Evidence map›Paper›PMID 37521375›Full record

ReviewBiochemistry and biophysics reports2023

MicroRNA targeting: A novel therapeutic intervention for ovarian cancer.

Elmira Roshani Asl, Sajed Sarabandi, Behrouz Shademan, Kourosh Dalvandi, Golshan Sheikhansari, Alireza Nourazarian

Open access · goldAbstract readReview
In one paragraph

Review in Biochemistry and biophysics reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.1field-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

11 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
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  9. Plasma miRNA-146b-3p, -222-3p, -221-5p, -21a-3p Expression Levels andInternational journal of molecular sciences · 2024
    Article
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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

6 authors at 5 institutions in 1 country.

Elmira Roshani AslSocial Determinants of Health Research Center, Saveh University of Medical Sciences, Saveh, Iran.
Sajed SarabandiDepartment of Veterinary, Faculty of Medicine Sciences, Islamic Azad University of Karaj, Karaj, Iran.
Behrouz ShademanStem Cell Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
Kourosh DalvandiMinistry of Health and Medical Education, Health Department, Tehran, Iran.
Golshan SheikhansariStudent Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.
Alireza NourazarianDepartment of Basic Medical Sciences, Khoy University of Medical Sciences, Khoy, Iran.
Tabriz University of Medical Sciences · IRIslamic Azad University, Karaj · IRIslamic Azad University, Khoy Branch · IRMinistry of Health and Medical Education · IRSaveh University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer, a perilous form of cancer affecting the female reproductive system, exhibits intricate communication networks that contribute to its progression. This study aims to identify crucial molecular abnormalities linked to the disease to enhance diagnostic and therapeutic strategies. In particular, we investigate the role of microRNAs (miRNAs) as diagnostic biomarkers and explore their potential in treating ovarian cancer. By targeting miRNAs, which can influence multiple pathways and genes, substantial therapeutic benefits can be attained. In this review we want to shed light on the promising application of miRNA-based interventions and provide insights into the specific miRNAs implicated in ovarian cancer pathogenesis.

Indexed as

BiomarkerDiagnostic biomarkermicroRNAOvarian cancerPrognosticsTherapeutic strategy

Identifiers

PMID37521375
PMCPMC10382632
OpenAlexW4385157286

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.