Evidence map›Paper›PMID 40746411›Full record

ArticleComputational and structural biotechnology journal2025

Towards predicting implant-induced fibrosis: A standardized network model of macrophage-fibroblast interactions.

Matilde Marradi, Martijn van Griensven, Nick R M Beijer, Jan de Boer, Aurélie Carlier

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. The pro-fibrogenic role of SPP1Frontiers in immunology · 2026
    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

5 authors.

Matilde MarradiDepartment of Cell Biology-Inspired Tissue Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, P.O. Box 616, Maastricht, MD 6200, the Netherlands.
Martijn van GriensvenDepartment of Cell Biology-Inspired Tissue Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, P.O. Box 616, Maastricht, MD 6200, the Netherlands.
Nick R M BeijerNational Institute of Public Health and Environment, Centre for Health Protection, Antonie van Leeuwenhoeklaan 9, Bilthoven, MA 3721, the Netherlands.
Jan de BoerDepartment of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, the Netherlands.
Aurélie CarlierDepartment of Cell Biology-Inspired Tissue Engineering, MERLN Institute for Technology-Inspired Regenerative Medicine, Maastricht University, P.O. Box 616, Maastricht, MD 6200, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The foreign body response (FBR) is a complex and multifaceted process that remains incompletely understood, often leading to complications in medical device integration. In this study, we constructed a literature-based network of the FBR and developed it into a semi-quantitative predictive model to better understand its dynamics. The

Indexed as

Fibrotic tissueForeign body responseImmune responseMechanotransductionStandardized ordinary differential equations

Identifiers

PMID40746411
PMCPMC12312070

What OpenQuestion holds

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LicenceCC BY
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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.