Evidence map›Paper›PMID 40285681›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Tailored Fluorescent Metal-Organic Frameworks Hybrid Membrane Sensor Arrays: Simultaneous and Selective Quantification of Multiple Antibiotics.

Tongtong Ma, Qiao Huang, Lei Yuan, Shugang Yan, Yalin Mo, Yibin Ying, Yingchun Fu, Jinming Pan

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

8 authors.

Tongtong MaCollege of Biosystems Engineering and Food Science, Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Zhejiang University, Hangzhou, 310058, China.
Qiao HuangCollege of Biosystems Engineering and Food Science, Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Zhejiang University, Hangzhou, 310058, China.
Lei YuanCollege of Biosystems Engineering and Food Science, Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Zhejiang University, Hangzhou, 310058, China.
Shugang YanCollege of Biosystems Engineering and Food Science, Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Zhejiang University, Hangzhou, 310058, China.
Yalin MoCollege of Biosystems Engineering and Food Science, Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Zhejiang University, Hangzhou, 310058, China.
Yibin YingCollege of Biosystems Engineering and Food Science, Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Zhejiang University, Hangzhou, 310058, China.
Yingchun FuCollege of Biosystems Engineering and Food Science, Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Zhejiang University, Hangzhou, 310058, China.ORCID https://orcid.org/0000-0003-0550-9052
Jinming PanCollege of Biosystems Engineering and Food Science, Zhejiang Key Laboratory of Intelligent Sensing and Robotics for Agriculture, Zhejiang University, Hangzhou, 310058, China.

Funding

Key R&D Program of Zhejiang Province 2025C02126National Key R&D Program of China 2023YFD1301501
6 · The paper itself

Abstract

Sensor array offers significant potential for rapid, high-throughput antibiotic detection. However, cross-reactivity-based sensor arrays often lack accuracy, despite comprehensive data analysis; while traditional high-affinity-based sensors based on antibodies/aptamers frequently suffer from complicated design and poor robustness. Here, a filterable paper-based fluorescent metal-organic frameworks (MOFs) sensor array is developed for one-to-one recognition and quantification of multiple antibiotics. Three representative MOFs are designed to exceptional affinity and specificity for the target antibiotic. A filtration-assisted detection enhances sensitivity, achieving parts-per-billion (ppb)-level detection in mixed solutions. The proposed approach integrates recognition and signal generation, streamlined 10-min process. The robustness of the MOFs also enables direct detection in raw samples containing organic solvents, which is not achievable by conventional methods. Notably, the sensor array can be easily incorporated into a smartphone-based portable device, coupled with a user-friendly image analysis applet for one-step extraction and quantitative detection in chicken samples. Leveraging MOFs' versatility, this method can be extended to simultaneously detect a broad range of antibiotics, offering the potential for universal, high-throughput accurate detection of various chemical targets.

Indexed as

Anti-Bacterial AgentsBiosensing TechniquesMetal-Organic FrameworksAnimalsChickensFluorescent DyesAnti-Bacterial AgentsFluorescent DyesMetal-Organic Frameworksantibioticshybrid membranemetal–organic frameworksensor arraysimultaneous detection

Identifiers

PMID40285681
PMCPMC12279192

What OpenQuestion holds

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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.