Evidence map›Paper›PMID 39722619›Full record

ReviewSe pu = Chinese journal of chromatography2025

[Advances in molecular networking technology for discovering emerging contaminants and transformation products].

Xiao-Mei Tan, Yu-Wei Zhang, Zhao-Yu Jiao, Nan-Yang Yu, Si Wei

Abstract readReviewEnglish Abstract
In one paragraph

Review in Se pu = Chinese journal of chromatography, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

5 authors.

Xiao-Mei TanState Key Laboratory of Pollution Control & Resource Reuse, School of Environment, Nanjing University, Nanjing 210046, China.
Yu-Wei ZhangState Key Laboratory of Pollution Control & Resource Reuse, School of Environment, Nanjing University, Nanjing 210046, China.
Zhao-Yu JiaoState Key Laboratory of Pollution Control & Resource Reuse, School of Environment, Nanjing University, Nanjing 210046, China.
Nan-Yang YuState Key Laboratory of Pollution Control & Resource Reuse, School of Environment, Nanjing University, Nanjing 210046, China.
Si WeiState Key Laboratory of Pollution Control & Resource Reuse, School of Environment, Nanjing University, Nanjing 210046, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emerging contaminants and their transformation products are widely distributed in the environment. These pollutants carry unknown risks owing to their persistence, migration, and toxicity. The wide variety and complex structures of these substances render them difficult to identify using only target analysis. Suspect screening analysis can identify more substances than target analysis in a single run. However, this analysis method is based on limited data and cannot meet the growing demand for compound identification, especially for emerging contaminants and their transformation products with unknown information. The development of high-resolution mass spectrometry technology has promoted the applications of nontarget analysis in the environmental field, especially for identifying unknown transformation products. At present, the challenges of nontarget analysis include the difficulty of finding compounds of interest and their transformation products from complex data. Molecular networking calculates the similarity between mass spectra based on an improved cosine similarity algorithm. This method can cluster molecular families with similar structures, achieve visualization and a collection of massive mass spectral datasets, and promote the annotation of pollutants through networks and communities. Molecular networking can globally organize and systematically interpret complex tandem mass spectral datasets, providing a new direction for nontarget analysis. This technology was first used in proteomics and gradually introduced into metabolomics for the discovery of new natural products. Recently, it has been introduced into the environmental field for the study of various man-made chemicals, particularly for the discovery of emerging contaminants and their transformation products. In this paper, we introduce a molecular networking analysis method based on high-resolution tandem mass spectrometry and describe its applications in the nontargeted screening of emerging contaminants, focusing on the technical principles, workflow, application status, and future development prospects. This paper discusses the applications of molecular networking technology in the detection of emerging contaminants and their transformation products such as drugs, perfluorinated compounds, and disinfection byproducts. Molecular networking technology is widely applicable to the screening of emerging contaminants in various environmental media, revealing the full range of pollutants in the environment and promoting studies on the environmental behavior and toxicological properties of these compounds.

Indexed as

Environmental PollutantsMass SpectrometryMetabolomicsEnvironmental Pollutantsemerging contaminantshigh-resolution tandem mass spectrometrymolecular networkingtransformation products

Identifiers

PMID39722619
PMCPMC11686472

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.