Evidence map›Paper›PMID 32588690›Full record

ArticleThe Journal of international medical research2020

c-Jun NH2-terminal kinase suppression significantly inhibits the growth of transplanted breast tumors in mice.

You-Cheng Huang, Wu Pan, Hui Li, Tao Yan

Open access · goldAbstract read
In one paragraph

Article in The Journal of international medical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 50% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
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 at 1 institution in 1 country.

You-Cheng HuangDepartment of Breast Surgery, Chengdu Second People's Hospital, Chengdu 610011, China.ORCID https://orcid.org/0000-0002-6552-7052
Wu PanDepartment of Breast Surgery, Chengdu Second People's Hospital, Chengdu 610011, China.
Hui LiDepartment of Breast Surgery, Chengdu Second People's Hospital, Chengdu 610011, China.
Tao YanDepartment of Breast Surgery, Chengdu Second People's Hospital, Chengdu 610011, China.
Chengdu Second People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe current study investigated the effect of c-Jun NH2-terminal kinase (JNK) expression on the growth of transplanted breast cancer tumors in mice.

methodsA breast cancer transplantation model was established in BALB/c mice, which were then treated with SP600125 (30 mg/kg) for 24 days. After sacrificing the mice, the inhibitory effects of SP600125 on breast cancer growth were calculated by weighing tumors. Moreover, vascular endothelial growth factor (VEGF) expression and the tumor microvascular density (MVD) were evaluated via immunohistochemistry. Cell apoptosis was also examined using a TUNEL kit.

resultsCompared with the findings in the control group, SP600125 treatment (30 mg/kg) obviously suppressed tumor growth during the 15-day observation period. SP600125 treatment markedly inhibited JNK mRNA expression. Furthermore, VEGF protein expression (50%

conclusionInhibition of JNK signaling can significantly suppress the growth of transplanted breast tumors in mice.

Indexed as

JNK Mitogen-Activated Protein KinasesVascular Endothelial Growth Factor AAnimalsApoptosisMiceMice, Inbred BALB CJNK Mitogen-Activated Protein KinasesVascular Endothelial Growth Factor Aapoptosisbreast cancerc-Jun NH2-terminal kinasemicrovascular densitySP600125transplantation modelvascular endothelial growth factor

Identifiers

PMID32588690
PMCPMC7325461
OpenAlexW3038058109

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.