Evidence map›Paper›PMID 34341534›Full record

ArticleNature biomedical engineering2021

Computational reconstruction of the signalling networks surrounding implanted biomaterials from single-cell transcriptomics.

Christopher Cherry, David R Maestas, Jin Han, James I Andorko, Patrick Cahan, Elana J Fertig, Lana X Garmire, Jennifer H Elisseeff

Open access · greenAbstract read
In one paragraph

Article in Nature biomedical engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
69citing papers in PubMed, 1 pooled it
8.4field-weighted citation impact, top 1% of its field
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

69 citing papers in PubMed, 1 synthesis or guideline pooled it, 129 citations in OpenAlex.

  1. Pooled it
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  10. Materiobiology in the omics era.Materials today. Bio · 2025
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9 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

8 authors at 3 institutions in 1 country.

Christopher CherryTranslational Tissue Engineering Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
David R MaestasTranslational Tissue Engineering Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Jin HanTranslational Tissue Engineering Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
James I AndorkoTranslational Tissue Engineering Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID http://orcid.org/0000-0002-5101-9495
Patrick CahanDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Elana J FertigDepartment of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Lana X GarmireDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Jennifer H ElisseeffTranslational Tissue Engineering Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA. jhe@jhu.edu.ORCID http://orcid.org/0000-0002-5066-1996
Johns Hopkins University · USBloomberg (United States) · USUniversity of Michigan · US

Funding

Biomaterials-directed regenerative immunotherapiesDP1AR076959 · NIAMS · JOHNS HOPKINS UNIVERSITY · PI ELISSEEFF, JENNIFER H · 2019 to 2023
$5.7M
From intra to intercellular regulatory networks that define cell type identityR35GM124725 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Patrick Cahan · 2017 to 2026
$4.5M
Translational Aging Research Training ProgramT32AG058527 · NIA · JOHNS HOPKINS UNIVERSITY · PI Peter M. Abadir, Esther Seunghee Oh · 2018 to 2026
$4.0M
An Integrative Omics Approach to Identify Biomarkers Related to Preeclampsia and Breast Cancer RisksR01HD084633 · NICHD · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GARMIRE, LANA X · 2016 to 2020
$3.0M
Single cell characterization of the biomaterial immune and stromal responseR01EB028796 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI ELISSEEFF, JENNIFER H · 2020 to 2023
$2.5M
Cancer precision medicine through spatially informative single cell image and transcriptomics data analysisR01LM012373 · NLM · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GARMIRE, LANA X · 2016 to 2024
$2.4M
DR. EPS: Drug Repurposing for Extended Patient SurvivalR01LM012907 · NLM · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GARMIRE, LANA X · 2019 to 2022
$1.0M
An Integrative Bioinformatics Approach to Study Single Cancer Cell HeterogeneityK01ES025434 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI GARMIRE, LANA X · 2014 to 2018
$905k
NIAMS NIH HHS DP1 AR076959NIA NIH HHS T32 AG058527NIBIB NIH HHS R01 EB028796NICHD NIH HHS R01 HD084633NIEHS NIH HHS K01 ES025434NIGMS NIH HHS R35 GM124725NLM NIH HHS R01 LM012373NLM NIH HHS R01 LM012907
6 · The paper itself

Abstract

The understanding of the foreign-body responses to implanted biomaterials would benefit from the reconstruction of intracellular and intercellular signalling networks in the microenvironment surrounding the implant. Here, by leveraging single-cell RNA-sequencing data from 42,156 cells collected from the site of implantation of either polycaprolactone or an extracellular-matrix-derived scaffold in a mouse model of volumetric muscle loss, we report a computational analysis of intercellular signalling networks reconstructed from predictions of transcription-factor activation. We found that intercellular signalling networks can be clustered into modules associated with specific cell subsets, and that biomaterial-specific responses can be characterized by interactions between signalling modules for immune, fibroblast and tissue-specific cells. In a Il17ra

Indexed as

Biocompatible MaterialsForeign-Body ReactionAnimalsExtracellular MatrixMiceProstheses and ImplantsTranscriptomeBiocompatible Materials

Identifiers

PMID34341534
PMCPMC9894531
OpenAlexW3191949154

What OpenQuestion holds

Textmetadata
LicenceTDM
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.