Evidence map›Paper›PMID 29357972›Full record

ReviewZhongguo fei ai za zhi = Chinese journal of lung cancer2018

[Progress of Long Non-coding RNA in Non-small Cell Lung Cancer].

Yachen Zhang, Di Liang, Jing Jin, Congmin Liu, Yutong He

Open access · greenAbstract readReview
In one paragraph

Review in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.2field-weighted citation impact, top 51% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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

5 authors at 1 institution in 1 country.

Yachen ZhangThe Fourth Hospital of Heibei Medical University, Cancer Institute, Shijiazhuang 050011, China.
Di LiangThe Fourth Hospital of Heibei Medical University, Cancer Institute, Shijiazhuang 050011, China.
Jing JinThe Fourth Hospital of Heibei Medical University, Cancer Institute, Shijiazhuang 050011, China.
Congmin LiuThe Fourth Hospital of Heibei Medical University, Cancer Institute, Shijiazhuang 050011, China.
Yutong HeThe Fourth Hospital of Heibei Medical University, Cancer Institute, Shijiazhuang 050011, China.
Hebei Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is one of the most important malignant tumors in the world. The morbidity and mortality rank the first in all kinds of cancer. Long non-coding RNA (lncRNA) is at least 200 nt long and has no protein coding capacity. It plays an important role in the epigenetic regulation, cell cycle regulation, the regulation of cell differentiation, and many other life activities. The studies indicate that dysregulation of lncRNAs in non-small cell lung cancer (NSCLC) tissue and blood circulation is associated with the occurrence and development of cancer. The lncRNAs play an significant role in proliferation, differentiation, migration and apoptosis of the tumor cells. Explore the potential mechanism between lncRNAs and NSCLC is beneficial for the early diagnosis, target therpy and improve prognosis. Therefore, the study aims to demonstrate the latest studies on the lncRNAs related to occurence, diagnosis, therpy and prognosis of NSCLC. It can help to deeply understanding of lncRNA, and provide new ideas for the prevention of NSCLC.

Indexed as

CarcinogenesisCarcinoma, Non-Small-Cell LungHumansMolecular Targeted TherapyRNA, Long NoncodingRNA, Long NoncodingDiagnosisLncRNALung neoplasmsPrognosisTreatment

Identifiers

PMID29357972
PMCPMC5972355
OpenAlexW3024727783

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.