Evidence map›Paper›PMID 40787625›Full record

ArticleFrontiers in cell and developmental biology2025

miR-383-3p and miR-6951-3p activate cell proliferation through the regulation of genes related to hypertelorism.

Chihiro Iwaya, Junichi Iwata

Abstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Chihiro IwayaDepartment of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, MI, United States.
Junichi IwataDepartment of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, MI, United States.

Funding

Deep learning for decoding genetic regulation and cellular maps in craniofacial developmentR01DE030122 · NIDCR · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI IWATA, JUNICHI, ZHAO, ZHONGMING · 2021 to 2023
$1.7M
NIDCR NIH HHS R01 DE030122
6 · The paper itself

Abstract

Hypertelorism, characterized by an abnormal increase in the distance between the eyes, is often associated with various congenital birth defects. While there is increasing evidence suggesting common underlying mechanisms for hypertelorism, the role of microRNAs (miRNAs)-short noncoding RNAs that suppress target genes by inhibiting translation and degrading mRNA-in the condition's pathogenesis remains unclear. This study aimed to identify the miRNAs associated with hypertelorism in mice. By searching the Mouse Genome Informatics (MGI) database and reviewing full-text references, we identified a total of 31 genes potentially related to hypertelorism. Advanced bioinformatics analyses revealed nine miRNAs that may regulate these genes. We experimentally evaluated candidate miRNAs in assays of cell proliferation and target gene regulation in primary cells isolated from developing frontonasal process mouse embryonic frontonasal mesenchymal and O9-1 cells, a murine neural crest cell line. Our findings indicated that overexpression of either miR-383-3p or miR-6951-3p stimulated cell proliferation, whereas miR-7116-3p and miR-124-3p did not have this effect. Additionally, we confirmed that miR-383-3p and miR-6951-3p regulated the expression of a set of hypertelorism-related genes in a dose-dependent manner. These results suggest that miR-383-3p and miR-6951-3p play significant roles in the development of hypertelorism.

Indexed as

birth defectscranial neural crest cellscraniofacial developmenthypertelorismMicroRNAs

Identifiers

PMID40787625
PMCPMC12333593

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Registered trials

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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.