Evidence map›Paper›PMID 40810769›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Cuproptosis Signature Would Reveal the Acute-Remitting Pattern in Patients with Neuromyelitis Optica Spectrum Disorder.

Peidong Liu, Ruoyu Li, Xinlin Wang, Hui Li, Huiru Hu, Ang Shen, Wenping Zhu, Jiali Pan, Yanmeng Xing, Weiming Xia and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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

18 authors.

Peidong LiuDepartment of Neurology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.ORCID https://orcid.org/0000-0002-3869-2167
Ruoyu LiDepartment of Neurology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.
Xinlin WangDepartment of Neurosurgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.
Hui LiDepartment of Neurology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.
Huiru HuDepartment of Neurology, Puyang People's Hospital, Puyang, 457000, China.
Ang ShenDepartment of Neurology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.
Wenping ZhuDepartment of Neurology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.
Jiali PanDepartment of Neurology, Sanbo Brain Hospital, Capital Medical University, Beijing, 100093, China.
Yanmeng XingDepartment of Neurology, Zhengzhou Central Hospital, Zhengzhou University, Zhengzhou, 450000, China.
Weiming XiaDepartment of Neurology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.
Henan JiaoDepartment of Neurosurgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.
Di ChenDepartment of Neurosurgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.
Lixin WuDepartment of Neurosurgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.
Li LiuDepartment of Neurology, the First Affiliated Hospital of Xinxiang Medical University, Xinxiang, 453100, China.
Ju LiuDepartment of Neurology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.
Bin YuDepartment of Neurosurgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.
Xianzhi LiuDepartment of Neurosurgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.
Hongbo LiuDepartment of Neurology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, 450000, China.ORCID https://orcid.org/0000-0003-2061-1450

Funding

China Postdoctoral Science Foundation 2024M763005Henan Province Medical Science and Technology Research Project LHGJ20220336National Natural Science Foundation of China 82471379National Natural Science Foundation of China-Henan Joint Fund U2004128
6 · The paper itself

Abstract

The acute-remitting course (the time interval from remission to the next relapse) is a distinct signature of neuromyelitis optica spectrum disorder (NMOSD), which harms patients and perplexes physicians. However, clinically actionable biomarkers to anticipate NMOSD relapse timing are unavailable. Recently, it is found that Cuproptosis-related genes would have an impact on the acute-remitting course in patients with aquaporin-4 (AQP4)-immunoglobulin G antibody positive NMOSD. A machine learning-based algorithm is developed to construct a consensus Cuproptosis-related prognosis risk (CRPR) model, followed by training a proportional hazards model to divide patients with NMOSD into high/low relapse risk groups. The CRPR is related to the clinical symptoms of patients with NMOSD. Finally, a nomogram is created using CRPR to predict the possibility of relapse in new cases of NMOSD. This prediction model can assist physicians and help develop appropriate interventions to prevent disease relapse.

Indexed as

Neuromyelitis OpticaAdultAlgorithmsAquaporin 4BiomarkersFemaleHumansMachine LearningMaleMiddle AgedPrognosisRecurrenceAQP4 protein, humanAquaporin 4Biomarkersacute‐remitting coursecuprotosisNMOSD

Identifiers

PMID40810769
PMCPMC12591142

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.