No abstract

Fasciola hepatica is a widespread pathogen that is known for its harmful effects on the health and productivity of ruminant animals. To identify the proteins present in all periods of infection with F. hepatica but not in those with Fasciola gigantica by shotgun liquid chromatography–tandem mass spectrometry (LC–MS/MS), we collected the ESPs and sera of F. hepatica and F. gigantica. In this study, the sheep were artificially infected with F. hepatica and the sera were collected at five different periods: 3 days post-infection (dpi), 7 dpi, 21 dpi, 63 dpi, and 112 dpi. The interacting proteins were pulled down from the sheep sera of all five periods and the sera with F. gigantica by co-immunoprecipitation (Co-IP) assay, before being identified by LC–MS/MS analysis. Thirty, twenty-two, twenty-three, twenty-seven, and twenty-two proteins were pulled down by the infected sera at 3 dpi, 7 dpi, 21 dpi, 63 dpi, and 112 dpi, respectively. Among them, 12 proteins existed in all periods, while six proteins could be detected in all periods in F. hepatica but not in F. gigantica. Protein relative pathway analysis revealed that these proteins mainly refer to the metabolism, regulation of genetic activity, and signal transduction of F. hepatica. In conclusion, this study provides meaningful data for the diagnosis of fasciolosis and to understand the interactions between F. hepatica and the host.

Tetrameres grusi is a significant parasitic nematode of cranes that is classified into suborder Spirurina. However, for more than a century, this classification has been controversial. Mitochondrial genomes are valuable resources for parasite taxonomy, population genetics and systematics studies. Here, the mitochondrial genome of T. grusi was determined and subsequently compared with those from Spirurina species using concatenated datasets of amino acid sequences predicted from mitochondrial protein-coding genes. The complete mitochondrial genome of T. grusi is circular with 13,709 bp, and it contains 12 protein-coding genes, 22 transfer RNA genes, two ribosomal RNA genes and one non-coding region. All of the protein-coding genes are transcribed in the same direction. There were 18 intergenic spacers of 1–44 bp, and six locations with gene overlaps, ranging from 1 bp to 28 bp, in the mitochondrial genome of T. grusi . The AT content of this mitochondrial genome was 71.56%. This was similar to mitochondrial genomes of other Spirurina species, which also exhibited strong AT content bias, not only in the nucleotide composition but also in codon usage. The sequenced mitogenomes of the 25 Spirurina nematodes showed three classes of gene arrangements based on the 12 protein-coding genes, and the gene arrangement of the T. grusi mitochondrial genome belonged to the Class I. Phylogenetic analyses using mitochondrial genomes of 25 Spirurina nematodes revealed that T. grusi (Habronematoidea) was closer to Gongylonema pulchrum (Spiruroidea) than Spirocerca lupi (Thelazioidea). The availability of the complete mitochondrial genome sequence of T. grusi provides new and useful genetic markers for further studies on Spirurina nematodes.

Species of the genus Russula are key components of ectomycorrhizal ecosystems worldwide, some of which are famous edible fungi. Although many new species have been described in China, their diversity in North China is still poorly known. Based on the morphology observation of specimens and molecular phylogenetic analyses, combined with the current classification frame of Russula, six new species of Russula subgenus Russula are proposed from the Yanshan Mountains in northern Beijing and northern Hebei Province of China in this study: viz. Russula miyunensis (subsection Chamaeleontinae), R. plana (subsection Chamaeleontinae), R. sinoparva (subsection Puellarinae), R. sinorobusta (subsection Puellarinae), R. subversatilis (subsection Roseinae), and R. yanshanensis (subsection Puellarinae). This is the first report of the species of Russula subgenus Russula from the Yanshan Mountains. This study enriches the species diversity of Russula in North China and provides new data support for the systematic study of Russula in subsequent research, including research and development on edibility.

Pharmacovigilance aims to identify adverse drug reactions using postmarket surveillance data under real-world conditions of use. Unlike passive pharmacovigilance, which is based on largely voluntary (and hence incomplete) spontaneous reports of adverse drug reactions with limited information on patient characteristics, active pharmacovigilance is based on electronic health records containing detailed information about patient populations, thereby allowing consideration of modifying factors such as polypharmacy and comorbidity, as well as sociodemographic characteristics. With the present shift toward active pharmacovigilance, statistical methods capable of addressing the complexities of such data are needed. We describe four such methods here, and demonstrate their application in the analysis of a large retrospective cohort of diabetics taking anti-hyperglycemic medications that may increase the risk of adverse cardiovascular events.