mentioned was resistance. A number of prominent events related to antibiotics led to a number of spikes in activity but these were short in duration. The category-based classifier developed was able to correctly classify 70% of manually labeled tweets (using a 10-fold cross validation procedure and 9 classes). The classifier also performed well when evaluated on a per category basis.

Conclusions

Using existing tools such as Hive, Flume, Hadoop, and machine learning techniques, it is possible to construct tools and workflows to collect and query large amounts of Twitter data to characterize the larger discussion taking place on Twitter with respect to a particular health-related topic. Furthermore, using newer machine learning techniques and a limited number of manually labeled tweets, an entire body of collected tweets can be classified to indicate what topics are driving the virtual, online discussion. The resulting classifier can also be used to efficiently explore collected tweets by category and search for messages of interest or exemplary content.     

Children's Parasympathetic Reactivity to Specific Emotions Moderates Response to Intervention for Early-Onset Aggression

Following theories that individual differences in respiratory sinus arrhythmia (RSA) denote differential sensitivity to environmental influences, this study examines whether differences in RSA reactivity to specific emotional challenges predict differential response to intervention. We present data from a randomized clinical trial of a targeted intervention for early onset aggression. In collaboration with a high-risk urban school district, 207 kindergarten children (73% African American, 66% male), identified by their teachers as having high levels of aggressive and disruptive behavior, were recruited. All children received a universal social-emotional curriculum. One hundred children were randomly assigned to an additional intervention consisting of weekly peer-based social skills training. Complete RSA data were available for 139 of the children. Teacher-reported externalizing symptoms and emotion regulation in 1st grade (post intervention) were examined controlling for baseline levels. First-grade peer nominations of aggressive behavior, controlling for baseline nominations, were also examined as outcomes. No effect of resting RSA was found. However, greater reactivity to anger was associated with higher externalizing symptoms and lower emotion regulation skills in 1st grade relative to low reactive children. Lower reactivity to fear was associated with greater improvement over time, an effect that was enhanced in the targeted intervention condition. Results suggest that measures of affective reactivity may provide insight into children's capacity to benefit from different types of interventions.     

The Noscapine Chronicle: A Pharmaco‐Historic Biography of the Opiate Alkaloid Family and its Clinical Applications

Given its manifold potential therapeutic applications and amenability to modification, noscapine is a veritable “Renaissance drug” worthy of commemoration. Perhaps the only facet of noscapine's profile more astounding than its versatility is its virtual lack of side effects and addictive properties, which distinguishes it from other denizens of Papaver somniferum. This review intimately chronicles the rich intellectual and pharmacological history behind the noscapine family of compounds, the length of whose arms was revealed over decades of patient scholarship and experimentation. We discuss the intriguing story of this family of nontoxic alkaloids, from noscapine's purification from opium at the turn of the 19th century in Paris to the recent torrent of rationally designed analogs with tremendous anticancer potential. In between, noscapine's unique pharmacology; impact on cellular signaling pathways, the mitotic spindle, and centrosome clustering; use as an antimalarial drug and cough suppressant; and exceptional potential as a treatment for polycystic ovarian syndrome, strokes, and diverse malignancies are catalogued. Seminal experiments involving some of its more promising analogs, such as amino‐noscapine, 9‐nitronoscapine, 9‐bromonoscapine, and reduced bromonoscapine, are also detailed. Finally, the bright future of these oftentimes even more exceptional derivatives is described, rounding out a portrait of a truly remarkable family of compounds.     

Focused antibody response to influenza linked to antigenic drift

The selective pressure that drives antigenic changes in influenza viruses is thought to originate from the human immune response. Here, we have characterized the B cell repertoire from a previously vaccinated donor whose serum had reduced neutralizing activity against the recently evolved clade 6B H1N1pdm09 viruses. While the response was markedly polyclonal, 88% of clones failed to recognize clade 6B viruses; however, the ability to neutralize A/USSR/90/1977 influenza, to which the donor would have been exposed in childhood, was retained. In vitro selection of virus variants with representative monoclonal antibodies revealed that a single amino acid replacement at residue K163 in the Sa antigenic site, which is characteristic of the clade 6B viruses, was responsible for resistance to neutralization by multiple monoclonal antibodies and the donor serum. The K163 residue lies in a part of a conserved surface that is common to the hemagglutinins of the 1977 and 2009 H1N1 viruses. Vaccination with the 2009 hemagglutinin induced an antibody response tightly focused on this common surface that is capable of selecting current antigenic drift variants in H1N1pdm09 influenza viruses. Moreover, amino acid replacement at K163 was not highlighted by standard ferret antisera. Human monoclonal antibodies may be a useful adjunct to ferret antisera for detecting antigenic drift in influenza viruses.     

Impact of the Combination of Daptomycin and Trimethoprim-Sulfamethoxazole on Clinical Outcomes in Methicillin-Resistant Staphylococcus aureus Infections

Complicated Staphylococcus aureus infections, including bacteremia, are often associated with treatment failures, prolonged hospital stays, and the emergence of resistance to primary and even secondary therapies. Daptomycin is commonly used as salvage therapy after vancomycin failure for the treatment of methicillin-resistant S. aureus (MRSA) infections. Unfortunately, the emergence of daptomycin resistance, especially in deep-seated infections, has been reported, prompting the need for alternative or combination therapy. Numerous antibiotic combinations with daptomycin have been investigated clinically and in vitro. Of interest, the combination of daptomycin and trimethoprim-sulfamethoxazole (TMP-SMX) has proved to be rapidly bactericidal in vitro to strains that are both susceptible and nonsusceptible to daptomycin. However, to date, there is limited clinical evidence supporting the use of this combination. This was a multicenter, retrospective case series of patients treated with the combination of daptomycin and TMP-SMX for at least 72 h. The objective of this study was to describe the safety and effectiveness of this regimen in clinical practice. The most commonly stated reason that TMP-SMX was added to daptomycin was persistent bacteremia and/or progressive signs and symptoms of infection. After the initiation of combination therapy, the median time to clearance of bacteremia was 2.5 days. Microbiological eradication was demonstrated in 24 out of 28 patients, and in vitro synergy was demonstrated in 17 of the 17 recovered isolates. Further research with this combination is necessary to describe the optimal role and its impact on patient outcomes.