Evidence map›Paper›PMID 40572311›Full record

ArticleMicroorganisms2025

Cepharanthine Inhibits

Yuqing Wang, Zenghui Yang, Jingwen Xue, Yitong Wang, Haibo Li, Zhihong Wu, Yizhou Gao

Abstract read
In one paragraph

Article in Microorganisms, 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. Review
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

7 authors.

Yuqing WangSchool of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Zhejiang Provincial Collaborative Innovation Center of Agricultural Biological Resources Biochemical Manufacturing, Hangzhou 310023, China.
Zenghui YangSchool of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Zhejiang Provincial Collaborative Innovation Center of Agricultural Biological Resources Biochemical Manufacturing, Hangzhou 310023, China.
Jingwen XueSchool of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Zhejiang Provincial Collaborative Innovation Center of Agricultural Biological Resources Biochemical Manufacturing, Hangzhou 310023, China.
Yitong WangSchool of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Zhejiang Provincial Collaborative Innovation Center of Agricultural Biological Resources Biochemical Manufacturing, Hangzhou 310023, China.
Haibo LiSchool of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Zhejiang Provincial Collaborative Innovation Center of Agricultural Biological Resources Biochemical Manufacturing, Hangzhou 310023, China.
Zhihong WuSchool of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Zhejiang Provincial Collaborative Innovation Center of Agricultural Biological Resources Biochemical Manufacturing, Hangzhou 310023, China.
Yizhou GaoSchool of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Zhejiang Provincial Collaborative Innovation Center of Agricultural Biological Resources Biochemical Manufacturing, Hangzhou 310023, China.ORCID 0000-0003-3286-3954

Funding

Fundamental Research Funds of Zhejiang University of Science and Technology 2025QN047National College Students Innovation and Entrepreneurship Training Program 202411057028National Natural Science Foundation of China 32402329
6 · The paper itself

Abstract

Cepharanthine (CEP) is a natural bisbenzylisoquinoline alkaloid known for its antibacterial, antiviral, and anti-inflammatory activities. Its antifungal effect, however, has not been well studied. In this work, we used machine learning-based virtual screening with Random Forest, Neural Network, and Support Vector Machine models to identify potential inhibitors of

Indexed as

antifungal activitycepharanthineCFEM domain-containing proteinFusarium solanimachine learningnatural compound

Identifiers

PMID40572311
PMCPMC12196386

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.