Evidence map›Paper›PMID 31285998›Full record

ReviewBiomolecular detection and quantification2019

For what factors should we normalize urinary extracellular mRNA biomarkers?

Pradeep Moon Gunasekaran, James Matthew Luther, James Brian Byrd

Abstract readReview
In one paragraph

Review in Biomolecular detection and quantification, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
  2. Article
  3. Review
  4. Article
  5. Article
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  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Urinary microRNA and mRNA in Tumors.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  14. Article
  15. Article
  16. Tissue-Engineered Human Myobundle System as a Platform for Evaluation of Skeletal Muscle Injury Biomarkers.Toxicological sciences : an official journal of the Society of Toxicology · 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

3 authors.

Pradeep Moon GunasekaranDepartment of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA.
James Matthew LutherDepartment of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA.
James Brian ByrdDepartment of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA.

Funding

A Novel Biomarker of Mineralocorticoid Receptor ActivationK23HL128909 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BYRD, JAMES BRIAN · 2016 to 2020
$972k
NHLBI NIH HHS K23 HL128909
6 · The paper itself

Abstract

mRNA is a critical biomolecule involved in the manifestation of the genetic code into functional protein molecules. Its critical role in the central dogma has made it a key target in many studies to determine biomarkers and drug targets for numerous diseases. Currently, there is a growing body of evidence to suggest that RNA molecules around the size of full-length mRNA transcripts can be assayed in the supernatant of human urine and urinary extracellular mRNA could provide information about transcription in cells of urogenital tissues. However, the optimal means of normalizing these signals is unclear. In this paper, we describe relevant first principles as well as research findings from our lab and other labs toward normalization of urinary extracellular mRNA.

Indexed as

BiomarkersCancerCardiometabolicCreatinineExosomesExRNAExtracellular RNAExtracellular vesiclesmRNASpecific gravityUrinaryUrine

Identifiers

PMID31285998
PMCPMC6591792

What OpenQuestion holds

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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.