Evidence map›Paper›PMID 42327494›Full record

ArticleBioactive materials2026

An AI-integrated organoid platform enables high-throughput functional evaluation of bioactive metal ions.

Yi Shao, Yongfeng Wang, Yan Wang, Jingru Xu, Ping Li, Jiaqi Zhao, Xuan Du, Xueqiang Liu, Shihui Xu, Lu Wang and 12 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bioactive 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

22 authors.

Yi ShaoJiangsu Key Laboratory of Advanced Metallic Materials, School of Materials Science and Engineering, Southeast University, Nanjing, Jiangsu, 211189, China.
Yongfeng WangInstitute of Biomedical Devices (Suzhou), Southeast University, Suzhou, Jiangsu, 215163, China.
Yan WangInstitute of Microphysiological Systems, State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Jingru XuInstitute of Biomedical Devices (Suzhou), Southeast University, Suzhou, Jiangsu, 215163, China.
Ping LiInstitute of Biomedical Devices (Suzhou), Southeast University, Suzhou, Jiangsu, 215163, China.
Jiaqi ZhaoInstitute of Biomedical Devices (Suzhou), Southeast University, Suzhou, Jiangsu, 215163, China.
Xuan DuInstitute of Biomedical Devices (Suzhou), Southeast University, Suzhou, Jiangsu, 215163, China.
Xueqiang LiuInstitute of Biomedical Devices (Suzhou), Southeast University, Suzhou, Jiangsu, 215163, China.
Shihui XuInstitute of Biomedical Devices (Suzhou), Southeast University, Suzhou, Jiangsu, 215163, China.
Lu WangJiangsu Clinical Innovation Center for Anorectal Diseases of T.C.M, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, 210022, China.
Zhimin FanJiangsu Clinical Innovation Center for Anorectal Diseases of T.C.M, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, 210022, China.
Yuxi YangCenter for Medical Device Evaluation, National Medical Products Administration, Beijing, 100076, China.
Yajuan GuoCenter for Medical Device Evaluation, National Medical Products Administration, Beijing, 100076, China.
Kuan ChenCenter for Medical Device Evaluation, National Medical Products Administration, Beijing, 100076, China.
Cheng WangJiangsu Key Laboratory of Advanced Metallic Materials, School of Materials Science and Engineering, Southeast University, Nanjing, Jiangsu, 211189, China.
Yue ZhangInstitute of Metallic Biomaterials, Helmholtz-Zentrum Hereon, Max-Planck-Str.1, Geesthacht, 21502, Germany.
Feng XueJiangsu Key Laboratory of Advanced Metallic Materials, School of Materials Science and Engineering, Southeast University, Nanjing, Jiangsu, 211189, China.
Jianjun GeInstitute of Biomedical Devices (Suzhou), Southeast University, Suzhou, Jiangsu, 215163, China.
Chenglin ChuJiangsu Key Laboratory of Advanced Metallic Materials, School of Materials Science and Engineering, Southeast University, Nanjing, Jiangsu, 211189, China.
Zaozao ChenInstitute of Microphysiological Systems, State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Zhongze GuInstitute of Microphysiological Systems, State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Jing BaiJiangsu Key Laboratory of Advanced Metallic Materials, School of Materials Science and Engineering, Southeast University, Nanjing, Jiangsu, 211189, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Organoids have emerged as one of the most predictive preclinical models in medical research due to their ability to closely retain the genetic and phenotypic characteristics of original tissues. Nevertheless, the application in the systematic evaluation of innovative medical devices (especially biodegradable metals) remains largely unexplored, whereas conventional analytical approaches have significant limitations in data throughput, objectivity, and reproducibility. Recent advances in deep learning-based artificial intelligence (AI) image analysis offer powerful quantitative tools to overcome this bottleneck. In this study, we established a high-throughput quantitative

Indexed as

Artificial intelligenceImage recognitionIon homeostasisMg2+/Zn2+Organoids

Identifiers

PMID42327494
PMCPMC13279892

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.