Evidence map›Paper›PMID 34266430›Full record

ArticleJournal of biomedical science2021

Downregulating lncRNA NEAT1 induces proliferation and represses apoptosis of ovarian granulosa cells in polycystic ovary syndrome via microRNA-381/IGF1 axis.

Jingran Zhen, Jiangli Li, Xia Li, Xue Wang, Yaling Xiao, Zhengyi Sun, Qi Yu

RetractedOpen access · diamondAbstract readRetracted Publication
In one paragraph

Article in Journal of biomedical science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
10.8field-weighted citation impact, top 1% 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

21 citing papers in PubMed, 52 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Cancers · 2021
    Review
  20. Roles of Noncoding RNA in Reproduction.Frontiers in genetics · 2021
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Jingran ZhenDepartment of Gynecological Endocrinology and Reproduction Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, 41 Damucang Hutong, Xicheng, Beijing, China.
Jiangli LiDepartment of Obstetrics and Gynecology, Zhongguancun Hospital, Beijing, 100080, China.
Xia LiCommunity Health Service Center, Beijing Forestry University, Beijing, 100053, China.
Xue WangDepartment of Gynecological Endocrinology and Reproduction Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, 41 Damucang Hutong, Xicheng, Beijing, China.
Yaling XiaoDepartment of Gynecological Endocrinology and Reproduction Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, 41 Damucang Hutong, Xicheng, Beijing, China.
Zhengyi SunDepartment of Gynecological Endocrinology and Reproduction Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, 41 Damucang Hutong, Xicheng, Beijing, China. sunzhengyi@263.net.
Qi YuDepartment of Gynecological Endocrinology and Reproduction Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, 41 Damucang Hutong, Xicheng, Beijing, China. YYYuqi577@163.com.
Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveResearchers have revealed the combined functions of long noncoding RNAs (lncRNAs) and microRNA (miRNAs) in polycystic ovary syndrome (PCOS). This study aimed to understand the role of nuclear-enriched abundant transcript 1 (NEAT1) and miR-381 involving insulin-like growth factor 1 (IGF1) in PCOS.

methodsPCOS rat model was established by dehydroepiandrosterone induction. NEAT1, miR-381 and IGF1 expression in ovarian granulosa cells of PCOS patients and ovarian tissues of PCOS rats were tested. Bioinformatics website and dual luciferase reporter gene assay were utilized to verify the relationship between NEAT1 and miR-381 and that between miR-381 and IGF1. Levels of sex hormone, pathological changes and ovarian granulosa cell apoptosis in ovarian tissues of PCOS rats were detected. Ovarian granulosa cell proliferation and apoptosis were analyzed in vitro.

resultsNEAT1 and IGF1 expression increased while miR-381 expression decreased in the ovarian granulosa cells of patients with PCOS and the ovarian tissues of PCOS rats. In in vivo experiments, interference with NEAT1 improved the levels of sex hormones, alleviated pathological changes and suppressed ovarian granulosa cell apoptosis in the ovarian tissues of PCOS rats. In in vitro cell experiments, interference with NEAT1 suppressed apoptosis and enhanced cell proliferation of ovarian granulosa cells. NEAT1 interference-mediated effect would be reversed by up-regulating miR-381. NEAT1 acted as a ceRNA to adsorb miR-381 to target IGF1. Overexpression of IGF1 reversed the inhibitory effect of miR-381 on ovarian granulosa cell apoptosis.

conclusionInterference with NEAT1 increases miR-381 and reduces IGF1 levels, effectively improving the levels of sex hormones and reducing the pathological damage of ovarian tissue in rats with PCOS.

Indexed as

Down-RegulationAnimalsApoptosisCell ProliferationFemaleGranulosa CellsMicroRNAsOvaryPolycystic Ovary SyndromeRatsRats, WistarRNA, Long NoncodingMicroRNAsMIRN381 microRNA, ratRNA, Long NoncodingApoptosisInsulin-like growth factor 1Long non-coding RNA nuclear-enriched abundant transcript 1MicroRNA-381Ovarian granulosa cellsPolycystic ovary syndromeProliferation

Identifiers

PMID34266430
PMCPMC8281489
OpenAlexW3181680807

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.