Evidence map›Paper›PMID 39816145›Full record

ArticleBiomedical optics express2025

Plasmonic Ag/PMMA/Eu nanocomposite for sensitive dual mode detection of malachite green.

Linlin Tian, Ziheng Song, Chengmei Sun, Chengcheng Xu, Dong Zhang, Qingru Wang

Abstract read
In one paragraph

Article in Biomedical optics express, 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.

Linlin TianSchool of Physical Science and Information Technology, Liaocheng University, Liaocheng 252059, China.
Ziheng SongSchool of Physical Science and Information Technology, Liaocheng University, Liaocheng 252059, China.
Chengmei SunSchool of Physical Science and Information Technology, Liaocheng University, Liaocheng 252059, China.
Chengcheng XuSchool of Physical Science and Information Technology, Liaocheng University, Liaocheng 252059, China.
Dong ZhangSchool of Physical Science and Information Technology, Liaocheng University, Liaocheng 252059, China.
Qingru WangSchool of Physical Science and Information Technology, Liaocheng University, Liaocheng 252059, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate and efficient determination of malachite green (MG) in aquaculture is crucial for ensuring environment and food safety. Herein, we present a dual-response fluorescence probe based on an Ag/PMMA/Eu nanocomposite for the sensitive detection of MG with low concentration and single droplet. The luminescence properties of the Ag/PMMA/Eu nanocomposite and the fluorescence resonance energy transfer (FRET) effect between Eu and MG are significantly improved due to the localized surface plasmon resonance (LSPR) effect. The dual-response system enables the detection of MG through both luminescence intensity and energy transfer efficiency using the Ag/PMMA/Eu nanocomposite as a detection platform in the range of 0-10.78 µmol/L. The detection limit reaches as low as 0.5 nmol/L, a significant improvement over the 0.11 µmol/L limit achievable by pure Eu film alone, demonstrating superior sensitivity compared to traditional fluorescence detection techniques. The results indicate that the nanocomposite significantly boosts the sensitivity of the dual-mode sensors. In addition, the sensor successfully detects MG residues in lake water, highlighting the Ag/PMMA/Eu nanocomposite's potential to advance high sensitivity, selectivity, stability, and accurate detection in food security and biological analysis.

Identifiers

PMID39816145
PMCPMC11729280

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.