Evidence map›Paper›PMID 34741346›Full record

ArticleJournal of clinical laboratory analysis2021

Comprehensive analysis of N

Hong-Xu Zhu, Wen-Jie Lu, Wei-Ping Zhu, Song Yu

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical laboratory analysis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.5field-weighted citation impact, top 42% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Establishment of a Prognostic Necroptosis-Related lncRNA Signature in Ovarian Cancer.Combinatorial chemistry & high throughput screening · 2026
    Article
  3. Review
  4. Review
  5. Effects of NFrontiers in oncology · 2022
    Review
  6. Comprehensive analysis of NJournal of clinical laboratory analysis · 2021
    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

4 authors at 3 institutions in 1 country.

Hong-Xu ZhuDepartment of Hepatic Surgery, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, China.
Wen-Jie LuDepartment of General Surgery, School of Medicine, Second Affiliated Hospital of Zhejiang University, Hangzhou, China.
Wei-Ping ZhuDepartment of Hepatic Surgery, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai, China.
Song YuDepartment of General Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.ORCID https://orcid.org/0000-0002-4296-0830
Fudan University Shanghai Cancer Center · CNSecond Affiliated Hospital of Zhejiang University · CNShanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLiver hepatocellular carcinoma (LIHC) is a lethal cancer. This study aimed to identify the N

methodsThe expression matrix of mRNA and lncRNA was obtained, and differentially expressed (DE) mRNAs and lncRNAs between tumor and normal samples were identified. Univariate Cox and pathway enrichment analyses were performed on the m

resultsA total of 5031 significant DEmRNAs and 292 significant DElncRNAs were screened, and 72 LIHC-specific m

conclusionThe m

Indexed as

AdenosineAgedBiomarkers, TumorCarcinoma, HepatocellularFemaleGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateLiver NeoplasmsMaleMiddle AgedPrognosisProportional Hazards ModelsRNA, Long NoncodingTumor MicroenvironmentAdenosineBiomarkers, TumorN-methyladenosineRNA, Long Noncodingliver hepatocellular carcinomalong non-coding RNAN6-methyladenosineprognosis prediction

Identifiers

PMID34741346
PMCPMC8649367
OpenAlexW3208612342

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.