Evidence map›Paper›PMID 40253782›Full record

ArticleJournal of hazardous materials2025

Rapid detection of microplastics and nanoplastics in seconds by mass spectrometry.

Mengyuan Xiao, Yongqing Yang, Hanin Alahmadi, Allison Harbolic, Gina M Moreno, Terry Yu, Jerry Liu, Alex Guo, Genoa R Warner, Phoebe A Stapleton and 1 more

Abstract read
In one paragraph

Article in Journal of hazardous materials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 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.

Mengyuan XiaoDepartment of Chemistry & Environmental Science, New Jersey Institute of Technology, Newark, NJ 07102, United States.
Yongqing YangDepartment of Chemistry & Environmental Science, New Jersey Institute of Technology, Newark, NJ 07102, United States.
Hanin AlahmadiDepartment of Chemistry & Environmental Science, New Jersey Institute of Technology, Newark, NJ 07102, United States.
Allison HarbolicDepartment of Chemistry & Environmental Science, New Jersey Institute of Technology, Newark, NJ 07102, United States.
Gina M MorenoDepartment of Pharmacology and Toxicology and Ernest Mario School of Pharmacy, Rutgers University, Piscataway, NJ 08854, United States.
Terry YuDepartment of Chemistry & Environmental Science, New Jersey Institute of Technology, Newark, NJ 07102, United States.
Jerry LiuDepartment of Chemistry & Environmental Science, New Jersey Institute of Technology, Newark, NJ 07102, United States.
Alex GuoDepartment of Chemistry & Environmental Science, New Jersey Institute of Technology, Newark, NJ 07102, United States.
Genoa R WarnerDepartment of Chemistry & Environmental Science, New Jersey Institute of Technology, Newark, NJ 07102, United States.
Phoebe A StapletonDepartment of Pharmacology and Toxicology and Ernest Mario School of Pharmacy, Rutgers University, Piscataway, NJ 08854, United States.
Hao ChenDepartment of Chemistry & Environmental Science, New Jersey Institute of Technology, Newark, NJ 07102, United States. Electronic address: hao.chen.2@njit.edu.

Funding

Translational Research Support CoreP30ES005022 · NIEHS · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI ROBERT John LAUMBACH · 1988 to 2026
$47.4M
TRAINING IN EVIRONMENTAL TOXICOLOGYT32ES007148 · NIEHS · RUTGERS THE ST UNIV OF NJ NEW BRUNSWICK · PI Lauren M Aleksunes · 1987 to 2026
$11.4M
Microvascular mechanisms of growth restriction after environmental toxicant exposureR01ES031285 · NIEHS · RUTGERS, THE STATE UNIV OF N.J. · PI STAPLETON, PHOEBE · 2021 to 2025
$3.5M
Combining Absolute Quantitative Cross-Linking Mass Spectrometry and Molecular Modeling for Probing PROTAC-Mediated Ternary Complex StructuresR21GM148874 · NIGMS · NEW JERSEY INSTITUTE OF TECHNOLOGY · PI CHEN, HAO, CHENG, XIAOLIN · 2023 to 2024
$429k
NIEHS NIH HHS P30 ES005022NIEHS NIH HHS R01 ES031285NIEHS NIH HHS T32 ES007148NIGMS NIH HHS R21 GM148874
6 · The paper itself

Abstract

Microplastics (MPs) and nanoplastics (NPs) are pervasive pollutants and their analyses by traditional mass spectrometric methods require time-intensive sample preparation (e.g., extraction, digestion, and separation). This study presents a rapid and novel method for detecting MPs and NPs using flame ionization mass spectrometry (FI-MS) in which a dried sample (e.g., powder, soil and tissue) is directly burnt or heated with a flame in front of the MS inlet. FI-MS enables decomposition and ionization of various plastics such as polyethylene terephthalate (PET) and polystyrene (PS), allowing for analysis to be completed as fast as 10 seconds per sample. As a demonstration of application of this technique, PET contaminants in 1 L of bottled water or in 0.65 L of apple juice contained in plastic bottles were quickly detected from a filter paper after sample filtration and brief drying. A 0.89 mg soil sample spiked with 6000 ppm PET microplastics was measured to contain 4.98 µg of PET (5595 ppm, quantitation error: 6.8 %). Strikingly, PS nanoplastics (200 nm size) in mouse placentas were successfully identified and quantified, highlighting the method's ability to analyze biological tissue without tedious sample preparation. Overall, this study demonstrates the high potential of FI-MS for real-world sample analysis of MPs and NPs in environmental, biological, or consumer product samples.

Indexed as

MicroplasticsNanoparticlesPlasticsAnimalsMass SpectrometryMicePolyethylene TerephthalatesPolystyrenesMicroplasticsPlasticsPolyethylene TerephthalatesPolystyrenesBiological tissueFlame ionizationPlastic pollutantSoil

Identifiers

PMID40253782
PMCPMC12396735

What OpenQuestion holds

Textmetadata
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Read underepoch 390

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.