Evidence map›Paper›PMID 31216622›Full record

ArticleInternational journal of molecular sciences2019

Analysis of the

Kumaraswamy Naidu Chitrala, Mitzi Nagarkatti, Prakash Nagarkatti, Suneetha Yeguvapalli

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Roles of HOTAIR in lung cancer susceptibility and prognosis.Molecular genetics & genomic medicine · 2020
    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.

Kumaraswamy Naidu ChitralaDepartment of Zoology, Sri Venkateswara University, Tirupati 517502, India. cksnaidu@gmail.com.
Mitzi NagarkattiDepartment of Pathology, Microbiology and Immunology, University of South Carolina School of Medicine, Columbia, SC 29208, USA. Mitzi.Nagarkatti@uscmed.sc.edu.
Prakash NagarkattiDepartment of Pathology, Microbiology and Immunology, University of South Carolina School of Medicine, Columbia, SC 29208, USA. prakash@mailbox.sc.edu.
Suneetha YeguvapalliDepartment of Zoology, Sri Venkateswara University, Tirupati 517502, India. ysuneethareddy4@gmail.com.
Sri Venkateswara University · INUniversity of South Carolina · US

Funding

Indian Council of Medical Research V0.25011/542-HRD/2016-HRNational Institutes of Health P01AT003961National Institutes of Health P20GM103641National Institutes of Health R01AI123947National Institutes of Health R01AI129788National Institutes of Health R01AT006888National Institutes of Health R01MH094755
6 · The paper itself

Abstract

Breast cancer is a leading cancer type and one of the major health issues faced by women around the world. Some of its major risk factors include body mass index, hormone replacement therapy, family history and germline mutations. Of these risk factors, estrogen levels play a crucial role. Among the estrogen receptors, estrogen receptor alpha (ERα) is known to interact with tumor suppressor protein p53 directly thereby repressing its function. Previously, we have studied the impact of deleterious breast cancer-associated non-synonymous single nucleotide polymorphisms (nsnps) rs11540654 (R110P), rs17849781 (P278A) and rs28934874 (P151T) in

Indexed as

Computational BiologyMachine LearningPolymorphism, Single NucleotideEstrogen Receptor alphaHumansMolecular Docking SimulationMolecular Dynamics SimulationMutationNeural Networks, ComputerProtein BindingProtein ConformationProtein Interaction Domains and MotifsStructure-Activity RelationshipTumor Suppressor Protein p53Estrogen Receptor alphaTumor Suppressor Protein p53breast cancerERαgenetic factorsmachine learningsingle nucleotide polymorphismTP53

Identifiers

PMID31216622
PMCPMC6627686
OpenAlexW2950777306

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.