Evidence map›Paper›PMID 40681821›Full record

ArticleScience China. Life sciences2025

Progress and gaps in antimicrobial resistance research within One Health sectors in China: a systematic analysis.

Cai Chen, Shu-Le Li, Jue Liu, Sabiha Y Essack, Yi Luo, Mui-Choo Jong, Xiang-Yu Dai, Yao-Yang Xu, Lise Korsten, David W Graham and 1 more

Abstract read
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In one paragraph

Article in Science China. Life sciences, 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

11 authors.

Cai ChenState Key Laboratory for Ecological Security of Regions and Cities, Ningbo Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.
Shu-Le LiState Key Laboratory for Ecological Security of Regions and Cities, Ningbo Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.
Jue LiuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Sabiha Y EssackAntimicrobial Research Unit, School of Health Sciences, University of KwaZulu-Natal, Durban, 4001, South Africa.
Yi LuoState Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, 210093, China.
Mui-Choo JongInstitute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518005, China.
Xiang-Yu DaiState Key Laboratory for Ecological Security of Regions and Cities, Ningbo Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.
Yao-Yang XuState Key Laboratory for Ecological Security of Regions and Cities, Ningbo Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.
Lise KorstenDepartment of Plant and Soil Sciences, University of Pretoria, Hatfield, Pretoria, 0028, South Africa.
David W GrahamState Key Laboratory for Ecological Security of Regions and Cities, Ningbo Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.
Yong-Guan ZhuState Key Laboratory for Ecological Security of Regions and Cities, Ningbo Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China. ygzhu@rcees.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial resistance (AMR) presents a multifaceted health threat to humans, animals, plants, food systems, and environments. In response, China initiated extensive research to understand and address AMR. However, there has been a lack of analysis and synthesis of research results at the national level. This study establishes a national AMR knowledge repository through the systematic analysis of over 44,000 scientific publications (2000-2024), employing a machine learning framework that combines transformer-based language models and cluster analysis. Natural language processing (NLP) was used to identify key AMR research topics, subtopics, and AMR detection methods across One Health sectors, including changes over time. Main findings include: (i) China's AMR research in human health aligns with societal disease burdens, yet gaps exist for pathogens like Clostridium difficile and Hepatitis B virus, despite their significant risks in China. (ii) While AMR research in probiotics is increasing, potential risks of AMR transmission associated with their use are often underestimated, particularly regarding the post-marketing surveillance and standardization of probiotic products. (iii) Discovery of new antimicrobial agents and alternative therapies is crucial for AMR prevention in China. (iv) Artificial intelligence (AI) methods are promising to guide and accelerate research, including exploration of natural products and plant extracts. Overall, while the AMR research in China aligns with One Health principles, with the plant health sector surpassing global counterparts, food systems require enhanced efforts and cross-sectoral research, particularly in the development of effective AMR detection and surveillance technologies. This work demonstrates a replicable methodological framework for establishing and sustaining country-specific scientific evidence platforms, offering valuable data-driven support for synthesizing findings, decision-making, and developing current and future action plans to manage AMR from a One Health perspective.

Indexed as

Anti-Bacterial AgentsDrug Resistance, BacterialOne HealthAnimalsChinaHumansMachine LearningNatural Language ProcessingProbioticsAnti-Bacterial Agentsantimicrobial resistanceartificial intelligenceChinaevidence integrationOne Health

Identifiers

PMID40681821

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.