Background: In 2008, the Southern California Earthquake Center in collaboration with the U.S. Geological Survey Earthquake Hazards Program launched the first annual Great ShakeOut, the largest earthquake preparedness drill in the history of the United States. Materials and Methods: We collected online survey data from 2052 campaign registrants to assess how people participated, whether audience segments shared behavioral patterns, and whether these segments were associated with five social cognitive factors targeted by the ShakeOut campaign. Results: Participants clustered into four behavioral patterns. The Minimal cluster had low participation in all activities (range: 0-39% participation). The Basic Drill cluster only participated in the drop, cover and hold drill (100% participation). The Community-Oriented cluster, involved in the drill (100%) and other interpersonal activities including attending disaster planning meetings (74%), was positively associated with interpersonal communication (β = 0.169), self-efficacy (β = 0.118), outcome efficacy (β = 0.110), and knowledge about disaster preparedness (β = 0.151). The Interactive and Games cluster, which participated in the drill (79%) and two online earthquake preparedness games (53% and 75%), was positively associated with all five social cognitive factors studied. Conclusions: Our results support audience segmentation approaches to engaging the public, which address the strengths and weaknesses of different segments. Offering games may help "gamers" gain competencies required to prepare for disasters. Targeting the highly active Community-Oriented cluster for leadership roles could help build community resilience by encouraging others to become more involved in disaster planning. We propose that the days of single, national education campaigns without local variation should end.

Microbial colonization of the human gastrointestinal tract plays an important role in establishing health and homeostasis. However, the time-dependent functional signatures of microbial and human proteins during early colonization of the gut have yet to be determined. To this end, we employed shotgun proteomics to simultaneously monitor microbial and human proteins in fecal samples from a preterm infant during the first month of life. Microbial community complexity increased over time, with compositional changes that were consistent with previous metagenomic and rRNA gene data. More specifically, the function of the microbial community initially involved biomass growth, protein production, and lipid metabolism, and then switched to more complex metabolic functions, such as carbohydrate metabolism, once the community stabilized and matured. Human proteins detected included those responsible for epithelial barrier function and antimicrobial activity. Some neutrophil-derived proteins increased in abundance early in the study period, suggesting activation of the innate immune system. Likewise, abundances of cytoskeletal and mucin proteins increased later in the time course, suggestive of subsequent adjustment to the increased microbial load. This study provides the first snapshot of coordinated human and microbial protein expression in a preterm infant's gut during early development.

Small proteins (10 200 amino acids aa in length) encoded by short open reading frames (sORF) play important regulatory roles in various biological processes, including tumor progression, stress response, flowering, and hormone signaling. However, ab initio discovery of small proteins has been relatively overlooked. Recent advances in deep transcriptome sequencing make it possible to efficiently identify sORFs at the genome level. In this study, we obtained 2.6 million expressed sequence tag (EST) reads from Populus deltoides leaf transcriptome and reconstructed full-length transcripts fromthe EST sequences. We identified an initial set of 12,852 sORFs encoding proteins of 10 200 aa in length. Three computational approaches were then used to enrich for bona fide protein-coding sORFs from the initial sORF set: (1) codingpotential prediction, (2) evolutionary conservation between P. deltoides and other plant species, and (3) gene familyclustering within P. deltoides. As a result, a high-confidence sORF candidate set containing 1469 genes was obtained. Analysis of the protein domains, non-protein-coding RNA motifs, sequence length distribution, and protein mass spectrometry data supported this high-confidence sORF set. In the high-confidence sORF candidate set, known protein domains were identified in 1282 genes (higher-confidence sORF candidate set), out of which 611 genes, designated as highest-confidence candidate sORF set, were supported by proteomics data. Of the 611 highest-confidence candidate sORF genes, 56 were newto the current Populus genome annotation. This study not only demonstrates that there are potential sORF candidates to be annotated in sequenced genomes, but also presents an efficient strategy for discovery of sORFs in species with no genome annotation yet available.