ArticleFrontiers in pharmacology2022
Article in Frontiers in pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed, 11 citations in OpenAlex.
- Artificial Intelligence- and Machine Learning-Assisted Structure-Based Virtual Screening of Compounds That Target 15PGDH.Pharmaceutics · 2026Article
- A seven-gene diagnostic and prognostic signature for papillary thyroid carcinoma.Discover oncology · 2026Article
- The integration of machine learning into traditional Chinese medicine.Journal of pharmaceutical analysis · 2025Review
- Multi-level association rule mining and network pharmacology to identify the polypharmacological effects of herbal materials and compounds in traditional medicine.Briefings in bioinformatics · 2025Article
- Computer-assisted discovery of natural inhibitors for platelet-derived growth factor alpha as novel therapeutics for thyroid cancer.Frontiers in pharmacology · 2024Article
- A general prediction model for compound-protein interactions based on deep learning.Frontiers in pharmacology · 2024Article
- Screening and Analysis of Possible Drugs Binding to PDGFRα: A Molecular Modeling Study.International journal of molecular sciences · 2023Article
- Machine learning in TCM with natural products and molecules: current status and future perspectives.Chinese medicine · 2023Review
- A novel gene signature related to focal adhesions for distinguishing and predicting the prognosis of lung squamous cell carcinoma.Frontiers in medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aberrant activation of platelet-derived growth factor receptor α (PDGFRA) has been implicated in tumorigenesis and radioiodine resistance of thyroid cancer, indicating its therapeutic potential. In the present study, we confirmed the association between PDGFRA and radioiodine resistance in thyroid cancer using bioinformatics analysis and constructed a prediction model of PDGFRA inhibitors using machine learning and molecular docking approaches. We then performed a virtual screening of a traditional Chinese medicine (TCM) derived compound library and successfully identified 4',5,7-trimethoxyflavone as a potential PDGFRA inhibitor. Further characterization revealed a significant inhibitory effect of 4',5,7-trimethoxyflavone on PDGFRA-MAPK pathway activation, and that it could upregulate expression of sodium iodide symporter (NIS) as well as improve radioiodine uptake capacity of radioiodine-refractory thyroid cancer (RAIR-TC), suggesting it a potential drug lead for the development of new RAIR-TC therapy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.