Evidence map›Paper›PMID 28210941›Full record

ReviewJournal of cell communication and signaling2017

B lymphocytes in renal interstitial fibrosis.

Fengge Zhu, Xueyuan Bai, Xiangmei Chen

Abstract readReview
In one paragraph

Review in Journal of cell communication and signaling, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Molecular and Cellular Mediators of Renal Fibrosis in Lupus Nephritis.International journal of molecular sciences · 2025
    Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Immune Cells in Subretinal Wound Healing and Fibrosis.Frontiers in cellular neuroscience · 2022
    Review
  11. Article
  12. Review
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

3 authors.

Fengge ZhuDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing, China.
Xueyuan BaiDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing, China. xueyuan_bai@163.com.
Xiangmei ChenDepartment of Nephrology, Chinese PLA General Hospital, Chinese PLA Institute of Nephrology, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing, China. xmchen301@126.com.

Funding

National Key Research and Development Program of China 2016YFA0101002National Natural Science Foundation of China 81330019National Natural Science Foundation of China 81570659
6 · The paper itself

Abstract

Fibrosis is defined as an excessive deposition of extracellular matrix (ECM), which leads to the destruction of organ structure and impairment of organ function. Fibrosis occurs not only in kidney but also in lung, liver, heart, and skin. Common pathways of fibrosis are thought to exist. Renal interstitial fibrosis is a complex process that involves multiple molecular signaling and multiple cellular components, in which B cells appear to be one of the emerging important players. B cells may affect fibrosis through cytokine production and through interaction with other cells including fibroblasts, macrophages and T cells. This review summarizes recent research findings of B cells in fibrosis and provides an insight of how the future therapeutics of fibrosis could be developed from a B-cell point of view.

Indexed as

B cellB lymphocyteInflammationRenal interstitial fibrosis

Identifiers

PMID28210941
PMCPMC5559395

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.