Evidence map›Paper›PMID 40084253›Full record

ReviewInternational journal of medical sciences2025

VIM model: a novel model to depict the spatial heterogeneity of the radiation microenvironment.

Yinan Sun, Ying Bi, Xiaohui Wang, Shunfang Liu, Lu Wang

Abstract readReview
In one paragraph

Review in International journal of medical sciences, 2025. 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

5 authors.

Yinan SunDepartment of Cardiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
Ying BiDepartment of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
Xiaohui WangThe Center for Biomedical Research, Department of Respiratory and Critical Care Medicine, NHC Key Laboratory of Respiratory Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
Shunfang LiuDepartment of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
Lu WangDepartment of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiation-induced disease (RID) is the most important factor limiting the radiotherapy dose for malignant tumors, especially for patients with organ insufficiency or chronic inflammation. In this paper, it studied the changes in the microenvironment after radiation exposure from the perspectives of molecular biology, cell biology and histopathology, and first proposed a novel model of the radiation microenvironment to depict radiation-induced spatial heterogeneity. The radiation microenvironment was divided into the VIM model: vascular microenvironment, inflammatory microenvironment, and metabolic microenvironment according to the special cell functions, molecular expressions and pathological structures after radiation. The structural functions of each microenvironment were explored to provide the new theoretical basis for molecular target prediction, radiation damage assessment, prevention and treatment of radiation-induced disease, and using radiation-induced liver injury as a template to depict the VIM model.

Indexed as

Models, BiologicalNeoplasmsRadiation InjuriesTumor MicroenvironmentHumansradiation-induced liver diseaseradiation microenvironmentspatial heterogeneity.VIM model

Identifiers

PMID40084253
PMCPMC11898854

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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.