Evidence map›Paper›PMID 33490232›Full record

ArticleBioMed research international2020

Unravelling Structure, Localization, and Genetic Crosstalk of KLF3 in Human Breast Cancer.

Khushbukhat Khan, Sadia Safi, Asma Abbas, Yasmin Badshah, Erum Dilshad, Mehak Rafiq, Kainat Zahra, Maria Shabbir

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

14 citing papers in PubMed, 19 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

8 authors at 2 institutions in 1 country.

Khushbukhat KhanDepartment of Healthcare Biotechnology, Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 44000, Pakistan.ORCID https://orcid.org/0000-0002-9946-9057
Sadia SafiDepartment of Healthcare Biotechnology, Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 44000, Pakistan.
Asma AbbasDepartment of Healthcare Biotechnology, Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 44000, Pakistan.
Yasmin BadshahDepartment of Healthcare Biotechnology, Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 44000, Pakistan.ORCID https://orcid.org/0000-0002-7136-8828
Erum DilshadDepartment of Biological Sciences, Capital University of Science & Technology, Islamabad 44000, Pakistan.
Mehak RafiqResearch Centre for Modelling & Simulation (RCMS), National University of Sciences and Technology, Islamabad 44000, Pakistan.ORCID https://orcid.org/0000-0003-1084-6782
Kainat ZahraDepartment of Healthcare Biotechnology, Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 44000, Pakistan.
Maria ShabbirDepartment of Healthcare Biotechnology, Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 44000, Pakistan.ORCID https://orcid.org/0000-0002-5685-3059
National University of Sciences and Technology · PKCapital University of Science and Technology · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is the most prevailing disease among women. It actually develops from breast tissue and has heterogeneous and complex nature that constitutes multiple tumor quiddities. These features are associated with different histological forms, distinctive biological characteristics, and clinical patterns. The predisposition of breast cancer has been attributed to a number of genetic factors, associated with the worst outcomes. Unfortunately, their behavior with relevance to clinical significance remained poorly understood. So, there is a need to further explore the nature of the disease at the transcriptome level. The focus of this study was to explore the influence of Krüppel-like factor 3 (KLF3), tumor protein D52 (TPD52), microRNA 124 (miR-124), and protein kinase C epsilon (PKC

Indexed as

Breast NeoplasmsKruppel-Like Transcription FactorsAdultBiomarkers, TumorFemaleHumansKruppel-Like Factor 4MicroRNAsMiddle AgedModels, MolecularNeoplasm ProteinsProtein Kinase C-epsilonSignal TransductionTranscriptomeBiomarkers, TumorKLF3 protein, humanKLF4 protein, humanKruppel-Like Factor 4Kruppel-Like Transcription FactorsMicroRNAsMIRN124 microRNA, humanNeoplasm ProteinsProtein Kinase C-epsilonTPD52 protein, human

Identifiers

PMID33490232
PMCPMC7803292
OpenAlexW3116480559

What Socratic 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 Socratic graph.