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February 28, 2026Food Chemistry6 citationsOpen Access

Hydrodynamic modulation of microplastic bioaccumulation in edible fish: Integrating biomarker networks, machine learning, and food safety perspectives

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MRMajid RastaNLNiloofar S LashkaryanXSXiaotao Shi

Key Points

  • The research aims to explore how hydrodynamics influence microplastic bioaccumulation and related physiological effects in fish.
  • Assessed 5 μm polystyrene microplastics at 1000 μg/L on Ctenopharyngodon idella
  • Tested conditions under static and varying water velocities (1, 3, 5 BL/s)
  • Analyzed muscle tissue for histological damage and biomarker levels using factorial ANOVA and structural equation modeling
  • Employed machine learning to identify key predictive biomarkers and assess model accuracy.
  • High water velocity led to maximum microplastic bioaccumulation of 58.1 ± 10.5 × 10 3 μg/kg
  • Histological analysis showed significant muscle damage, including fiber degeneration and necrosis
  • Biomarkers indicated oxidative stress, neurotoxicity, and disrupted energy metabolism were key physiological impacts
  • Machine learning achieved 87.5% accuracy in identifying ATPase, superoxide dismutase, and cholinesterase as predictive biomarkers.

Abstract

Microplastic (MP) pollution poses increasing environmental and food safety risks, yet the role of hydrodynamics in MPs bioaccumulation and fish physiology is unclear. This study assessed the effects of 5 μm polystyrene MPs (1000 μg/L) on Ctenopharyngodon idella under static conditions and at water velocities of 1, 3, and 5 body lengths per second (BL/s). Fish exposed to high velocity showed highest MPs bioaccumulation (58.1 ± 10.5 × 10 3 μg/kg), and histological damage, including fiber degeneration, necrosis, and hemorrhage. Biomarkers indicated oxidative stress, neurotoxicity, and disrupted energy metabolism, while endocrine and neurochemical disturbances reflected systemic stress and reduced tissue quality. Factorial ANOVA and structural equation modeling revealed independent and synergistic effects of MPs and hydrodynamics on muscle damage. Machine learning identified ATPase, superoxide dismutase, and cholinesterase as key predictive biomarkers (87.5% accuracy). Collectively, these findings challenge static-exposure paradigms in MPs toxicity studies and demonstrate hydrodynamics drive MPs bioaccumulation and effects, requiring ecological risk assessment inclusion. • Hydrodynamic intensify MPs accumulation and damage in edible fish muscle tissue. • Oxidative stress, neurotoxicity, and endocrine disruption mechanistically drive muscle dysfunction. • Biomarkers and modeling provide predictive tools for seafood safety. • ML and SEM reveal combined MPs and velocity effects on fish muscle.

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Cite This Study

Rasta et al. (2026) studied this question.

synapsesocial.com/papers/69a285da0a974eb0d3c00c05https://doi.org/10.1016/j.foodchem.2026.148610
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