Evidence map›Paper›PMID 42027973›Full record

ArticleTanaffos2025

New Insights into Pulmonary Arterial Hypertension Treatment with Non-Coding RNAs: What is the Best Option, microRNAs or Small-Interfering RNAs?

Hannaneh Yousefi-Koma, Babak Sharif-Kashani, Abdolreza Mohammadnia, Mahdi Ahmadinia, Shadi Shafaghi

Abstract readLetter
In one paragraph

Article in Tanaffos, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Hannaneh Yousefi-KomaLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Babak Sharif-KashaniLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Abdolreza MohammadniaChronic Respiratory Diseases Research Center, NRITLD, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mahdi AhmadiniaLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Shadi ShafaghiLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Disease (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pulmonary arterial hypertension is a devastating disease that can lead to other serious comorbidities. Heart failure is a major problem in patients with pulmonary arterial hypertension. It usually begins with right-sided heart failure, but in severe or uncontrolled cases, it can progress to left-sided heart failure. Currently, available treatment options do not have desirable effects. Therefore, considering a new treatment strategy is a cardiology priority. Non-coding RNAs, including small interfering RNA and microRNA, are valuable treatment options to study. Several non-coding RNAs have been studied and even approved for treatment in other hard-to-treat diseases. However, deciding which to choose can be complex. That is because these non-coding RNAs can have multiple interaction processes. Therefore, a thorough understanding of pulmonary arterial hypertension's pathological pathways and our target non-coding RNA interaction pathways is crucial. Here, we discuss the potential benefits and harms of these options in treating patients with pulmonary arterial hypertension.

Indexed as

MicroRNANon-coding RNAPulmonary arterial hypertensionPulmonary hypertensionSmall interfering RNA

Identifiers

PMID42027973
PMCPMC13102083

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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.