Evidence map›Paper›PMID 40206826›Full record

ArticleFrontiers in bioengineering and biotechnology2025

Enhancing lateral flow immunoassay performance for cardiac troponin I detection with pore-size tailored silica nanoparticles and smartphone-based "AdaptiScan" analysis.

Shaonian Ye, Cifu Xu, Huilin Li, Shilun Feng, Yan Wang, Fang Gao

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2025. 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
–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

1 citing paper in PubMed.

  1. 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.

Shaonian YeInstitute of Energy Materials Science, University of Shanghai for Science and Technology, Shanghai, China.
Cifu XuCollege of Information and Electrical Engineering, China Agricultural University, Beijing, China.
Huilin LiDepartment of Nephrology, Gongli Hospital of Shanghai Pudong New Area, Shanghai, China.
Shilun FengState Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China.
Yan WangCollege of Information and Electrical Engineering, China Agricultural University, Beijing, China.
Fang GaoInstitute of Energy Materials Science, University of Shanghai for Science and Technology, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The accurate and rapid detection of cardiac troponin I (cTnI) at the point of care is crucial for the timely diagnosis of myocardial infarction (MI). This study introduces an advanced lateral flow immunoassay (LFIA) platform for cTnI detection. We employed small-sized, large-pore dendritic mesoporous silica nanoparticles (DMSN-2) to encapsulate quantum dots (QDs), achieving an enhanced QD loading capacity of 1.427 g QD/g silica, compared to 0.881 g QD/g silica for smaller pore counterparts (DMSN-1). This nano-LFIA was further integrated with "AdaptiScan", a smartphone-based detection system that uses adaptive detection algorithms to automatically extract and analyze fluorescence signals from LFIA strips. This integration of pore-size tailored DMSNs and "AdaptiScan" resulted in a limit of detection for cTnI of 42.6 ng/L, which meets clinical diagnostic requirements. The platform offers a sensitive, cost-effective, and portable solution for rapid detection of MI, potentially transforming point-of-care testing in resource-limited settings.

Indexed as

lateral flow immunoassaymesoporouspore sizequantum dotssmartphone-based analysis

Identifiers

PMID40206826
PMCPMC11978842

What Socratic 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 Socratic graph.