Evidence map›Paper›PMID 37839439›Full record

ArticleAnnals of medicine2023

Expression profiles and functional analysis of tRNA-derived small RNAs in epicardial adipose tissue of patients with heart failure.

Lei Zhao, Yuanshu Peng, Pixiong Su

Open access · goldAbstract read
In one paragraph

Article in Annals of medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.6field-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

10 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
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  5. Exploring the landscape of exosomes in heart failure: a bibliometric analysis.International journal of surgery (London, England) · 2025
    Review
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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 at 1 institution in 1 country.

Lei ZhaoHeart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Yuanshu PengHeart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Pixiong SuHeart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHeart failure is considered an epidemic disease in the modern world. Since it presents as a multifactorial, systemic disease, a comprehensive understanding of the underlying mechanism is essential. Epicardial adipose tissue (EAT) is increasingly recognized to be metabolically active and is able to secrete myriad bioactive molecules, including exosomes carrying tRNA-derived small RNAs (tsRNAs). Mounting evidence has suggested that these specific tsRNAs dynamically impact fundamental cellular processes, but no studies have focused on the influence of tsRNA in EAT on cardiac dysfunction.

methodsTo investigate the regulatory mechanism of tsRNAs of EAT associated with HF, we collected EAT from HF (

resultsWe ultimately identified an expression profile of 343 tsRNAs in EAT. Of those, a total of 24 tsRNAs were significantly differentially expressed between HF and controls: 17 were upregulated and 7 were downregulated (fold change >1.5,

conclusionsOur study profiled tsRNA expression in EAT with HF and identified a comprehensive dimension of potential target genes and tsRNA-mRNA interactions.

Indexed as

Heart FailureRNA, TransferAdipose TissueComputational BiologyHumansRNA, MessengerRNA, MessengerRNA, Transferbioinformaticsepicardial adipose tissueHeart failuresequencingtsRNAs

Identifiers

PMID37839439
PMCPMC10578101
OpenAlexW4387652021

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.