Evidence map›Paper›PMID 30355335›Full record

ArticleBMC immunology2018

The excretory-secretory products of Echinococcus granulosus protoscoleces stimulated IL-10 production in B cells via TLR-2 signaling.

Wei Pan, Hui-Wen Xu, Wen-Ting Hao, Fen-Fen Sun, Yan-Fang Qin, Shan-Shan Hao, Hua Liu, Jian-Ping Cao, Yu-Juan Shen, Kui-Yang Zheng

Abstract read
In one paragraph

Article in BMC immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Cells · 2022
    Article
  8. Article
  9. Article
  10. The non-oral infection of larvalFrontiers in immunology · 2022
    Article
  11. Transcriptomic Profiles of Splenic CD19Frontiers in veterinary science · 2022
    Article
  12. Therapeutic Efficacy of Excretory-Secretory Products ofFrontiers in cellular and infection microbiology · 2021
    Article
  13. Article
  14. Review
  15. Metabolomics Analysis of Splenic CD19Frontiers in veterinary science · 2021
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Wei PanNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, China.
Hui-Wen XuJiangsu Key Laboratory of Immunity and Metabolism, Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Xuzhou, Jiangsu Province, China.
Wen-Ting HaoJiangsu Key Laboratory of Immunity and Metabolism, Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Xuzhou, Jiangsu Province, China.
Fen-Fen SunJiangsu Key Laboratory of Immunity and Metabolism, Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Xuzhou, Jiangsu Province, China.
Yan-Fang QinJiangsu Key Laboratory of Immunity and Metabolism, Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Xuzhou, Jiangsu Province, China.
Shan-Shan HaoJiangsu Key Laboratory of Immunity and Metabolism, Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Xuzhou, Jiangsu Province, China.
Hua LiuNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, China.
Jian-Ping CaoNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, China.
Yu-Juan ShenNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention; Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, China. amyshyj12@163.com.
Kui-Yang ZhengJiangsu Key Laboratory of Immunity and Metabolism, Department of Pathogenic Biology and Immunology, Xuzhou Medical University, Xuzhou, Jiangsu Province, China. zky02@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExcretory-secretory products released by Echinococcus granulosus protoscoleces (EgPSC-ESPs) are well-known to regulate T cell responses. However, their direct influence on the differentiation of B cell subsets remains largely elusive. This study investigated the effects of EgPSC-ESPs on the differentiation of IL-10-producing B cells (B10), and explored the possible role of Toll-like receptor 2 (TLR-2) signaling in this process.

resultsIn comparison to phosphate buffered saline (PBS), B cells exposed to the excretory-secretory products (ESPs) generated higher percentages of B10 cells, with higher expression of IL-10 mRNA, and larger amount of IL-10 production, which were in a dose dependent way. The mRNA and protein expression of TLR-2 in the ESPs-stimulated B cells were significantly higher than those in PBS, which was consistent to the results in B cells isolated from EgPSC infected mice. Moreover, TLR-2

conclusionOverall, this study revealed that TLR-2 signaling was required for B10 induction mediated by EgPSC-ESPs, which might be an immunomodulatory target against the parasite infection.

Indexed as

AnimalsAntigens, HelminthB-Lymphocyte SubsetsEchinococcosisEchinococcus granulosusInterleukin-10Mice, Inbred C57BLPhosphatidylinositol 3-KinaseProto-Oncogene Proteins c-aktPTEN PhosphohydrolaseToll-Like Receptor 2Antigens, HelminthIL10 protein, mouseInterleukin-10Phosphatidylinositol 3-KinaseProto-Oncogene Proteins c-aktPTEN PhosphohydrolasePten protein, mouseTlr2 protein, mouseToll-Like Receptor 2B10 cellsEchinococcus granulosus protoscolecesExcretory-secretory productsPI3KPTENTLR-2

Identifiers

PMID30355335
PMCPMC6201587

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.