Evidence map›Paper›PMID 42483598›Full record

ReviewEnvironment & health (Washington, D.C.)2026

Gaps between Laboratory Experiments and Real-World Exposure: Toxicological Assessment of Microplastics Is Based on Inadequate Evidence.

Yuzhu Zhang, Qunfang Zhou, Shanjun Song, Qian Liu

Abstract readReview
In one paragraph

Review in Environment & health (Washington, D.C.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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

4 authors.

Yuzhu ZhangNational Institute of Metrology, Beijing 100029, China.
Qunfang ZhouState Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.ORCID https://orcid.org/0000-0003-2521-100X
Shanjun SongNational Institute of Metrology, Beijing 100029, China.ORCID https://orcid.org/0000-0002-4125-5179
Qian LiuState Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.ORCID https://orcid.org/0000-0001-8525-7961

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global significance of microplastic (MP) toxicity assessment is widely acknowledged. Current studies have enhanced our understanding of the mechanisms behind MP toxicity; however, most research mainly focused on the toxicity of individual MPs, overlooking the environmental complexity that arises from the diversity of MPs and the combined effects of multiple pollutants. Furthermore, a notable gap exists in research concerning low-dose and long-term exposure, which significantly limits the relevance of current toxicity data for risk assessments. To address these challenges, we suggest a more thorough and logical approach to evaluating MP toxicity, including: enhancing the harmonization of methods for detecting and quantifying MPs in various environmental and biological matrixes; leveraging AI to simulate real environmental exposures and to predict the complex interactions between MPs and other environmental factors; and combining insights from environmental science, toxicology, materials science, and other relevant fields to bridge the gap between laboratory findings and real-world conditions. Collectively, these efforts could transform fragmented data into risk intelligence, delivering actionable governance solutions for global MP challenges.

Indexed as

Analytical methodsMicroplasticsReal-world variabilityToxicological Assessment

Identifiers

PMID42483598
PMCPMC13386370

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.