Evidence map›Paper›PMID 41691505›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Developing a Single-Cell Spatial Transcriptomics Workflow for In Vivo Evaluation of Implanted Biomaterials.

Alex H P Chan, Yunfei Hu, Billie Pardavi, Xueying Xu, Angus J Grant, Steven G Wise, Lipin Loo, Richard P Tan

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Alex H P ChanSchool of Medical Sciences, Faculty of Health and Medicine, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia.
Yunfei HuSchool of Medical Sciences, Faculty of Health and Medicine, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia.
Billie PardaviSchool of Medical Sciences, Faculty of Health and Medicine, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia.
Xueying XuSchool of Medical Sciences, Faculty of Health and Medicine, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia.
Angus J GrantSchool of Medical Sciences, Faculty of Health and Medicine, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia.
Steven G WiseSchool of Medical Sciences, Faculty of Health and Medicine, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia.
Lipin LooSchool of Medical Sciences, Faculty of Health and Medicine, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia.
Richard P TanSchool of Medical Sciences, Faculty of Health and Medicine, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia.ORCID https://orcid.org/0000-0002-2670-2882

Funding

Australian Research CouncilNational Health and Medical Research Council APP2019164National Heart FoundationNSW HealthUniversity of Sydney
6 · The paper itself

Abstract

In vivo evaluation of biomaterials largely relies on histology to assess biocompatibility and foreign body responses. While effective for capturing end-stage outcomes, these methods offer limited insight into the cellular mechanisms driving tissue remodeling, hindering efforts to rationally design better biomaterials. Transcriptomics has revolutionized our understanding of gene activity driving cellular function, yet remains underutilized in biomaterial evaluation. Recent advances in high-resolution spatial transcriptomics now enable precise mapping of gene expression within tissue, offering detailed insight into cellular states and spatial organization. To align biomaterial research with advances in spatial biology, we develop a bioinformatics workflow for the Xenium platform to analyze in vivo responses to implanted materials. Applying this workflow to evaluate electrospun polycaprolactone (PCL) scaffolds implanted subcutaneously in mice, we identify spatially distinct macrophage and fibroblast subpopulations with unique gene expression profiles. Spatial analyses show shared phenotypic features between co-localized macrophages and fibroblasts, oriented from the scaffold body to its surface. Gene ontology linked these spatial transitions to functional roles, with immune cell recruitment occurring within the scaffold and fibrosis at the surface. These transitions were not detectable by histology, highlighting spatial transcriptomics as a powerful approach for uncovering cellular dynamics and enabling better biologically-informed design of biomaterials.

Indexed as

Biocompatible MaterialsSingle-Cell AnalysisTissue ScaffoldsTranscriptomeAnimalsFibroblastsForeign-Body ReactionMacrophagesMicePolyestersSpatial TranscriptomicsWorkflowBiocompatible MaterialspolycaprolactonePolyestersbioengineeringbiomaterialsin vivo evaluationpolycaprolactonespatial transcriptomics

Identifiers

PMID41691505
PMCPMC13116268

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.