The domestic pig is of enormous agricultural significance and valuable models for many human diseases. Information concerning the pig microRNAome (miRNAome) has been long overdue and elucidation of this information will permit an atlas of microRNA (miRNA) regulation functions and networks to be constructed. Here we performed a comprehensive search for porcine miRNAs on ten small RNA sequencing libraries prepared from a mixture of tissues obtained during the entire pig lifetime, from the fetal period through adulthood. The sequencing results were analyzed using mammalian miRNAs, the precursor hairpins (pre-miRNAs) and the first release of the high-coverage porcine genome assembly (Sscrofa9, April 2009) and the available expressed sequence tag (EST) sequences. Our results extend the repertoire of pig miRNAome to 867 pre-miRNAs (623 with genomic coordinates) encoding for 1,004 miRNAs, of which 777 are unique. We preformed real-time quantitative PCR (q-PCR) experiments for selected 30 miRNAs in 47 tissue-specific samples and found agreement between the sequencing and q-PCR data. This broad survey provides detailed information about multiple variants of mature sequences, precursors, chromosomal organization, development-specific expression, and conservation patterns. Our data mining produced a broad view of the pig miRNAome, consisting of miRNAs and isomiRs and a wealth of information of pig miRNA characteristics. These results are prelude to the advancement in pig biology as well the use of pigs as model organism for human biological and biomedical studies.

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Objective: Analyses of crash data have shown that older, obese, and/or female occupants have a higher risk of injury in frontal crashes compared to the rest of the population. The objective of this study was to use parametric finite element (FE) human models to assess the increased injury risks and identify safety concerns for these vulnerable populations. Methods: We sampled 100 occupants based on age, sex, stature, and body mass index (BMI) to span a wide range of the U.S. adult population. The target anatomical geometry for each of the 100 models was predicted by the statistical geometry models for the rib cage, pelvis, femur, tibia, and external body surface developed previously. A regional landmark-based mesh morphing method was used to morph the Global Human Body Models Consortium (GHBMC) M50-OS model into the target geometries. The morphed human models were then positioned in a validated generic vehicle driver compartment model using a statistical driving posture model. Frontal crash simulations based on U.S. New Car Assessment Program (U.S. NCAP) were conducted. Body region injury risks were calculated based on the risk curves used in the US NCAP, except that scaling was used for the neck, chest, and knee-thigh-hip injury risk curves based on the sizes of the bony structures in the corresponding body regions. Age effects were also considered for predicting chest injury risk. Results: The simulations demonstrated that driver stature and body shape affect occupant interactions with the restraints and consequently affect occupant kinematics and injury risks in severe frontal crashes. U-shaped relations between occupant stature/weight and head injury risk were observed. Chest injury risk was strongly affected by age and sex, with older female occupants having the highest risk. A strong correlation was also observed between BMI and knee-thigh-hip injury risk, whereas none of the occupant parameters meaningfully affected neck injury risks.Conclusions: This study is the first to use a large set of diverse FE human models to investigate the combined effects of age, sex, stature, and BMI on injury risks in frontal crashes. The study demonstrated that parametric human models can effectively predict the injury trends for the population and may now be used to optimize restraint systems for people who are not similar in size and shape to the available anthropomorphic test devices (ATDs). New restraints that adapt to occupant age, sex, stature, and body shape may improve crash safety for all occupants. ARTICLE HISTORY

We constructed a quantitative Ecopath model of a trophic network to evaluate the energy flow and properties in a polyculture ecosystem containing 4 species (swimming crab Portunus trituberculatus, white shrimp Litopenaeus vannamei, short-necked clam Ruditapes philippinarum, and redlip mullet Liza haematochila) over a 90 d experimental period. The model contained 10 consumers, 4 detritus groups, and 4 primary producers. Ecotrophic efficiency values indicated that the system had high energy utilization efficiency. However, benthic bacteria converted the largest amount of energy back to the detritus groups, which had the lowest ecotrophic efficiency (0.01). When aggregating the network to discrete trophic levels (TLs), most of the throughput and biomass of the system were distributed on the first 2 TLs; consequently, there was high energy transfer efficiency between TL I and II (81.98%). The trophic flow of this ecosystem was dominated by energy that originated from the detritus groups (73.77%). Imported artificial food was particularly important for the trophic flow of the total ecosystem, contributing 31.02% to total system consumption. The trophic network of the polyculture ecosystem had a moderate Finn's cycling index (17.44%), a relatively low connectance index (CI: 26.70%), and a low system omnivory index (SOI: 0.08). Relative ascendancy was estimated as 44.90% in this model. Overall, ecosystem properties (i.e. CI, SOI, and relative ascendancy) showed that the artificial 4-species polyculture system represents a simple and fragile, but also 'balanced,' ecosystem.