Evidence map›Paper›PMID 41776305›Full record

ArticleCommunications biology2026

Downfield magnetic resonance signals serve as endogenous imaging biomarkers of nucleotide metabolism in glioma.

Xinyi Zhu, Ke Zhou, Yang Cao, Jiaqiang Zhou, Yingchao Liu, Yibo Liu, Sheng Chen, Min Wang

Abstract read
In one paragraph

Article in Communications biology, 2026. 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

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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Xinyi ZhuKey Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.
Ke ZhouKey Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.
Yang CaoKey Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.
Jiaqiang ZhouDepartment of Endocrinology and Metabolism, Sir Run Run Shaw Hospital, Department of Endocrinology, Zhejiang University, Hangzhou, China.
Yingchao LiuDepartment of Neurosurgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.ORCID http://orcid.org/0000-0002-6656-2511
Yibo LiuDepartment of Neurosurgery, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China.
Sheng ChenDepartment of Neurosurgery, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China.
Min WangKey Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China. wangmin707@zju.edu.cn.ORCID http://orcid.org/0000-0002-1072-5983

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82572290Natural Science Foundation of Zhejiang Province (Zhejiang Provincial Natural Science Foundation) Z25H180012
6 · The paper itself

Abstract

Gliomas, the most common primary brain tumors, exhibit profound metabolic alterations that can be non-invasively probed using magnetic resonance spectroscopy (MRS). Compared to upfield signals in traditional MRS, downfield signals exhibit complex composition with limited understanding of their metabolite origins. Correlating high-throughput metabolic profiles provided by untargeted metabolomics with MRS signals can help elucidate the origins of metabolites in MRS. In this study, upfield and downfield MRS spectra are obtained from control and glioma-bearing male Wistar rats, followed by correlation analysis with untargeted metabolomics from corresponding brain tissues. Here, we show that multiple downfield MRS peaks are significantly elevated in glioma rats and correlate with metabolomic features. Notably, downfield MRS demonstrate the capability of capturing adenosine triphosphate (ATP)-associated nucleotide metabolism. Furthermore, MRS signatures exhibit predictive potential for tumor growth parameters. This work establishes an integrated MRS-metabolomics framework, providing a basis for non-invasively monitoring dynamic metabolic reprogramming and predicting glioma progression.

Indexed as

Biomarkers, TumorBrain NeoplasmsGliomaNucleotidesAnimalsMagnetic Resonance SpectroscopyMaleMetabolomeMetabolomicsRatsRats, WistarBiomarkers, TumorNucleotides

Identifiers

PMID41776305
PMCPMC13066600

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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.