Microplastics in focus: a silent disruptor of liver health- a systematic review
Bibliographic record
Abstract
Micro- and nanoplastics (MNPs) are widespread environmental contaminants, yet their impact on human liver health is not fully understood. We conducted a systematic review of 25 experimental, observational, and organoid-based studies published between 2022 and 2025 that investigated the hepatotoxic effects of polystyrene micro- and nanoplastics (PS-MPs/NPs). Following PRISMA guidelines, we screened 770 records from PubMed, EMBASE, Scopus, and Web of Science. After removing duplicates, conducting dual-stage screening, and assessing quality using the Newcastle–Ottawa Scale, 25 studies met our predefined inclusion criteria. Seventeen studies using human liver-derived cell lines consistently reported oxidative stress, inflammation, apoptosis, mitochondrial dysfunction, and disturbances in lipid-metabolism in a size- and dose-dependent manner, with nanoplastics showing the highest toxicity. Six investigations using pluripotent-stem-cell-derived liver organoids confirmed and expanded upon these findings, demonstrating that both pristine and aged PS-MPs (1–10 µm) disrupt sulfur amino acid and iron homeostasis (e.g., increased serum cysteine, decreased hepatic cysteine, and disturbed homocysteine metabolism), impair mitochondrial bioenergetics, and lead to significant lipid accumulation after exposures lasting up to 500 h. Limited human evidence indicated transplacental transfer of PS-MP associated with elevated fetal liver enzymes (alkaline phosphatase, aspartate aminotransferase, and γ-glutamyl transferase) in 1,057 pregnancies, and higher microplastic levels were found in cirrhotic livers compared to non-diseased livers, underscoring potential clinical implications. Current findings suggest that exposure to PS-MP/NP disrupts hepatic redox balance, metabolic function, and structural integrity across in vitro , organoid, and human models. However, variability in particle characterization, exposure methods, and outcome measures, along with limited epidemiological data, hinder definitive risk assessment. Future research should prioritize standardized methodologies, longitudinal human studies, and advanced mechanistic models to establish exposure thresholds and develop strategies to mitigate microplastic-induced hepatotoxicity. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251159265 .
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".