Evidence map›Paper›PMID 36203940›Full record

ReviewFrontiers in physiology2022

Non-coding RNAs as potential biomarkers and therapeutic targets in polycystic kidney disease.

Qi Zheng, Glen Reid, Michael R Eccles, Cherie Stayner

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in physiology, 2022. 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
3.2field-weighted citation impact, top 8% 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, 18 citations in OpenAlex.

  1. Review
  2. Gene therapy in polycystic kidney disease: A promising future.Journal of translational internal medicine · 2024
    Article
  3. Review
  4. Article
  5. Review
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.

Qi ZhengDepartment of Pathology, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.
Glen ReidDepartment of Pathology, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.
Michael R EcclesDepartment of Pathology, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.
Cherie StaynerDepartment of Pathology, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.
University of Otago · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polycystic kidney disease (PKD) is a significant cause of end-stage kidney failure and there are few effective drugs for treating this inherited condition. Numerous aberrantly expressed non-coding RNAs (ncRNAs), particularly microRNAs (miRNAs), may contribute to PKD pathogenesis by participating in multiple intracellular and intercellular functions through post-transcriptional regulation of protein-encoding genes. Insights into the mechanisms of miRNAs and other ncRNAs in the development of PKD may provide novel therapeutic strategies. In this review, we discuss the current knowledge about the roles of dysregulated miRNAs and other ncRNAs in PKD. These roles involve multiple aspects of cellular function including mitochondrial metabolism, proliferation, cell death, fibrosis and cell-to-cell communication. We also summarize the potential application of miRNAs as biomarkers or therapeutic targets in PKD, and briefly describe strategies to overcome the challenges of delivering RNA to the kidney, providing a better understanding of the fundamental advances in utilizing miRNAs and other non-coding RNAs to treat PKD.

Indexed as

autosomal dominant polycystic kidney diseaselong non-coding RNAsmiRNAsnon-coding RNAspolycystic kidney disease

Identifiers

PMID36203940
PMCPMC9531119
OpenAlexW4297907001

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.