Evidence map›Paper›PMID 27257368›Full record

ArticleBiomarker insights2016

Precision-Cut Kidney Slices as a Tool to Understand the Dynamics of Extracellular Matrix Remodeling in Renal Fibrosis.

Federica Genovese, Zsolt S Kàrpàti, Signe H Nielsen, Morten A Karsdal

Open access · goldAbstract read
In one paragraph

Article in Biomarker insights, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 16% 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

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. A practical toolbox for modelling fibrosis in vitro.Nature biomedical engineering · 2026
    Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Murine Precision-Cut Kidney Slices as anFrontiers in physiology · 2017
    Article
  7. 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 1 institution in 1 country.

Federica GenoveseNordic Bioscience, Herlev, Denmark.
Zsolt S KàrpàtiNordic Bioscience, Herlev, Denmark.
Signe H NielsenNordic Bioscience, Herlev, Denmark.
Morten A KarsdalNordic Bioscience, Herlev, Denmark.
Nordic Bioscience (Denmark) · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to set up an ex vivo model for renal interstitial fibrosis in order to investigate the extracellular matrix (ECM) turnover profile in the fibrotic kidney. We induced kidney fibrosis in fourteen 12-week-old male Sprague Dawley rats by unilateral ureteral obstruction (UUO) surgery of the right ureter. The left kidney (contralateral) was used as internal control. Six rats were sham operated and used as the control group. Rats were terminated two weeks after the surgery; the kidneys were excised and precision-cut kidney slices (PCKSs) were cultured for five days in serum-free medium. Markers of collagen type I formation (P1NP), collagen type I and III degradation (C1M and C3M), and α-smooth muscle actin (αSMA) were measured in the PCKS supernatants by enzyme-linked immunosorbent assay. P1NP, C1M, C3M, and α-SMA were increased up to 2- to 13-fold in supernatants of tissue slices from the UUO-ligated kidneys compared with the contralateral kidneys (P < 0.001) and with the kidneys of sham-operated animals (P < 0.0001). The markers could also reflect the level of fibrosis in different animals. The UUO PCKS ex vivo model provides a valuable translational tool for investigating the extracellular matrix remodeling associated with renal interstitial fibrosis.

Indexed as

extracellular matrixex vivokidney fibrosisPCKSUUO

Identifiers

PMID27257368
PMCPMC4877083
OpenAlexW2400270437

What OpenQuestion holds

Textmetadata
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.