Short-chain fatty acids (SCFAs) are not only an important energy source, but they also play a regulatory role in various physiological processes in humans and rodents. Current studies, mostly in humans and rodents, have revealed that SCFAs acted as endogenous ligands for G protein-coupled receptor GPR41 and GPR43. Whether proteins similar to human GPR41 and GPR43 mediate the regulatory effects of SCFAs in swine remains unclear to date. The aims of this study were to determine whether GPR41 and GPR43 genes are expressed in porcine different tissues; and whether the expression of GPR41 and GPR43 is tissue-specific and/or time-associated. The alignment results showed that pig chromosome 6 contained GPR41 and GPR43 genes. Reverse transcription polymerase chain reaction (RT-PCR) indicated that GPR41 and GPR43 were expressed in porcine various tissues. The 2218 bp and 1908 bp nucleotide sequence representing the full-length cDNA sequence of porcine GPR41 and GPR43 was obtained from the ileum and spleen using rapid amplification of cDNA ends (RACE), which were capable of encoding 335 and 329 amino acid sequences, respectively. The structure prediction revealed that porcine GPR41 and GPR43 proteins had seven putative trans-membrane domains. The real-time PCR results indicated that GPR41 and GPR43 were expressed throughout the developmental stages in a tissue-specific and time-associated manner. GPR41 and GPR43 were most highly expressed in the ileum (P<0.01) and the spleen (P<0.01), respectively. Western blot results showed that porcine GPR41 and GPR43 proteins were expressed in a variety of porcine tissues, including the spleen, ileum, colon, and adipose tissue. In situ GPR41 and GPR43 immunoreactivities were observed through immunohistochemistry in the spleen, ileum, colon, and adipose tissue. In conclusion, the pig genome encoded GPR41 and GPR43 genes, and these two genes were detected in a variety of porcine tissues and expressed in tissue-specific and time-associated manner.
Based on the core hysteresis features, the RTD-fluxgate core, while working, is repeatedly saturated with excitation field. When the fluxgate simulates, the accurate characteristic model of the core may provide a precise simulation result. As the shape of the ideal hysteresis loop model is fixed, it cannot accurately reflect the actual dynamic changing rules of the hysteresis loop. In order to improve the fluxgate simulation accuracy, a dynamic hysteresis loop model containing the parameters which have actual physical meanings is proposed based on the changing rule of the permeability parameter when the fluxgate is working. Compared with the ideal hysteresis loop model, this model has considered the dynamic features of the hysteresis loop, which makes the simulation results closer to the actual output. In addition, other hysteresis loops of different magnetic materials can be explained utilizing the described model for an example of amorphous magnetic material in this manuscript. The model has been validated by the output response comparison between experiment results and fitting results using the model.
The commensal gut microbial communities play an important role in the health and production efficiency of growing-finishing pigs. This study aimed to analyse the composition and diversity of the microbiota in the gastrointestinal tract sections (stomach, duodenum, jejunum, ileum, caecum, colon and rectum) of growing-finishing pigs. This analysis was assessed using 454 pyrosequencing targeting the V3–V6 region of the 16S rRNA gene. Samples were collected from 20, healthy pigs aged 24 weeks and weighing 115.9 ± 5.4 kg. The dominant bacterial phyla in the various gastrointestinal tract sections were Firmicutes, Bacteroidetes, Proteobacteria and Actinobacteria. At the genus level, Prevotella, unclassified Lachnospiraceae, Ruminococcus, unclassified Ruminococcaceae and Oscillospira were more abundant in the large intestine than in the stomach and the small intestine. Unclassified Peptostreptococcaceae and Corynebacterium were more abundant in the small intestine than in the stomach and the large intestine. Shuttleworthia, unclassified Veillonellaceae and Mitsuokella were more abundant in the stomach than in the small and large intestines. At the species level, M. el.s.d.enii and M. multacida were predominant in the stomach. In addition, P. stercorea, P. copri, C. butyricum, R. flavefaciens and R. bromii were significantly more abundant in the large intestine than in the stomach and the small intestine. B. pseudolongum and B. thermacidophilum were significantly more abundant in the small intestine than in the stomach and the large intestine. Principal coordinates analysis showed that the overall composition of the pig gastrointestinal microbiota could be clustered into three groups: stomach, small intestine (duodenum, jejunum and ileum) and large intestine (caecum, colon and rectum). Venn diagrams illustrated the distribution of shared and specific operational taxonomic units among the various gastrointestinal tract sections.
ABSTRACT:The classic TRIAD was used to obtain the attitude of air vehicles. However, the accuracy was dominated by the sensor noise and the calculation order. To improve that in this paper, a new method based on weighting the vectors summation and difference was proposed. Then both simulation and experiment verified the advantages of the optimized algorithm.
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