Evidence map›Paper›PMID 39959419›Full record

ReviewFrontiers in pharmacology2025

Spatial metabolomics in mental disorders and traditional Chinese medicine: a review.

Chaofang Lei, Jiaxu Chen, Zhigang Chen, Chongyang Ma, Xudong Chen, Xiongxing Sun, Xukun Tang, Jun Deng, Shiliang Wang, Junlin Jiang and 2 more

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 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

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

12 authors.

Chaofang LeiDepartment of Neurology, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine (The Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine), Changsha, China.
Jiaxu ChenSchool of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Zhigang ChenDepartment of Neurology, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, China.
Chongyang MaSchool of Traditional Chinese Medicine, Capital Medical University, Beijing, China.
Xudong ChenDepartment of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.
Xiongxing SunDepartment of Neurology, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine (The Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine), Changsha, China.
Xukun TangDepartment of Neurology, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine (The Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine), Changsha, China.
Jun DengDepartment of Neurology, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine (The Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine), Changsha, China.
Shiliang WangDepartment of Neurology, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine (The Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine), Changsha, China.
Junlin JiangDepartment of Neurology, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine (The Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine), Changsha, China.
Dahua WuDepartment of Neurology, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine (The Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine), Changsha, China.
Le XieDepartment of Neurology, Hunan Provincial Hospital of Integrated Traditional Chinese and Western Medicine (The Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine), Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spatial metabolomics is an emerging technology that integrates mass spectrometry imaging (MSI) with metabolomics, offering a novel visual perspective for traditional metabolomics analysis. This technology enables in-depth analysis in three dimensions: qualitative, quantitative, and localization of metabolites. Spatial metabolomics precisely reflects the characteristics of metabolic network changes in metabolites within entire tissues or specific micro-regions. It provides a detailed understanding of the pharmacodynamic material basis and mechanisms of action. These capabilities suggest that spatial metabolomics can offer significant technical support for studying the complex pathophysiology of mental disorders. Although the mechanisms underlying mental disorders have been reviewed multiple times, this paper provides a comprehensive comparison between traditional metabolomics and spatial metabolomics. It also summarizes the latest progress and challenges of applying spatial metabolomics to the study of mental disorders and traditional Chinese medicine.

Indexed as

DESI-MSIMALDI-MSImass spectrometry imagingmental disordersSIMSspatial metabolomicstraditional Chinese medicine

Identifiers

PMID39959419
PMCPMC11825820

What OpenQuestion holds

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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 OpenQuestion graph.