Evidence map›Paper›PMID 23384043›Full record

ArticleJournal of ovarian research2013

Establishment of a new representative model of human ovarian cancer in mice.

Jianjun Zhang, Xinlian Chen, Gang Shi, Xiaoyan Xie, Hongqian Liu, Xuemei Zhang, Yi Lai, Yan Zuo, Zhong Chen, Shanling Liu and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of ovarian research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.7field-weighted citation impact, top 14% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

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  6. Preclinical humanized mouse model with ectopic ovarian tissues.Experimental and therapeutic medicine · 2014
    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

11 authors at 4 institutions in 2 countries.

Jianjun ZhangLaboratory of Genetics, West China Institute of Maternal and Child Health, West China Second University Hospital, Sichuan University, Chengdu 610041, P, R, China. z.chen2000@yahoo.cn.
Xinlian Chen
Gang Shi
Xiaoyan Xie
Hongqian Liu
Xuemei Zhang
Yi Lai
Yan Zuo
Zhong Chen
Shanling Liu
He Wang
Ministry of Education of the People's Republic of China · CNSichuan University · CNWest China Second University Hospital of Sichuan University · CNUniversity of Utah · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

unlabelled

backgroundIntraperitoneal (i.p.) models that accurately mimic the feature behavior of human ovarian cancer are required to investigate the pathology and therapeutics of the disease. However, established i.p. models which are well-characterized and reliable are few. The purposes of this study are to establish a representative mice i.p. model of the disease and to analyze the consequent pathology.

methodsFresh tumor cells fiom the ascites of patient were injected into female NOD/SCID mice intraperitoneally. Histology, Cytogenetic, immunohistochemistry,tumor markers of CA125,AFP, CA-199 and CEA were used to analyze the model.

resultsThe mice developed marked abdominal distention within 6 months after inoculated with tumor cells from a patient with epithelial ovarian carcinoma. The mice developed clinically evident intraperitoneal tumors and massive ascites containing numerous tumor cells in clumps. CA125 level in our model was high in both serum and ascites supernatants, while levels of other tumor markers, such as AFP, CA-199 and CEA, were normal. Cytogenetic analysis and immunohistochemical staining confirmed its characteristics resembling human epithelial ovarian tumor.

conclusionsThe model described in this paper accurately mimics the features of ovarian tumor, which may be useful for evaluation of new therapeutics.

Identifiers

PMID23384043
PMCPMC3573975
OpenAlexW2114760898

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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 OpenQuestion graph.