Evidence map›Paper›PMID 31346383›Full record

ReviewComputational and structural biotechnology journal2019

Avenues Toward microRNA Detection

Chu-Shu Zhu, Lingyun Zhu, De-An Tan, Xin-Yuan Qiu, Chuan-Yang Liu, Si-Si Xie, Lv-Yun Zhu

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Computational and structural biotechnology journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
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

16 citing papers in PubMed.

  1. Review
  2. Review
  3. MicroRNAs in neurodegenerative diseases: from molecular mechanisms to clinical biomarkers, detection methods and therapeutic strategies-advances and challenges.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Review
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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

7 authors.

Chu-Shu ZhuDepartment of Biology and Chemistry, College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, Hunan 410073, PR China.
Lingyun ZhuDepartment of Biology and Chemistry, College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, Hunan 410073, PR China.
De-An TanDepartment of Clinical Laboratory, Hospital of National University of Defense Technology, Changsha, Hunan 410073, PR China.
Xin-Yuan QiuDepartment of Biology and Chemistry, College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, Hunan 410073, PR China.
Chuan-Yang LiuDepartment of Biology and Chemistry, College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, Hunan 410073, PR China.
Si-Si XieDepartment of Biology and Chemistry, College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, Hunan 410073, PR China.
Lv-Yun ZhuDepartment of Biology and Chemistry, College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, Hunan 410073, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the decades, the biological role of microRNAs (miRNAs) in the post-transcriptional regulation of gene expression has been discovered in many cancer types, thus initiating the tremendous expectation of their application as biomarkers in the diagnosis, prognosis, and treatment of cancer. Hence, the development of efficient miRNA detection methods

Indexed as

Additional micro-/nano-materialsBiological recognition elementsmicroRNA detection in vitroSignal transduction/readout elements

Identifiers

PMID31346383
PMCPMC6630062

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.