Evidence map›Paper›PMID 42498990›Full record

ArticleAdvanced healthcare materials2026

A Lightweight, 3D-Printable, Low-Cost, "One-Click" Dorsal Skin Window for High-Quality Long-Term Multimodal Subcutaneous Tumor Imaging.

Iván Cortés Domínguez, Xabier Morales Urteaga, Maider Esparza, Lucía Grande, Ainhoa Urbiola, Cristina Ederra, Tomas Muñoz Santoro, Beatrice Pinci, Alvaro Teijeira, Carlos Ortiz de Solórzano

Abstract read
In one paragraph

Article in Advanced healthcare materials, 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

10 authors.

Iván Cortés DomínguezImaging Platform, CIMA Universidad de Navarra, Pamplona, Spain.ORCID https://orcid.org/0000-0001-5660-7694
Xabier Morales UrteagaImaging Platform, CIMA Universidad de Navarra, Pamplona, Spain.ORCID https://orcid.org/0000-0003-0303-9958
Maider EsparzaImaging Platform, CIMA Universidad de Navarra, Pamplona, Spain.ORCID https://orcid.org/0000-0001-7958-3154
Lucía GrandeImaging Platform, CIMA Universidad de Navarra, Pamplona, Spain.ORCID https://orcid.org/0000-0002-7922-8731
Ainhoa UrbiolaImaging Platform, CIMA Universidad de Navarra, Pamplona, Spain.ORCID https://orcid.org/0009-0004-5189-7011
Cristina EderraImaging Platform, CIMA Universidad de Navarra, Pamplona, Spain.ORCID https://orcid.org/0009-0003-9876-4657
Tomas Muñoz SantoroImaging Platform, CIMA Universidad de Navarra, Pamplona, Spain.ORCID https://orcid.org/0009-0009-8065-3194
Beatrice PinciImmunology and Immunotherapy Program, CIMA Universidad de Navarra, Cancer Center Clínica Universidad de Navarra (CCUN), Pamplona, Spain.ORCID https://orcid.org/0000-0001-6929-2134
Alvaro TeijeiraImmunology and Immunotherapy Program, CIMA Universidad de Navarra, Cancer Center Clínica Universidad de Navarra (CCUN), Pamplona, Spain.ORCID https://orcid.org/0000-0002-7339-4464
Carlos Ortiz de SolórzanoImaging Platform, CIMA Universidad de Navarra, Pamplona, Spain.ORCID https://orcid.org/0000-0001-8720-0205

Funding

Agencia Estatal de Investigación PID2021-122409OB-C22Agencia Estatal de Investigación PID2023-151730OB-I00Agencia Estatal de Investigación PID2024-155384OB-C22Agencia Estatal de Investigación RTI2018-094494-B-C22European Regional Development Fund PID2021-122409OB-C22European Regional Development Fund PID2023-151730OB-I00European Regional Development Fund PID2024-155384OB-C22European Regional Development Fund RTI2018-094494-B-C22European UnionMinisterio de Ciencia, Innovación y Universidades PID2021-122409OB-C22Ministerio de Ciencia, Innovación y Universidades PID2023-151730OB-I00Ministerio de Ciencia, Innovación y Universidades PID2024-155384OB-C22Ministerio de Ciencia, Innovación y Universidades RTI2018-094494-B-C22
6 · The paper itself

Abstract

Intravital microscopy (IVM) using dorsal skinfold chambers (DSCs) enables real-time, high-resolution imaging of the tumor microenvironment. Conventional, metal-based DSC systems often cause animal distress and require technically demanding surgical implantation. To address these challenges and adhere to the 3Rs principles of animal welfare, this study presents a novel, stereolithography (SLA)-based, 3D-printed DSC featuring a lightweight (0.69 g) biocompatible resin structure and a suture-free "one-click" fixation system. This affordable device simplifies surgical installation and minimizes postoperative inflammation, allowing continuous multimodal imaging-IVM, micro-CT, ultrasound, and in vivo fluorescence-for up to four weeks. The system is validated in mice bearing subcutaneous tumors generated from PDAC93-GFP pancreatic tumor organoids implanted in the DSC. Longitudinal, high-resolution imaging successfully tracks tumor expansion, active stromal remodeling characterized by progressive collagen fiber compaction and alignment, and the emergence of a highly tortuous peritumoral vascular network. Furthermore, in vivo tracking in Catchup mice reveals a distinct transition of tumor-associated neutrophils from random acute inflammatory migration to directed tumor-driven chemotaxis. Overall, this ergonomic and robust DSC design provides a highly reliable platform for sustained, high-quality assessment of tumor-stroma-immune interactions and therapeutic responses, while notably improving animal welfare.

Indexed as

Multimodal ImagingPrinting, Three-DimensionalAnimalsCell Line, TumorHumansIntravital MicroscopyMiceTumor Microenvironment3D printinganimal welfaredorsal skinfold chamberintravital microscopymultimodal imagingneutrophil trackingtumor microenvironment

Identifiers

PMID42498990
PMCPMC13495834

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.