The impact of micro- and nanoplastics on immune system development and functions: Current knowledge and future directions
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".