Evidence map›Paper›PMID 40128073›Full record

ArticleMedicine2025

Mechanistic insights into the anticancer effects of Pinellia ternata (Thunb.) Ten. ex Breitenb. and Ligusticum chuanxiong Hort. ex S. H. Qiu & al. on papillary thyroid carcinoma: A network pharmacology approach.

Gang Wang, Jing Chen, Xiangding Kong, Kuanyu Wang

Abstract read
In one paragraph

Article in Medicine, 2025. 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

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

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

4 authors.

Gang WangThe First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang, China.
Jing Chen
Xiangding Kong

Funding

Scientific Research Project of Chinese Medicine in Heilongjiang Province ZHY2022-002
6 · The paper itself

Abstract

This study aims to elucidate the mechanisms of action of Pinellia ternata (Thunb.) Ten. ex Breitenb. and Ligusticum chuanxiong Hort. ex S. H. Qiu & al. (PAL) in treating papillary thyroid carcinoma (PTC) using bioinformatics and network analysis. Compounds in PAL were identified from the HERB database. Potential herbal targets were predicted using the SwissADME and SwissTargetPrediction platforms. Differential expression genes related to PTC were extracted from the GEO database and protein-protein interaction networks were constructed using the String database and Cytoscape software. Additionally, gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted, and core compound-target interactions were validated through molecular docking. Effective components identified included 32 from Pinellia ternata (Thunb.) Ten. ex Breitenb. and 105 from Ligusticum chuanxiong Hort. ex S. H. Qiu & al., comprising 825 targets. A total of 2155 differential expression genes related to PTC were selected using GEO2R software, with 71 therapeutic targets identified. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses suggest that PAL may exert effects through cancer-related pathways and signal transduction processes. Molecular docking indicated high binding affinity between several compounds and their targets. Specific active components in PAL may act through various mechanisms on PTC, offering scientific bases for further drug development and treatment strategies.

Indexed as

Drugs, Chinese HerbalLigusticumPinelliaPlant ExtractsThyroid Cancer, PapillaryThyroid NeoplasmsComputational BiologyGene OntologyHumansMolecular Docking SimulationNetwork PharmacologyProtein Interaction MapsDrugs, Chinese HerbalPlant Extracts

Identifiers

PMID40128073
PMCPMC11936596

What Socratic holds

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LicenceCC BY
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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 Socratic graph.