Evidence map›Paper›PMID 29343615›Full record

ArticleDisease models & mechanisms2018

Growth of human breast cancers in

Vimala Kaza, Elena Farmaki, Amanda Havighorst, Janet Crossland, Ioulia Chatzistamou, Hippokratis Kiaris

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Disease models & mechanisms, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 44% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

6 authors at 1 institution in 1 country.

Vimala KazaPeromyscus Genetic Stock Center, University of South Carolina, SC 29208, USA.
Elena FarmakiDepartment of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, SC 29208, USA.
Amanda HavighorstDepartment of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, SC 29208, USA.
Janet CrosslandPeromyscus Genetic Stock Center, University of South Carolina, SC 29208, USA.
Ioulia ChatzistamouDepartment of Pathology, Microbiology and Immunology, University of South Carolina School of Medicine, SC 29208, USA.
Hippokratis KiarisPeromyscus Genetic Stock Center, University of South Carolina, SC 29208, USA kiarish@sccp.sc.edu.ORCID 0000-0002-8999-8289
University of South Carolina · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modeling breast cancer in general and hormone-sensitive breast cancer, in particular in mice, has several limitations. These are related to the inbred nature of laboratory mice, and do not allow adequate appreciation of the contribution of the host's genetic heterogeneity in tumor growth. In addition, the naturally low estrogen levels of mice makes estradiol supplementation obligatory for tumor growth. Here, we show that

Indexed as

AnimalsBreast NeoplasmsCell Line, TumorFemaleHumansPeromyscusXenograft Model Antitumor AssaysDiversityHeterogeneityMammary cancerOutbred

Identifiers

PMID29343615
PMCPMC5818077
OpenAlexW2792082815

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.