Evidence map›Paper›PMID 42491657›Full record

ArticleiScience2026

Longitudinal co-activation pattern analysis of menstrual cycle-related brain dynamics in primary dysmenorrhea.

Huiping Liu, Xing Su, Yanran Chen, Huiyan Gan, Meiling Shang, Xiaotong Chi, Youjun Li, Tao Lu, Ming Zhang, Wanghuan Dun and 1 more

Abstract read
In one paragraph

Article in iScience, 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

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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

11 authors.

Huiping LiuDepartment of Medical Imaging, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
Xing SuThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, The Key Laboratory of Neuro-informatics and Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi 710049, China.
Yanran ChenDepartment of Medical Imaging, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
Huiyan GanXi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710049, China.
Meiling ShangDepartment of Medical Imaging, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
Xiaotong ChiXi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710049, China.
Youjun LiThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, The Key Laboratory of Neuro-informatics and Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi 710049, China.
Tao LuDepartment of Medical Imaging, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
Ming ZhangDepartment of Medical Imaging, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
Wanghuan DunRehabilitation Medicine Department, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
Zi-Gang HuangThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, The Key Laboratory of Neuro-informatics and Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi 710049, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Primary dysmenorrhea (PDM) is a chronic pelvic pain condition characterized by recurrent painful phases. While abnormal prostaglandin activity is central to its pain mechanism, and previous studies link PDM to central nervous system alterations associated with prostaglandin F2αlevels and pain intensity, the dynamic evolution of brain networks across the menstrual cycle remains unknown. This study employed the co-activation pattern analysis to investigate dynamic brain network characteristics across the menstrual, periovulatory, and luteal phases. Correlation analyses were performed between CAP metrics, pain scores, and PGF2α levels. Our results revealed that dynamic alterations of brain networks in patients with PDM exhibited trending changes throughout the menstrual cycle. Notably, the default mode network, salience network, sensorimotor network, and central executive network demonstrated significant periodic changes, which correlated with fluctuations in pain and PGF2α levels. This longitudinal study elucidates the dynamic neural mechanisms of patients with PDM, offering insights for early intervention strategies.

Indexed as

NeurosciencePhysiology

Identifiers

PMID42491657
PMCPMC13378385

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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.