Evidence map›Paper›PMID 34613450›Full record

ArticleMikrochimica acta2021

A simple strategy for signal enhancement in lateral flow assays using superabsorbent polymers.

Taeyeong You, Woojin Jeong, Hwankyu Lee, Yun Suk Huh, Sun Min Kim, Tae-Joon Jeon

Abstract read
PubMed Publisher
In one paragraph

Article in Mikrochimica acta, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 54% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Review
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 2 institutions in 1 country.

Taeyeong YouDepartment of Biological Sciences and Bioengineering, Inha University, Incheon, 22212, South Korea.
Woojin JeongDepartment of Biological Sciences and Bioengineering, Inha University, Incheon, 22212, South Korea.
Hwankyu LeeDepartment of Chemical Engineering, Dankook University, Yongin, 16890, South Korea.
Yun Suk HuhDepartment of Biological Sciences and Bioengineering, Inha University, Incheon, 22212, South Korea. yunsuk.huh@inha.ac.kr.
Sun Min KimDepartment of Biological Sciences and Bioengineering, Inha University, Incheon, 22212, South Korea. sunmk@inha.ac.kr.
Tae-Joon JeonDepartment of Biological Sciences and Bioengineering, Inha University, Incheon, 22212, South Korea. tjjeon@inha.ac.kr.
Inha University · KRDankook University · KR

Funding

rural development administration PJ014238042021
6 · The paper itself

Abstract

To enhance the sensitivity of lateral flow assays (LFAs), a simple strategy is proposed using a nitrocellulose membrane modified with a superabsorbent polymer (SAP). SAP was incorporated into a nitrocellulose membrane for the flow control of detection probes. When absorbing aqueous solutions, SAP promoted the formation of biomolecule complexes to achieve up to a tenfold sensitivity improvement for the detection of human IgG. The assay time was optimized experimentally and numerically to within 20 min using this strategy. Moreover, fluid saturation in LFAs modified with SAP was mathematically simulated to better understand the underlying process, and molecular dynamics simulations were carried out to determine the effect of SAP. The proposed design was also applied to samples spiked with human immunoglobulin-depleted serum to test its applicability. The strategy presented is unique in that it preserves the characteristics of conventional LFAs, as it minimizes user intervention and is simple to manufacture at scale.

Indexed as

Colorimetric detectionFlow controlLateral flow assayPaper-based biosensorSensitivity enhancementSuperabsorbent polymer

Identifiers

PMID34613450
OpenAlexW3202272115

What OpenQuestion holds

Textmetadata
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.