15 research outputs found

    Selection of Reference Genes for Gene Expression Studies in Porcine Whole Blood and Peripheral Blood Mononuclear Cells under Polyinosinic:Polycytidylic Acid Stimulation

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    Investigating gene expression of immune cells of whole blood or peripheral blood mononuclear cells (PBMC) under polyinosinic:polycytidylic acid (poly I:C) stimulation is valuable for understanding the immune response of organism to RNA viruses. Quantitative real-time PCR (qRT-PCR) is a standard method for quantification of gene expression studies. However, the reliability of qRT-PCR data critically depends on proper selection of reference genes. In the study, using two different analysis programs, geNorm and NormFinder, we systematically evaluated the gene expression stability of six candidate reference genes (GAPDH, ACTB, B2M, RPL4, TBP, and PPIA) in samples of whole blood and PBMC with or without poly I:C stimulation. Generally, the six candidate genes performed a similar trend of expression stability in the samples of whole blood and PBMC, but more stably expressed in whole blood than in PBMC. geNorm ranked B2M and PPIA as the best combination for gene expression normalization, while according to NormFinder, TBP was ranked as the most stable reference gene, followed by B2M and PPIA. Comprehensively considering the results from the two programs, we recommended using the geometric mean of the three genes, TBP, PPIA and B2M, to normalize the gene expression of whole blood and PBMC with poly I:C stimulation. Our study is the first detailed survey of the gene expression stability in whole blood and PBMC with or without poly I:C stimulation and should be helpful for investigating the molecular mechanism involved in porcine whole blood and PBMC in response to poly I:C stimulation

    On the solvability of infinite horizon forward-backward stochastic differential equations with absorption coefficients

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    Solvability of infinite horizon forward-backward stochastic differential equations with absorption coefficients is considered by successive approximation method. The uniqueness and existence of an adapted solution is established for the equations.Infinite horizon Forward-backward stochastic differential equations Absorption condition

    Transcriptomic Analysis of the Porcine Endometrium during Embryo Implantation

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    In pigs, successful embryo implantation is an important guarantee for producing litter size, and early embryonic loss occurring on day 12–30 of gestation critically affects the potential litter size. The implantation process is regulated by the expression of numerous genes, so comprehensive analysis of the endometrium is necessary. In this study, RNA sequencing (RNA-Seq) technology is used to analyze endometrial tissues during early pregnancy. We investigated the changes of gene expression between three stages (day 12, 18, and 25) by multiple comparisons. There were 1557, 8951, and 2345 differentially expressed genes (DEGs) revealed between the different periods of implantation. We selected several genes for validation by the use of quantitative real-time RT-PCR. Bioinformatic analysis of differentially expressed genes in the endometrium revealed a number of biological processes and pathways potentially involved in embryo implantation in the pig, most noticeably cell proliferation, regulation of immune response, interaction of cytokine-cytokine receptors, and cell adhesion. These results showed that specific gene expression patterns reflect the different functions of the endometrium in three stages (maternal recognition, conceptus attachment, and embryo implantation). This study identified comprehensive transcriptomic profile in the porcine endometrium and thus could be a foundation for targeted studies of genes and pathways potentially involved in abnormal endometrial receptivity and embryo loss in early pregnancy

    Toxic Effects of Two Representative Rare Earth Elements (La and Gd) on Danio rerio Based on Transcriptome Analysis

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    The expanding applications of rare earth elements (REEs) in various fields have raised concerns about their biosafety. However, previous studies are insufficient to elucidate their toxic effects and mechanisms of action and whether there are uniform or predictable toxicity patterns among REEs. Herein, we investigated the toxic effects of two representative REEs (lanthanum (La) and gadolinium (Gd)) on zebrafish (Danio rerio) through toxicity experiments and transcriptome analysis. The results of the toxicity experiments showed that the two REEs have similar lethality, with half-lethal concentrations (LC50) at micromolar levels and mixed toxicity showing additive effects. Differential expression gene screening and functional group enrichment analysis showed that La and Gd might affect the growth and development of Danio rerio by interfering with some biological molecules. The two REEs showed significant effects on the metabolic pathways of exogenous or endogenous substances, including glutathione sulfotransferase and acetaldehyde dehydrogenase. Moreover, some basic biological processes, such as DNA replication, the insulin signaling pathway, and the p53 signaling pathway, were significantly enriched. Overall, the toxicity patterns of La and Gd may affect some biological processes with different intensities; however, there are many similarities in their toxicity mechanisms and modes of action. The concentrations investigated in this study were comparable to those of REE residues at highly contaminated sites, thus mimicking the ecotoxicological effects at environmentally relevant concentrations

    MicroRNA Transcriptome of Poly I:C-Stimulated Peripheral Blood Mononuclear Cells Reveals Evidence for MicroRNAs in Regulating Host Response to RNA Viruses in Pigs

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    MicroRNAs (miRNAs) are one family of small noncoding RNAs that function to modulate the activity of specific mRNA targets in animals. To understand the role of miRNAs in regulating genes involved in the host immune response to RNA viruses, we profiled and characterized the miRNAs of swine peripheral blood mononuclear cells (PBMC) stimulated with poly I:C, a synthetic dsRNA analog, by miRNA-sequencing (miRNA-seq). We identified a total of 905 miRNAs, of which 503 miRNAs were firstly exploited herein with no annotation in the latest miRBase 21.0. Expression analysis demonstrated that poly I:C stimulation can elicit significantly differentially expressed (DE) miRNAs in Dapulian (n = 20), one Chinese indigenous breed, as well as Landrace (n = 23). By integrating the mRNA expression profiles of the same sample with miRNA profiles, we carried out function analyses of the target genes of these DE miRNAs, with the results indicating that target genes were most enriched in some immune-related pathways and gene ontology (GO) terms, suggesting that DE miRNAs play an important role in the regulation of host to poly I:C stimulation. Furthermore, we also detected 43 and 61 significantly DE miRNAs between the two breeds in the control sample groups and poly I:C stimulation groups, respectively, which may be involved in regulation of the different characteristics of the two breeds. This study describes for the first time the PBMC miRNA transcriptomic response to poly I:C stimulation in pigs, which not only contributes to a broad view of the pig miRNAome but improves our understanding of miRNA function in regulating host immune response to RNA viruses

    Clustering-inspired Channel Selection Method for Weakly Supervised Object Localization

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    Weakly Supervised Object Localization (WSOL) aims to utilize the features learned by a classifier on the image-level labels to locate target objects. However, these existing channel selection methods for WSOL still cannot effectively select the important channels and remove the unimportant ones. To address this issue, we propose a Clustering-inspired Channel Selection method based on Class Activation Maps (CCS-CAM). Compared with the traditional methods, the advantage of CCS-CAM is that it is very simple yet effective for channel selection due to the K-means clustering based on Class Activation Maps. It can effectively ensure both object localization and classification accuracy. The effectiveness of the proposed CCS-CAM method has been demonstrated using multiple public datasets, with GT-Know Loc reaching 87.9% and 63.71% on the CUB200-2011 and ImageNet-1k respectively, which is superior to the other state-of-the-art methods.</p
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