Evidence map›Paper›PMID 27453073›Full record

ArticleAsian journal of andrology

Unfoldomics of prostate cancer: on the abundance and roles of intrinsically disordered proteins in prostate cancer.

Kevin S Landau, Insung Na, Ryan O Schenck, Vladimir N Uversky

Open access · goldAbstract read
In one paragraph

Article in Asian journal of andrology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. 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 2 institutions in 2 countries.

Kevin S LandauDepartment of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA.
Insung NaDepartment of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA.
Ryan O SchenckDepartment of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA.
Vladimir N UverskyDepartment of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA; USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, Florida 33612, USA; Laboratory of Structural Dynamics, Stability and Folding of Proteins, Institute of Cytology, Russian Academy of Sciences, St. Petersburg, Russia, .
University of South Florida · USInstitute of Cytology · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostatic diseases such as prostate cancer and benign prostatic hyperplasia are highly prevalent among men. The number of studies focused on the abundance and roles of intrinsically disordered proteins in prostate cancer is rather limited. The goal of this study is to analyze the prevalence and degree of disorder in proteins that were previously associated with the prostate cancer pathogenesis and to compare these proteins to the entire human proteome. The analysis of these datasets provides means for drawing conclusions on the roles of disordered proteins in this common male disease. We also hope that the results of our analysis can potentially lead to future experimental studies of these proteins to find novel pathways associated with this disease.

Indexed as

Databases, ProteinHumansIntrinsically Disordered ProteinsMaleProstateProstatic HyperplasiaProstatic NeoplasmsProtein FoldingProteomeIntrinsically Disordered ProteinsProteome

Identifiers

PMID27453073
PMCPMC5000786
OpenAlexW2466723095

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.