Evidence map›Paper›PMID 28635106›Full record

ReviewCNS neuroscience & therapeutics2017

Long noncoding RNA and its contribution to autism spectrum disorders.

Jie Tang, Yizhen Yu, Wei Yang

Open access · bronzeAbstract readReview
In one paragraph

Review in CNS neuroscience & therapeutics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 9% 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

40 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Jie TangThe First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.ORCID http://orcid.org/0000-0002-0568-8444
Yizhen YuDepartment of Child and Women Health Care, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Wei YangDepartment of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Huazhong University of Science and Technology · CNFirst Affiliated Hospital of Guangzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies have indicated that long noncoding RNAs (lncRNAs) play important roles in multiple processes, such as epigenetic regulation, gene expression regulation, development, nutrition-related and other diseases, toxic response, and response to drugs. Although the functional roles and mechanisms of several lncRNAs have been discovered, a better understanding of the vast majority of lncRNAs remains elusive. To understand the functional roles and mechanisms of lncRNAs is critical because these transcripts represent the majority of the transcriptional output of the mammalian genome. Recent studies have also suggested that lncRNAs are more abundant in the human brain and are involved in neurodevelopment and neurodevelopmental disorders, including autism spectrum disorders (ASDs). In this study, we review several known functions of lncRNAs and the potential contribution of lncRNAs to ASDs and to other genetic syndromes that have a similar clinical presentation to ASDs, such as fragile X syndrome and Rett syndrome.

Indexed as

AnimalsAutism Spectrum DisorderHumansRNA, Long NoncodingRNA, Long NoncodingAngelman syndromeautism spectrum disordersdown syndromelong noncoding RNAneurodevelopmentPrader-Willi syndromeRett syndrome

Identifiers

PMID28635106
PMCPMC6492731
OpenAlexW2654158031

What OpenQuestion holds

Textmetadata
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.