Evidence map›Paper›PMID 37767528›Full record

ArticleMicrosystems & nanoengineering2023

Single-molecule RNA capture-assisted droplet digital loop-mediated isothermal amplification for ultrasensitive and rapid detection of infectious pathogens.

Liying Jiang, Xianghao Lan, Linjiao Ren, Zhiyuan Jin, Xuchen Shan, Mingzhu Yang, Lingqian Chang

Open access · goldAbstract read
In one paragraph

Article in Microsystems & nanoengineering, 2023. 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
1.2field-weighted citation impact, top 23% 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, 11 citations in OpenAlex.

  1. 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 at 3 institutions in 1 country.

Liying JiangSchool of Electrical and Information Engineering, Zhengzhou University of Light Industry, 450002 Zhengzhou, China.
Xianghao LanSchool of Electrical and Information Engineering, Zhengzhou University of Light Industry, 450002 Zhengzhou, China.
Linjiao RenSchool of Electrical and Information Engineering, Zhengzhou University of Light Industry, 450002 Zhengzhou, China.
Zhiyuan JinBeijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, 100191 Beijing, China.
Xuchen ShanSchool of Physics, Beihang University, 100191 Beijing, China.
Mingzhu YangBeijing Research Institute of Mechanical Equipment, 100143 Beijing, China.
Lingqian ChangBeijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, 100191 Beijing, China.
Beihang University · CNZhengzhou University of Light Industry · CNBeijing Research Institute of Mechanical and Electrical Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To minimize and control the transmission of infectious diseases, a sensitive, accurate, rapid, and robust assay strategy for application on-site screening is critical. Here, we report single-molecule RNA capture-assisted digital RT-LAMP (SCADL) for point-of-care testing of infectious diseases. Target RNA was captured and enriched by specific capture probes and oligonucleotide probes conjugated to magnetic beads, replacing laborious RNA extraction. Droplet generation, amplification, and the recording of results are all integrated on a microfluidic chip. In assaying commercial standard samples, quantitative results precisely corresponded to the actual concentration of samples. This method provides a limit of detection of 10 copies mL

Indexed as

BiosensorsMicrofluidics

Identifiers

PMID37767528
PMCPMC10519972
OpenAlexW4387020235

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.