Tweeting the meeting: an in-depth analysis of Twitter activity at Kidney Week 2011

In recent years, the American Society of Nephrology (ASN) has increased its efforts to use its annual conference to inform and educate the public about kidney disease. Social media, including Twitter, has been one method used by the Society to accomplish this goal. Twitter is a popular microblogging service that serves as a potent tool for disseminating information. It allows for short messages (140 characters) to be composed by any author and distributes those messages globally and quickly. The dissemination of information is necessary if Twitter is to be considered a tool that can increase public awareness of kidney disease. We hypothesized that content, citation, and sentiment analyses of tweets generated from Kidney Week 2011 would reveal a large number of educational tweets that were disseminated to the public. An ideal tweet for accomplishing this goal would include three key features: 1) informative content, 2) internal citations, and 3) positive sentiment score. Informative content was found in 29% of messages, greater than that found in a similarly sized medical conference (2011 ADA Conference, 16%). Informative tweets were more likely to be internally, rather than externally, cited (38% versus 22%, p<0.0001), thereby amplifying the original information to an even larger audience. Informative tweets had more negative sentiment scores than uninformative tweets (means -0.162 versus 0.199 respectively, p<0.0001), therefore amplifying a tweet whose content had a negative tone. Our investigation highlights significant areas of promise and improvement in using Twitter to disseminate medical information in nephrology from a scientific conference. This goal is pertinent to many nephrology-focused conferences that wish to increase public awareness of kidney disease.     

Tracking Time Evolution of Collective Attention Clusters in Twitter: Time Evolving Nonnegative Matrix Factorisation

Micro-blogging services, such as Twitter, offer opportunities to analyse user behaviour. Discovering and distinguishing behavioural patterns in micro-blogging services is valuable. However, it is difficult and challenging to distinguish users, and to track the temporal development of collective attention within distinct user groups in Twitter. In this paper, we formulate this problem as tracking matrices decomposed by Nonnegative Matrix Factorisation for time-sequential matrix data, and propose a novel extension of Nonnegative Matrix Factorisation, which we refer to as Time Evolving Nonnegative Matrix Factorisation (TENMF). In our method, we describe users and words posted in some time interval by a matrix, and use several matrices as time-sequential data. Subsequently, we apply Time Evolving Nonnegative Matrix Factorisation to these time-sequential matrices. TENMF can decompose time-sequential matrices, and can track the connection among decomposed matrices, whereas previous NMF decomposes a matrix into two lower dimension matrices arbitrarily, which might lose the time-sequential connection. Our proposed method has an adequately good performance on artificial data. Moreover, we present several results and insights from experiments using real data from Twitter.     

Rumor Diffusion and Convergence during the 3.11 Earthquake: A Twitter Case Study

We focus on Internet rumors and present an empirical analysis and simulation results of their diffusion and convergence during emergencies. In particular, we study one rumor that appeared in the immediate aftermath of the Great East Japan Earthquake on March 11, 2011, which later turned out to be misinformation. By investigating whole Japanese tweets that were sent one week after the quake, we show that one correction tweet, which originated from a city hall account, diffused enormously. We also demonstrate a stochastic agent-based model, which is inspired by contagion model of epidemics SIR, can reproduce observed rumor dynamics. Our model can estimate the rumor infection rate as well as the number of people who still believe in the rumor that cannot be observed directly. For applications, rumor diffusion sizes can be estimated in various scenarios by combining our model with the real data.     

PCR and Culture Identification of Pathogenic Leptospira spp. from Coastal Soil in Leyte,Philippines, after a Storm Surge during Super Typhoon Haiyan (Yolanda)

Leptospirosis is a zoonosis caused by pathogenic Leptospira spp. Most of the outbreaks of leptospirosis occur after floods caused by heavy rain in countries where Leptospira spp. are endemic. It has been believed that the overflow of seawater rarely causes outbreaks of leptospirosis because the leptospires are killed by salt water. On 8 November 2013, a storm surge caused by Super Typhoon Haiyan (Yolanda) inundated the entire coastal areas of Tacloban and Palo in Leyte, Philippines. The present study was carried out in order to determine whether the environmental leptospires in soil were able to survive after the storm surge in the affected areas. We collected 23 wet soil samples along the coastal areas of Tacloban and Palo 2 months after the storm surge. The samples were suspended in HEPES buffer, and the supernatants were cultured in liquid or semisolid Korthof''s medium supplemented with five antimicrobial agents to inhibit the growth of contaminants. Leptospires were isolated from primary cultures of 22 out of 23 samples. The DNA of pathogenic Leptospira species was detected in 11 samples (47.8%) by analysis of flaB by nested PCR. Eventually, two pathogenic Leptospira strains were isolated and showed the highest 16S rRNA gene sequence similarity to Leptospira kmetyi. When these isolates were experimentally mixed with soil, they were found to survive in seawater for 4 days. These results show the possibility that leptospires living in soil survived after the storm surge. Our findings may serve as a warning that when seawater inundates the land during a storm surge or a tsunami, an outbreak of leptospirosis could occur in the disaster-stricken area.     

Psychological Resilience after Hurricane Sandy: The Influence of Individual- and Community-Level Factors on Mental Health after a Large-Scale Natural Disaster

Several individual-level factors are known to promote psychological resilience in the aftermath of disasters. Far less is known about the role of community-level factors in shaping postdisaster mental health. The purpose of this study was to explore the influence of both individual- and community-level factors on resilience after Hurricane Sandy. A representative sample of household residents (N = 418) from 293 New York City census tracts that were most heavily affected by the storm completed telephone interviews approximately 13–16 months postdisaster. Multilevel multivariable models explored the independent and interactive contributions of individual- and community-level factors to posttraumatic stress and depression symptoms. At the individual-level, having experienced or witnessed any lifetime traumatic event was significantly associated with higher depression and posttraumatic stress, whereas demographic characteristics (e.g., older age, non-Hispanic Black race) and more disaster-related stressors were significantly associated with higher posttraumatic stress only. At the community-level, living in an area with higher social capital was significantly associated with higher posttraumatic stress. Additionally, higher community economic development was associated with lower risk of depression only among participants who did not experience any disaster-related stressors. These results provide evidence that individual- and community-level resources and exposure operate in tandem to shape postdisaster resilience.     

Temporal patterns of happiness and information in a global social network: hedonometrics and Twitter

Individual happiness is a fundamental societal metric. Normally measured through self-report, happiness has often been indirectly characterized and overshadowed by more readily quantifiable economic indicators such as gross domestic product. Here, we examine expressions made on the online, global microblog and social networking service Twitter, uncovering and explaining temporal variations in happiness and information levels over timescales ranging from hours to years. Our data set comprises over 46 billion words contained in nearly 4.6 billion expressions posted over a 33 month span by over 63 million unique users. In measuring happiness, we construct a tunable, real-time, remote-sensing, and non-invasive, text-based hedonometer. In building our metric, made available with this paper, we conducted a survey to obtain happiness evaluations of over 10,000 individual words, representing a tenfold size improvement over similar existing word sets. Rather than being ad hoc, our word list is chosen solely by frequency of usage, and we show how a highly robust and tunable metric can be constructed and defended.     

Japanese Organic Farmers: Strategies of Uncertainty after the Fukushima Disaster

This ethnographic study of organic farmers affected by radioactive contamination in Japan illuminates responses to situated uncertainty as an everyday mode of subjectivity and practice. The farmers' strategies vary along a continuum from accommodation with dominant institutions to precautions of possible uncertainty to innovations and oppositions of potential uncertainty. Significantly these strategies are contradictory and they show variations in power and morality. The data indicate a subjective- and practice-oriented response that I call localized, relational uncertainty. It is contextualized in farms and villages with responsibility for family, consumers, and organic agriculture itself and it enables farmers to embrace multiple strategies. Thus, uncertainty brings loss and limitations, but also produces opportunities through, for example, expanded trust in relationships, deepened commitment to place, reinterpretation of organic agriculture, and sharpened critique of Japan's trajectory of economic growth.     

Twitter evolution: converging mechanisms in birdsong and human speech

Vocal imitation in human infants and in some orders of birds relies on auditory-guided motor learning during a sensitive period of development. It proceeds from 'babbling' (in humans) and 'subsong' (in birds) through distinct phases towards the full-fledged communication system. Language development and birdsong learning have parallels at the behavioural, neural and genetic levels. Different orders of birds have evolved networks of brain regions for song learning and production that have a surprisingly similar gross anatomy, with analogies to human cortical regions and basal ganglia. Comparisons between different songbird species and humans point towards both general and species-specific principles of vocal learning and have identified common neural and molecular substrates, including the forkhead box P2 (FOXP2) gene.     

Evolving changes in lung interstitial fluid content after acute myocardial infarction: mechanisms and pathophysiological correlates

In acute myocardial infarction (AMI), alveolar interstitium edema is generally attributed to a hydrostatic imbalance. However, inflammatory burden and/or neural/hormonal/hemodynamic stimulation might injure the microvascular endothelium, eliciting interstitial overflow and altering alveolar-capillary gas diffusion. In 118 patients with AMI (ejection fraction >or=50% and wedge pulmonary pressure <16 mmHg), admission alveolar-capillary gas diffusing membrane conductance (DM) averaged 35.1 ml.min(-1).mmHg(-1) and was 27% lower than in 25 controls (P < 0.01). Infusion of saline in the pulmonary circulation (to test sodium exchange across the pulmonary capillary wall) lowered DM by 7.1% (P < 0.01) and was neutral in controls. At 1 wk, 83 patients that showed DM improvement >5% were assigned to group 1, and 28 patients with DM worsening >5% were assigned to group 2. Saline retained efficacy in group 2 and had no DM effect in group 1 (supporting a link between changes in baseline DM and those in microvascular salt exchange). Ventricular function was unchanged in group 1, whereas group 2 had developed diastolic dysfunction. At 1 yr, 3% of cases in group 1 and 37% of cases in group 2 had alveolar edema. Thus, AMI is frequently associated with abnormal pulmonary microvascular sodium transport/water conductance that, in the case of ventricular dysfunction supervenience, may persist and worsen the outcome. In 37 AMI similar patients and 11 control subjects, nitric oxide overexpression with l-arginine improved baseline DM and in AMI patients prevented DM reduction by saline, suggesting a mechanistic role of an impaired nitric oxide pathway in the microvascular barrier dysfunction.     

Pandemics in the age of Twitter: content analysis of Tweets during the 2009 H1N1 outbreak

Background

Surveys are popular methods to measure public perceptions in emergencies but can be costly and time consuming. We suggest and evaluate a complementary “infoveillance” approach using Twitter during the 2009 H1N1 pandemic. Our study aimed to: 1) monitor the use of the terms “H1N1” versus “swine flu” over time; 2) conduct a content analysis of “tweets”; and 3) validate Twitter as a real-time content, sentiment, and public attention trend-tracking tool.

Methodology/Principal Findings

Between May 1 and December 31, 2009, we archived over 2 million Twitter posts containing keywords “swine flu,” “swineflu,” and/or “H1N1.” using Infovigil, an infoveillance system. Tweets using “H1N1” increased from 8.8% to 40.5% (R ² = .788; p<.001), indicating a gradual adoption of World Health Organization-recommended terminology. 5,395 tweets were randomly selected from 9 days, 4 weeks apart and coded using a tri-axial coding scheme. To track tweet content and to test the feasibility of automated coding, we created database queries for keywords and correlated these results with manual coding. Content analysis indicated resource-related posts were most commonly shared (52.6%). 4.5% of cases were identified as misinformation. News websites were the most popular sources (23.2%), while government and health agencies were linked only 1.5% of the time. 7/10 automated queries correlated with manual coding. Several Twitter activity peaks coincided with major news stories. Our results correlated well with H1N1 incidence data.

Conclusions

This study illustrates the potential of using social media to conduct “infodemiology” studies for public health. 2009 H1N1-related tweets were primarily used to disseminate information from credible sources, but were also a source of opinions and experiences. Tweets can be used for real-time content analysis and knowledge translation research, allowing health authorities to respond to public concerns.     

Functions and regulation of NF-kappaB RelA during pneumococcal pneumonia

Eradication of bacteria in the lower respiratory tract depends on the coordinated expression of proinflammatory cytokines and consequent neutrophilic inflammation. To determine the roles of the NF-kappaB subunit RelA in facilitating these events, we infected RelA-deficient mice (generated on a TNFR1-deficient background) with Streptococcus pneumoniae. RelA deficiency decreased cytokine expression, alveolar neutrophil emigration, and lung bacterial killing. S. pneumoniae killing was also diminished in the lungs of mice expressing a dominant-negative form of IkappaBalpha in airway epithelial cells, implicating this cell type as an important locus of NF-kappaB activation during pneumonia. To study mechanisms of epithelial RelA activation, we stimulated a murine alveolar epithelial cell line (MLE-15) with bronchoalveolar lavage fluid (BALF) harvested from mice infected with S. pneumoniae. Pneumonic BALF, but not S. pneumoniae, induced degradation of IkappaBalpha and IkappaBbeta and rapid nuclear accumulation of RelA. Moreover, BALF-induced RelA activity was completely abolished following combined but not individual neutralization of TNF and IL-1 signaling, suggesting either cytokine is sufficient and necessary for alveolar epithelial RelA activation during pneumonia. Our results demonstrate that RelA is essential for the host defense response to pneumococcus in the lungs and that RelA in airway epithelial cells is primarily activated by TNF and IL-1.     

Functions of mammalian spinal interneurons during movement

The major recent advances in understanding the role of spinal neurons in generating movement include new information about the modulation of classic reflex pathways during fictive locomotion and in response to pharmacological probes. The possibility of understanding movements in terms of spinal representations of a basic set of movement primitives has been extended by the analysis of normal reflexes. Recordings of the activity of cervical interneurons in behaving monkeys has elucidated their contribution to generating voluntary movement and revealed their involvement in movement preparation.     

Evolving Darwin's 'most wonderful' plant: ecological steps to a snap-trap

Among carnivorous plants, Darwin was particularly fascinated by the speed and sensitivity of snap-traps in Dionaea and Aldrovanda . Recent molecular work confirms Darwin's conjecture that these monotypic taxa are sister to Drosera , meaning that snap-traps evolved from a 'flypaper' trap. Transitions include tentacles being modified into trigger hairs and marginal 'teeth', the loss of sticky tentacles, depressed digestive glands, and rapid leaf movement. Pre-adaptations are known for all these traits in Drosera yet snap-traps only evolved once. We hypothesize that selection to catch and retain large insects favored the evolution of elongate leaves and snap-tentacles in Drosera and snap-traps. Although sticky traps efficiently capture small prey, they allow larger prey to escape and may lose nutrients. Dionaea 's snap-trap efficiently captures and processes larger prey providing higher, but variable, rewards. We develop a size-selective model and parametrize it with field data to demonstrate how selection to capture larger prey strongly favors snap-traps. As prey become larger, they also become rarer and gain the power to rip leaves, causing returns to larger snap-traps to plateau. We propose testing these hypotheses with specific field data and Darwin-like experiments. The complexity of snap-traps, competition with pitfall traps, and their association with ephemeral habitats all help to explain why this curious adaptation only evolved once.     

Evolving nature of the AP2 alpha-appendage hub during clathrin-coated vesicle endocytosis

Clathrin-mediated endocytosis involves the assembly of a network of proteins that select cargo, modify membrane shape and drive invagination, vesicle scission and uncoating. This network is initially assembled around adaptor protein (AP) appendage domains, which are protein interaction hubs. Using crystallography, we show that FxDxF and WVxF peptide motifs from synaptojanin bind to distinct subdomains on alpha-appendages, called 'top' and 'side' sites. Appendages use both these sites to interact with their binding partners in vitro and in vivo. Occupation of both sites simultaneously results in high-affinity reversible interactions with lone appendages (e.g. eps15 and epsin1). Proteins with multiple copies of only one type of motif bind multiple appendages and so will aid adaptor clustering. These clustered alpha(appendage)-hubs have altered properties where they can sample many different binding partners, which in turn can interact with each other and indirectly with clathrin. In the final coated vesicle, most appendage binding partners are absent and thus the functional status of the appendage domain as an interaction hub is temporal and transitory giving directionality to vesicle assembly.     

Functions and Roles of Proteins: Diabetes as a Paradigm

Molecular and cellular biology has moved towards complete and accurate knowledge of how molecules behave in space and time. Protein is considered as the primary group of molecules responsible for mediating most physiological processes. Changes in the levels of proteins may lead to the altered function and are responsible for many diseases. This review provides a partial molecular explanation of biological force-ratio generation that may act to split protein into branches, and shows molecular functional divergence. Developing a non-reductionist theory of the cellular function in medicine is clearly not sufficient. Finding effective parameters of the models by characterizing molecular interactions becomes necessary. Protein interactivity and stability provides a basis for an integrated understanding of pathologies such diabetes. One example of how a mechanistic analysis of such physiological processes can be of value is the time-delay between mRNA and translation that can act as a fork allowing a slowdown in gene expression.