Evidence map›Paper›PMID 38961073›Full record

ArticleNature communications2024

Barbed arrow-like structure membrane with ultra-high rectification coefficient enables ultra-fast, highly-sensitive lateral-flow assay of cTnI.

Juanhua Li, Yiren Liu, Tianyu Wu, Zihan Xiao, Jianhang Du, Hongrui Liang, Cuiping Zhou, Jianhua Zhou

Abstract read
In one paragraph

Article in Nature communications, 2024. 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
–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

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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.

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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

8 authors.

Juanhua Li *School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China.
Yiren Liu *School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China.ORCID 0000-0003-3741-2060
Tianyu WuSchool of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China.
Zihan XiaoSchool of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China.ORCID 0009-0001-9292-6657
Jianhang DuGuangdong Innovative Engineering and Technology Research Center for Assisted Circulation, the Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, Guangdong, China.
Hongrui LiangSchool of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China.
Cuiping ZhouDepartment of Emergency, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Jianhua ZhouSchool of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China. zhoujh33@mail.sysu.edu.cn.ORCID 0000-0001-9895-8679

Funding

National Natural Science Foundation of China (National Science Foundation of China) 22174167
6 · The paper itself

Abstract

Acute myocardial infarction (AMI) has become a public health disease threatening public life safety due to its high mortality. The lateral-flow assay (LFA) of a typical cardiac biomarker, troponin I (cTnI), is essential for the timely warnings of AMI. However, it is a challenge to achieve an ultra-fast and highly-sensitive assay for cTnI (hs-cTnI) using current LFA, due to the limited performance of chromatographic membranes. Here, we propose a barbed arrow-like structure membrane (BAS Mem), which enables the unidirectional, fast flow and low-residual of liquid. The liquid is rectified through the forces generated by the sidewalls of the barbed arrow-like grooves. The rectification coefficient of liquid flow on BAS Mem is 14.5 (highest to date). Using BAS Mem to replace the conventional chromatographic membrane, we prepare batches of lateral-flow strips and achieve LFA of cTnI within 240 s, with a limit of detection of 1.97 ng mL

Indexed as

Myocardial InfarctionTroponin IBiomarkersHumansLimit of DetectionMembranes, ArtificialSensitivity and SpecificityBiomarkersMembranes, ArtificialTroponin I

Identifiers

PMID38961073
PMCPMC11222510

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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.