Evidence map›Paper›PMID 39920417›Full record

ArticleAnnals of nuclear medicine2025

Specific molecular imaging of BALB/c model mice with Graves' ophthalmopathy based on high expression of insulin-like growth factor 1 receptor.

Zhiting Zhang, Ziyu Ma, Xuan Wang, Yaqian Zhou, Ruixin Wu, Yiming Shen, Ning Li, Qiang Jia, Hong Zhang, Wei Li and 1 more

Abstract read
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Article in Annals of nuclear medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Zhiting Zhang *Tianjin Medical University General Hospital, Tianjin, China.
Ziyu Ma *Tianjin Medical University General Hospital, Tianjin, China.
Xuan WangTianjin Medical University General Hospital, Tianjin, China.
Yaqian ZhouTianjin Medical University General Hospital, Tianjin, China.
Ruixin WuTianjin Medical University General Hospital, Tianjin, China.
Yiming ShenTianjin Medical University General Hospital, Tianjin, China.
Ning LiTianjin Medical University General Hospital, Tianjin, China.
Qiang JiaTianjin Medical University General Hospital, Tianjin, China.
Hong ZhangTianjin Chest Hospital, Tianjin, China.
Wei LiTianjin Medical University General Hospital, Tianjin, China. liwei01@tmu.edu.cn.
Wei ZhengTianjin Medical University General Hospital, Tianjin, China. zhengw@tmu.edu.cn.ORCID http://orcid.org/0000-0003-1206-9243

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveAt present, most of the targeted imaging based on insulin-like growth factor 1 receptor (IGF-1R) is for tumor research, and there is no IGF-1R-targeted imaging for Graves' ophthalmopathy(GO). This study aims to develop a peptide probe,

methods99mTc-ZIGF1R:4551-GGGC probe was synthesized using a direct labeling method and its labeling efficiency assessed via instant thin-layer chromatography (ITLC). Western blot analysis confirmed the overexpression of IGF-1R in malignant melanoma B16F10 cells. Subsequent SPECT/CT whole-body imaging of B16F10 tumor-bearing mice evaluated the probe's targeting accuracy. In addition, a GO model was established using an electroporation immunoassay, followed by serological and histopathological examinations. The GO models then underwent 99mTc-ZIGF1R:4551-GGGC SPECT/CT imaging to assess eye-targeted imaging capabilities.

resultsThe peptide probe exhibited a labeling efficiency exceeding 90%. Both GD and GO models were effectively created via electroporation immunoassay. Imaging results indicated significant accumulation and retention of the peptide probes in the tumors of B16F10 tumor-bearing mice. In the GO models, probe uptake was predominantly observed in retrobulbar tissues, contrasting with primary accumulation in the lungs and gastrointestinal tract in normal mice, where only minimal tracer was observed in retrobulbar tissues. Notably, GO mice demonstrated higher probe uptake and prolonged retention.

conclusionThis study successfully established GD and GO models, reducing the duration of the immune cycle. Moreover, a peptide probe targeting IGF-1R was synthesized, enabling specific imaging of retrobulbar tissues in GO models.

Indexed as

Graves OphthalmopathyMolecular ImagingReceptor, IGF Type 1AnimalsCell Line, TumorDisease Models, AnimalFemaleInsulin-Like PeptidesMiceMice, Inbred BALB CSingle Photon Emission Computed Tomography Computed TomographyTissue DistributionInsulin-Like PeptidesReceptor, IGF Type 1Graves’ diseaseGraves’ ophthalmopathyIGF-1RPeptide probeTSHRZIGF1R:4551-GGGC

Identifiers

PMID39920417
PMCPMC11914231

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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.