Evidence map›Paper›PMID 28101223›Full record

ArticleOncology letters2016

Modulatory effect of luteolin on redox homeostasis and inflammatory cytokines in a mouse model of liver cancer.

Qiang Zhang, Jie Yang, Jun Wang

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.4field-weighted citation impact, top 21% of its field
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

17 citing papers in PubMed, 43 citations in OpenAlex.

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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 at 1 institution in 1 country.

Qiang ZhangDepartment of General Surgery, Xiangyang Hospital, Affiliated Hospital of Hubei University of Medicine, Xiangyang, Hubei 441000, P.R. China.
Jie YangDepartment of General Surgery, Xiangyang Hospital, Affiliated Hospital of Hubei University of Medicine, Xiangyang, Hubei 441000, P.R. China.
Jun WangDepartment of General Surgery, Xiangyang Hospital, Affiliated Hospital of Hubei University of Medicine, Xiangyang, Hubei 441000, P.R. China.
Hubei University of Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liver cancer is one of the leading causes of cancer-associated mortality worldwide. Due to changes in lifestyle and daily exposure to various chemicals, which may lead to chemical intoxication, liver cancer has become a prominent disease in humans. Chemical-induced carcinogenesis in experimental animals has become a reliable model for the investigation of liver cancer-associated biological alterations that may mimic human hepatic cancer. Liver cancer in BALB/c mice was induced by administering diethylnitrosamine (DN) in drinking water for 6 weeks. Luteolin (LUT) is a flavone that is found in the leaves of the majority of spice-associated plants. In the present study, 20 µg/kg of body weight LUT was administered intraperitoneally every alternate day to treat the DN-induced liver cancer in mice. LUT improved the host system by modifying the levels of α-fetoprotein, enzymatic antioxidants, such as superoxide dismutase and catalase, marker enzymes, such as AST and ALT, and lipid peroxides in the plasma or liver tissue. LUT also reduced the levels of glutathione and the inflammatory cytokines interleukin-2 and interferon-γ in the plasma or liver tissue. These findings augmented the treatment against liver cancer and supported the effective anticancer activity of LUT against DN-induced liver carcinogenesis in mice.

Indexed as

diethylnitrosamineinflammatory cytokineslipid peroxidationliver cancerluteolinmarker enzymes

Identifiers

PMID28101223
PMCPMC5228171
OpenAlexW2533223223

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.