Evidence map›Paper›PMID 40247044›Full record

ArticleScientific reports2025

Artificial intelligence driven platform for rapid catalytic performance assessment of nanozymes.

Wenjie Xuan, Xiaofo Li, Honglei Gao, Luyao Zhang, Jili Hu, Liping Sun, Hongxing Kan

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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  5. CeOPlant molecular biology · 2026
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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

7 authors.

Wenjie XuanSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China.
Xiaofo LiSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China.
Honglei GaoSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China.
Luyao ZhangSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China.
Jili HuSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China. hujili@ahtcm.edu.cn.
Liping SunSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China. sunliping@ahtcm.edu.cn.
Hongxing KanSchool of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, China. ffdkhx@ahtcm.edu.cn.

Funding

Natural Science Key Project of Anhui Provincial Department of Education (Liping Sun) 2024AH051025The 2024 Xin An Medical Research Institute and Traditional Chinese Medicine Modernization Institute "Top-notch Leadership" Project 2024CXMMTCM003The UniversitySynergy Innovation Program of AnhuiProvince GXXT-2023-071
6 · The paper itself

Abstract

Traditional methods for synthesizing nanozymes are often time-consuming and complex, hindering efficiency. Artificial intelligence (AI) has the potential to simplify these processes, but there are very few dedicated nanozyme databases available, limiting the resources for research and application. To address this gap, we developed AI-ZYMES, a comprehensive nanozyme database featuring 1,085 entries and 400 types of nanozymes. The platform incorporates several key innovations that distinguish it from existing databases: Firstly, standardized Data Curation: AI-ZYMES resolves inconsistencies in catalytic metrics (e.g., K

Indexed as

Artificial IntelligenceEnzymesNanostructuresCatalysisDatabases, FactualKineticsEnzymesArtificial intelligenceDatabaseMachine learningNanozyme

Identifiers

PMID40247044
PMCPMC12006436

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.