Evidence map›Paper›PMID 32824113›Full record

ArticlePharmaceutics2020

Noninvasive Assessment of Fibrosis Following Ischemia/Reperfusion Injury in Rodents Utilizing Na Magnetic Resonance Imaging.

Per Mose Nielsen, Christian Østergaard Mariager, Daniel Guldager Kring Rasmussen, Marie Mølmer, Federica Genovese, Morten Asser Karsdal, Christoffer Laustsen, Rikke Nørregaard

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 33% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Assessment of Acute Kidney Injury using MRI.Journal of magnetic resonance imaging : JMRI · 2025
    Review
  3. Review
  4. 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

8 authors at 2 institutions in 1 country.

Per Mose NielsenDepartment of Clinical Medicine, Aarhus University, 8200 Aarhus N, Denmark.
Christian Østergaard MariagerMR Research Centre, Department of Clinical Medicine, Aarhus University, 8200 Aarhus N, Denmark.
Daniel Guldager Kring RasmussenNordic Bioscience A/S, 2730 Herlev, Denmark.ORCID 0000-0003-1642-7482
Marie MølmerDepartment of Clinical Medicine, Aarhus University, 8200 Aarhus N, Denmark.
Federica GenoveseNordic Bioscience A/S, 2730 Herlev, Denmark.
Morten Asser KarsdalNordic Bioscience A/S, 2730 Herlev, Denmark.
Christoffer LaustsenMR Research Centre, Department of Clinical Medicine, Aarhus University, 8200 Aarhus N, Denmark.ORCID 0000-0002-0317-2911
Rikke NørregaardDepartment of Clinical Medicine, Aarhus University, 8200 Aarhus N, Denmark.
Aarhus University · DKNordic Bioscience (Denmark) · DK

Funding

Aarhus Universitets Forskningsfond AUFF-E-2015-FLS-8-69A.P. Møller Foundation 17-L-0524Danish Agency for Science, Technology and Innovation 4135-00023Sundhed og Sygdom, Det Frie Forskningsråd 6110-00231B
6 · The paper itself

Abstract

Fibrosis is often heterogeneously distributed, and classical biopsies do not reflect this. Noninvasive methods for renal fibrosis have been developed to follow chronic kidney diseases (CKD) and to monitor anti-fibrotic therapy. In this study, we combined two approaches to assess fibrosis regression following renal ischemia-reperfusion injury (IRI): magnetic resonance imaging (MRI) and noninvasive extracellular matrix (ECM) biomarkers. MRI was used to evaluate fibrosis in bilateral IRI in rats after reperfusion at 7, 14, and 21 days. This was performed with

Indexed as

interstitial fibrosisMRInoninvasive ECM markersrat modelsrenal IRI

Identifiers

PMID32824113
PMCPMC7463828
OpenAlexW3049011934

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.