Evidence map›Paper›PMID 42032262›Full record

Reviewnpj biomedical innovations2025

Engineering human endometrial model systems in reproductive health and disease.

Yaqing Wang, Yuxin Guo, Yizhao Yang, Xiaoxin Ma, Jianhua Qin

Abstract readReview
In one paragraph

Review in npj biomedical innovations, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Review
  6. Frontiers in global women's health · 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.

Yaqing WangSchool of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Yuxin GuoDivision of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China.
Yizhao YangMolecular Sciences Research Hub, Imperial College London, London, UK.
Xiaoxin MaDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Jianhua QinSchool of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China. jhqin@dicp.ac.cn.

Funding

National Key R&D Program of China 2022YFA1104700, 2022YFA1205000National Natural Science Foundation of China 32301206Noncommunicable Chronic Diseases-National Science and Technology Major Project 2024ZD0531000
6 · The paper itself

Abstract

The human endometrium is a vital component of the female reproductive system that is essential for fertilization, embryo development and female health. However, due to significant ethical concerns and practical limitations associated with human subject research and species differences in animal models, it is highly required to develop in vitro biomimetic human models to facilitate the understanding of physiology and pathology of endometrium in biomedical research. In this review, we highlight recent progress in bioengineered technologies, including organs-on-chips, organoids, advanced biomaterials and bioprinting that enable the reconstruction of functional endometrial models in vitro. We summarize various bioengineering strategies developed to recapitulate key features of the human endometrium in both healthy and diseased states. Furthermore, we introduce the application of these in vitro models in studies of reproductive biology, pregnancy processes and disease mechanisms. Finally, we discuss current challenges and future opportunities in the development of more sophisticated in vitro human endometrial models for biomedical research.

Identifiers

PMID42032262
PMCPMC13055076

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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.