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The impact of micro- and nanoplastics on immune system development and functions: Current knowledge and future directions

2025· review· en· W4410596130 on OpenAlexafffund
Alain Lamarre

Bibliographic record

VenueReproductive Toxicology · 2025
Typereview
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchFondation Jean-Louis LévesqueArmand-Frappier Foundation
KeywordsCurrent (fluid)Immune systemRisk analysis (engineering)BusinessEngineeringBiologyImmunologyElectrical engineering

Abstract

fetched live from OpenAlex

The prevalence of microplastics (MPs)/ nanoplastics (NPs) in the environment has raised significant concerns regarding their potential toxicity, particularly their impact on biological systems. These particles, particularly NPs, possess unique properties due to their small size and high surface area, enabling them to more easily cross biological barriers and accumulate in tissues. Among various types of plastic materials, polystyrene (PS) is one of the most studied for its toxicological effects, given its widespread use and environmental persistence. This narrative review examines current research on the effects of MPs/NPs, on the immune system, with a focus on both the development of the immune system and its functional responses. Evidence from in vitro and in vivo studies suggests that MP/NP exposure can disrupt immune function, including hematopoiesis, immune cell activation, and the production of inflammatory cytokines. Although in vitro studies highlight cellular toxicity and altered immune cell behavior, in vivo studies reveal more complex outcomes, with some findings suggesting significant effects on organ systems such as the spleen and intestines, while others indicate minimal or no impact under environmentally relevant exposure conditions. Here, we aim to consolidate and summarize the current evidence on the topic, highlight key limitations in the field, and identify areas that warrant further investigation for immunotoxicologists. In addition, we emphasize the importance of using relevant exposure concentrations and complex in vitro or in vivo models to better understand the potential risks associated with MP/NP exposure and their long-term implications for immune health.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.291
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2025
Admission routes2
Has abstractyes

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