Evidence map›Paper›PMID 40496912›Full record

ReviewEnvironmental science and ecotechnology2025

Emerging technologies for detecting antibiotics in aquaculture wastewater: A critical review.

Xinyu Chang, Junchi Cui, Guihua Wang, Shujuan Meng, Lingling Chen, Meng Zhang

Abstract readReview
In one paragraph

Review in Environmental science and ecotechnology, 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. 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

6 authors.

Xinyu ChangSchool of Electronic and Information Engineering, Beihang University, Beijing, 100191, China.
Junchi CuiSchool of Environment, Beijing Normal University, Beijing, 100875, China.
Guihua WangSchool of Electronic and Information Engineering, Beihang University, Beijing, 100191, China.
Shujuan MengSchool of Materials Science and Engineering, Beihang University, Beijing, 100191, China.
Lingling ChenCollege of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, 518118, China.
Meng ZhangSchool of Electronic and Information Engineering, Beihang University, Beijing, 100191, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibiotic release and transfer within environmental systems significantly impact ecological stability and human health, posing considerable safety risks. Consequently, accurate and efficient detection methods for antibiotics, particularly within complex environmental matrices, are essential. A growing body of research is focusing on antibiotic pollution in wastewater and other environmental settings. Nevertheless, pervasive matrix interferences in complex water matrices and the inherent limitations of standalone analytical approaches in sensitivity, detection range, and other performance metrics underscore the demand for more robust and versatile detection platforms. Here we show a comprehensive overview and critical assessment of antibiotic contaminants, examining their sources, environmental distribution, and current detection methods. We focus on emerging antibiotic detection technologies, comparing their performance and highlighting suitable application contexts. Furthermore, we discuss fundamental principles and historical advancements in antibiotic detection and analytical methodologies. Finally, we identify significant challenges for antibiotic detection in complex environments, suggest viable strategies for future improvements, and outline promising research directions. This review not only provides essential guidance for advancing environmental antibiotic monitoring but also sheds light on the development of a strategic framework for robust, integrated platforms enabling multiplexed antibiotic monitoring in challenging environmental water matrices.

Indexed as

Analytical methodsAntibioticsDetectionEnvironmental samplesWastewater

Identifiers

PMID40496912
PMCPMC12149589

What OpenQuestion holds

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LicenceCC BY
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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.