Evidence map›Paper›PMID 33552682›Full record

ArticleMolecular therapy. Nucleic acids2021

Long non-coding RNA lnc-CCNL1-3:1 promotes granulosa cell apoptosis and suppresses glucose uptake in women with polycystic ovary syndrome.

Jiayu Huang, Jun Zhao, Xueying Geng, Weiwei Chu, Shang Li, Zi-Jiang Chen, Yanzhi Du

Open access · goldAbstract read
In one paragraph

Article in Molecular therapy. Nucleic acids, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

32 citing papers in PubMed, 55 citations in OpenAlex.

  1. Review
  2. Review
  3. The roles of RNA-binding proteins in ovarian aging.Journal of assisted reproduction and genetics · 2026
    Review
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  20. Food science & nutrition · 2023
    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

7 authors at 2 institutions in 1 country.

Jiayu HuangCenter for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200135, China.
Jun ZhaoCenter for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200135, China.
Xueying GengCenter for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200135, China.
Weiwei ChuCenter for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200135, China.
Shang LiCenter for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200135, China.
Zi-Jiang ChenCenter for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200135, China.
Yanzhi DuCenter for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200135, China.
Shanghai Jiao Tong University · CNShandong University · CN

Funding

Functional Electrical Stimulation and Volitional Effort TrainingR21HD085527 · NICHD · KESSLER FOUNDATION, INC. · PI NOLAN, KAREN J. · 2015 to 2016
$413k
NICHD NIH HHS R21 HD085527
6 · The paper itself

Abstract

Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic disease in premenopausal women. Long non-coding RNAs (lncRNAs) constitute important factors in numerous biological processes. However, their roles in PCOS pathogenesis require further clarification. Our study aims to elucidate the roles of lncRNA lnc-CCNL1-3:1 (CCNL) in PCOS.

Indexed as

Follicular atresiaGranulosa cellsInsulin resistanceLncRNAPolycystic ovary syndrome

Identifiers

PMID33552682
PMCPMC7819816
OpenAlexW3111621906

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.