Evidence map›Paper›PMID 31406466›Full record

ArticleInfection and drug resistance2019

Development of a multiple cross displacement amplification combined with nanoparticles-based biosensor assay to detect

Shijun Li, Chunting Liu, Ying Liu, Qing Ma, Yue Wang, Yi Wang

Open access · goldAbstract read
In one paragraph

Article in Infection and drug resistance, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.3field-weighted citation impact, top 13% 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

13 citing papers in PubMed, 21 citations in OpenAlex.

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  9. Rapid and Visual Differentiation ofFrontiers in microbiology · 2021
    Article
  10. Article
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  13. A Novel Detection ofInfection and drug resistance · 2019
    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

6 authors at 1 institution in 1 country.

Shijun Li *Laboratory of Bacterial Infectious Disease of Experimental Center, Guizhou Provincial Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, People's Republic of China.
Chunting Liu *Laboratory of Bacterial Infectious Disease of Experimental Center, Guizhou Provincial Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, People's Republic of China.
Ying LiuLaboratory of Bacterial Infectious Disease of Experimental Center, Guizhou Provincial Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, People's Republic of China.
Qing MaLaboratory of Bacterial Infectious Disease of Experimental Center, Guizhou Provincial Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, People's Republic of China.
Yue WangLaboratory of Bacterial Infectious Disease of Experimental Center, Guizhou Provincial Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, People's Republic of China.
Yi WangKey Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 10045, People's Republic of China.
Guizhou Center for Disease Control and Prevention · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background

methodsA set of 10 primers specifically to recognize 10 different regions of the

resultsMCDA-LFB assay was successfully established for the detection of

conclusionThe MCDA-LFB techniques developed in the present study are an effective tool for the rapid detection of

Indexed as

lateral flow biosensorlimit of detectionMCDA-LFBmultiple cross displacement amplificationNeisseria meningitidis

Identifiers

PMID31406466
PMCPMC6642637
OpenAlexW2962644898

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.