Evidence map›Paper›PMID 41674990›Full record

ArticleTranslational cancer research2026

Total flavonoids extracted from

Xiaoyan Li, Xiaoqiang Zhang, Junchao Xue

Abstract read
In one paragraph

Article in Translational cancer research, 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

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

3 authors.

Xiaoyan LiDepartment of General Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine Linping Campus, Hangzhou, China.
Xiaoqiang ZhangDepartment of Infectious Disease and Hepatology, The Second Affiliated Hospital of Zhejiang University School of Medicine Linping Campus, Hangzhou, China.
Junchao XueDepartment of Pharmacy, Tongde Hospital of Zhejiang Province, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Flavonoids are primary bioactive components of Methods: A nude mouse model of subcutaneous tumor formation of hepatocellular carcinoma was established. Following PCPTF treatment, the pathological changes, tumor cell proliferation and apoptosis, serum inflammatory factors and oxidative stress levels, and the levels of Janus kinase 2 (JAK2) and signal transducer and activator of transcription 3 (STAT3) proteins in tumor tissues were detected. Lipopolysaccharides (LPS) was applied to construct liver cancer cell inflammation models in vitro. After treatment of PCPTF and JAK2 agonist coumermycin A1 (CA1) in the cells, protein levels, cell proliferation, inflammation, and oxidative stress were evaluated to explore the mechanism of PCPTF in improving liver cancer. Results: In mice with liver cancer, PCPTF treatment inhibited tumor growth, improved the pathological changes, down-regulated interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), malondialdehyde (MDA), reactive oxygen species (ROS), up-regulated superoxide dismutase (SOD), and suppressed JAK2 and STAT3 phosphorylation. In liver cancer cells, PCPTF blocked the JAK2/STAT3 pathway, proliferation, and the release of inflammatory factors, regulated oxidative stress, and promoted apoptosis. However, CA1 reversed the effect of PCPTF on liver cancer cells. Conclusions: PCPTF suppresses the progression of liver cancer by ameliorating oxidative stress and inflammatory response, primarily through the regulation of the JAK2/STAT3 signaling pathway.

Indexed as

inflammationLiver canceroxidative stresstotal flavonoids extracted from Penthorum chinense Pursh (PCPTF)

Identifiers

PMID41674990
PMCPMC12885919

What OpenQuestion holds

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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 OpenQuestion graph.