Evidence map›Paper›PMID 42557295›Full record

ArticleScientific reports2026

Recapitulating gestational progression: a high-throughput 3D bioprinted vascularized human placenta demonstrating stage-specific molecular and functional signatures of human pregnancy.

Cristina Antich, Yu-Chi Chen, Justine Noel, Yanyan Qu, Yuhong Fang, Shayne Frebert, Dingyin Tao, Lauren S Richardson, Ramkumar Menon, Min Jae Song and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 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

11 authors.

Cristina Antich3D Tissue Bioprinting Laboratory, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA.
Yu-Chi Chen3D Tissue Bioprinting Laboratory, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA.
Justine Noel3D Tissue Bioprinting Laboratory, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA.
Yanyan QuAnalytical Chemistry Core, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA.
Yuhong FangAnalytical Chemistry Core, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA.
Shayne Frebert3D Tissue Bioprinting Laboratory, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA.
Dingyin TaoAnalytical Chemistry Core, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA.
Lauren S RichardsonDivision of Maternal-Fetal Medicine & Perinatal Research, Department of Obstetrics & Gynecology, The University of Texas Medical Branch, Galveston, TX, USA.
Ramkumar MenonDivision of Maternal-Fetal Medicine & Perinatal Research, Department of Obstetrics & Gynecology, The University of Texas Medical Branch, Galveston, TX, USA.
Min Jae Song3D Tissue Bioprinting Laboratory, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA.
Marc Ferrer3D Tissue Bioprinting Laboratory, Division of Preclinical Innovation, National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH), Rockville, MD, USA. marc.ferrer@nih.gov.

Funding

3-D biofabricated feto-maternal interface tissue model to determine drug efficacy during pregnancy to reduce the risk of preterm birthUH2TR004117 · NCATS · UNIVERSITY OF TEXAS MED BR GALVESTON · PI HAN, ARUM, MENON, RAMKUMAR · 2022 to 2023
$842k
NCATS NIH HHS UH2 TR004117NIH UH2/UH3 1UH2TR004117-01
6 · The paper itself

Abstract

The placenta is a highly dynamic organ that supports the growth and development of the fetus during gestation. Malfunction of the placenta causes disorders of the pregnancy, including preeclampsia and pre-term birth. The study of the pathophysiology of the placenta throughout pregnancy has been hindered by limited access to the human placenta and lack of predictive cellular and animal models. Here, we describe 3D bioprinted human placenta barrier (hPB) tissue models using primary human trophoblasts and stroma cells that recapitulate the physiology of the human placenta at early and late stages of gestation. These bioprinted vascularized hPB tissue models mimic the architecture and function early and late-stages human placenta, including barrier function, nutrient uptake, transporters activity and hormones secretion. Assembled in a 96-well transwell plate format, this deeply characterized platform provides a robust high-fidelity system for predictive screening of therapeutics and potentially hazardous agents for placenta diseases and safety, and a better understanding of placental pathophysiology.

Indexed as

BioprintingPlacentaPrinting, Three-DimensionalFemaleHumansPregnancyTrophoblasts

Identifiers

PMID42557295
PMCPMC13443107

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.