Evidence map›Paper›PMID 30483246›Full record

ReviewFrontiers in immunology2018

Unraveling SSc Pathophysiology; The Myofibroblast.

Arjan van Caam, Madelon Vonk, Frank van den Hoogen, Peter van Lent, Peter van der Kraan

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 1 pooled it
–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

100 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  14. The complexities of cell death mechanisms: a new perspective in systemic sclerosis therapy.Apoptosis : an international journal on programmed cell death · 2025
    Review
  15. Review
  16. Article
  17. Review
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  19. p53 and the E3 Ubiquitin Ligase MDM2 in Glaucomatous Lamina Cribrosa Cells.International journal of molecular sciences · 2024
    Article
  20. Article

40 more citing papers are in PubMed but not listed here.

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

5 authors.

Arjan van CaamExperimental Rheumatology, Radboudumc, Nijmegen, Netherlands.
Madelon VonkDepartment of Rheumatology, Radboudumc, Nijmegen, Netherlands.
Frank van den HoogenDepartment of Rheumatology, Radboudumc, Nijmegen, Netherlands.
Peter van LentExperimental Rheumatology, Radboudumc, Nijmegen, Netherlands.
Peter van der KraanExperimental Rheumatology, Radboudumc, Nijmegen, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systemic sclerosis (SSc) is a severe auto-immune disease, characterized by vasculopathy and fibrosis of connective tissues. SSc has a high morbidity and mortality and unfortunately no disease modifying therapy is currently available. A key cell in the pathophysiology of SSc is the myofibroblast. Myofibroblasts are fibroblasts with contractile properties that produce a large amount of pro-fibrotic extracellular matrix molecules such as collagen type I. In this narrative review we will discuss the presence, formation, and role of myofibroblasts in SSc, and how these processes are stimulated and mediated by cells of the (innate) immune system such as mast cells and T helper 2 lymphocytes. Furthermore, current novel therapeutic approaches to target myofibroblasts will be highlighted for future perspective.

Indexed as

ApoptosisCollagen Type ICytokinesExtracellular MatrixHumansImmunity, InnateKiller Cells, NaturalMacrophagesMast CellsMyofibroblastsNeutrophilsScleroderma, SystemicTh2 CellsCollagen Type ICytokinescytokineimmune systemmyofibroblastsystemic sclerodermatreatment

Identifiers

PMID30483246
PMCPMC6242950

What OpenQuestion holds

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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.