Evidence map›Paper›PMID 32489713›Full record

ReviewAging and disease2020

Implications of Long Non-Coding RNAs in Age-Altered Proteostasis.

Cristina-Sorina Catana, Catalina-Angela Crișan, Dana Opre, Ioana Berindan-Neagoe

Open access · goldAbstract readReview
In one paragraph

Review in Aging and disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 42% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Liuwei Dihuang Prevents Human Umbilical Vein Endothelial Cells SenescenceCombinatorial chemistry & high throughput screening · 2026
    Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. 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 1 country.

Cristina-Sorina Catana1Department of Medical Biochemistry, "Iuliu Haţieganu" University of Medicine and Pharmacy Cluj-Napoca, Cluj-Napoca, Romania.
Catalina-Angela Crișan2Department of Neurosciences, "Iuliu Haţieganu" University of Medicine and Pharmacy Cluj-Napoca, Cluj-Napoca, Romania.
Dana Opre3Department of Psychology, Babeș-Bolyai University, Cluj-Napoca, Romania.
Ioana Berindan-Neagoe4MEDFUTURE - Research Center for Advanced Medicine, Cluj-Napoca, Romania.
Babeș-Bolyai University · ROIuliu Hațieganu University of Medicine and Pharmacy · RO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review aims to summarize the current knowledge on how lncRNAs are influencing aging and cancer metabolism. Recent research has shown that senescent cells re-enter cell-cycle depending on intrinsic or extrinsic factors, thus restoring tissue homeostasis in response to age-related diseases (ARDs). Furthermore, maintaining proteostasis or cellular protein homeostasis requires a correct quality control (QC) of protein synthesis, folding, conformational stability, and degradation. Long non-coding RNAs (lncRNAs), transcripts longer than 200 nucleotides, regulate gene expression through RNA-binding protein (RBP) interaction. Their association is linked to aging, an event of proteostasis collapse. The current review examines approaches that lead to recognition of senescence-associated lncRNAs, current methodologies, potential challenges that arise from studying these molecules, and their crucial implications in clinical practice.

Indexed as

age-related diseasescancer metabolismHOTAIRlnc RNAproteostasis

Identifiers

PMID32489713
PMCPMC7220293
OpenAlexW3025222617

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.