Evidence map›Paper›PMID 41972614›Full record

ArticleNanomaterials (Basel, Switzerland)2026

Ordered Macro-Microporous ZIF-8 Decorated with Nanoparticles for Highly Sensitive Detection of Auramine O in Tropical Fruits.

Weiao Li, Litiao Ren, Yuqi Zhao, Xinping Cong, Mingjin Zhang, Yan Liu, Qihui Shen, Xiaoyang Liu

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2026. 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. 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

8 authors.

Weiao LiCollege of Chemistry and Pharmaceutical Engineering, Jilin University of Chemical Technology, Jilin 132022, China.
Litiao RenCollege of Chemistry and Pharmaceutical Engineering, Jilin University of Chemical Technology, Jilin 132022, China.
Yuqi ZhaoCollege of Chemistry and Pharmaceutical Engineering, Jilin University of Chemical Technology, Jilin 132022, China.
Xinping CongCollege of Chemistry and Pharmaceutical Engineering, Jilin University of Chemical Technology, Jilin 132022, China.
Mingjin ZhangCollege of Chemistry and Pharmaceutical Engineering, Jilin University of Chemical Technology, Jilin 132022, China.
Yan LiuCollege of Chemistry and Pharmaceutical Engineering, Jilin University of Chemical Technology, Jilin 132022, China.
Qihui ShenCollege of Chemistry and Pharmaceutical Engineering, Jilin University of Chemical Technology, Jilin 132022, China.ORCID 0000-0003-2204-3258
Xiaoyang LiuState Key Laboratory of Inorganic Synthesis & Preparative Chemistry, Jilin University, Changchun 130021, China.ORCID 0000-0002-7128-8457

Funding

Jilin Provincial Natural Science Foundation YDZJ202101ZYTS125
6 · The paper itself

Abstract

Herein, an electrochemical sensor is reported for the first time based on an ordered macro-microporous composite derived from metal-organic frameworks (MOFs) for the highly sensitive detection of auramine O (AO), a Group 2B carcinogen. The hierarchical pore architecture, integrating an ordered macroporous network with a microporous ZIF-8 framework, enables the uniform dispersion of a high density of catalytically active sites. The interconnected macroporous channels facilitate efficient mass transport and rapid removal of reaction byproducts, effectively preventing pore blockage and ensuring stable sensing performance during repeated measurements. Owing to these structural advantages, the proposed sensor exhibits outstanding analytical performance toward AO detection, with a sensitivity of 0.4843 μA μM

Indexed as

auramine Oelectrochemistryordered macro–microporous MOF

Identifiers

PMID41972614
PMCPMC13074856

What OpenQuestion holds

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Registered trials

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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.