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Microplastic contamination in South Asian commercially important seafood: A comprehensive assessment of occurrence, source, and human health risk.

Seafood is a cornerstone of global food security and human nutrition, serving as the primary source of animal protein for more than one-fourth of the global population, with South Asia representing one of the world's fastest-growing seafood-consuming regions. However, escalating microplastic (MP) pollution in marine ecosystems poses an emerging threat to seafood safety and human health, yet a comprehensive regional assessment of MP contamination in South Asian seafood remains lacking. This study presents the first region-wide systematic synthesis of the literature on MP contamination in commercially important seafood across South Asia, integrating occurrence patterns, human exposure assessment, polymer-specific hazard evaluation, and bibliometric analysis to address this critical knowledge gap. The meta-analysis estimated an average microplastic exposure of 145 particles/person/day through seafood consumption in South Asia, with fish contributing the highest intake (121 particles/person/day). The detected polymers were classified into PHI hazard levels I-IV, with polyvinyl chloride (PVC), polyurethane (PU), and polyacrylamide (PAM) representing the highest hazard categories. The mean pollution load index (PLI) was 7.71 (Category I), with crustaceans exhibiting the highest contamination (PLI = 10.07). Polypropylene was the predominant polymer, whereas fragments and blue particles were the most frequently reported microplastic characteristics. These findings provide the first regional baseline for assessing microplastic contamination, polymer-associated hazards, and human exposure through seafood consumption in South Asia, underscoring the need for standardized monitoring and targeted mitigation strategies to safeguard seafood safety and public health.

Animals

Thermal analysis techniques for microplastic mass quantification: Methodological challenges and standardization needs.

Microplastics (MPs, 1 &#x3bc;m-5 mm) and nanoplastics (NPs, <1&#x202f;&#x3bc;m) are ubiquitous contaminants requiring standardized quantification methods. This systematic review evaluates thermal analysis techniques for mass-based MP detection, including pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS), thermogravimetry-MS (TGA-MS), thermal extraction desorption-GC-MS (TED-GC-MS), and differential scanning calorimetry (DSC). Database searches (Web of Science, from inception to December 1, 2025) following PRISMA guidelines identified studies across seven environmental matrices (water, soil/sediment, atmosphere, biota, human tissues). We identify critical standardization gaps: inconsistent marker ion selection, unvalidated conversion factors for tire and road wear particles (TRWPs), and the absence of certified reference materials for complex matrices. Py-GC-MS demonstrates versatility but suffers from lipid interference in biological samples; TED-GC-MS offers superior sensitivity (sample capacity &#x223c;200&#xd7; Py-GC-MS) but lacks real-time chromatographic monitoring. To advance data comparability, we propose: (i) harmonized ion selection hierarchies based on specificity-sensitivity balance, (ii) matrix-specific TRWP quantification protocols, and (iii) inter-laboratory validation using environmental reference materials. This review provides a methodological roadmap for standardizing thermal analysis in MP research.

Humans

Towards microplastic bioremediation: Fungal degradation of pristine and pretreated high-density polyethylene and polystyrene.

Microplastic (MP) contamination has become a significant ecological issue because of its enduring existence in the ecosystem and its possible negative impacts. Therefore, using degrading strategies to eliminate these stubborn polymers has been a subject of scientific research. However, the currently used degradation methods are relatively inefficient. Given the pervasiveness of High-Density Polyethylene (HDPE) and Polystyrene (PS) and their resistance to biodegradability, disposal strategies are critical and must be addressed. This manuscript examines the biodegradation of pristine and UV-treated HDPE and PS MPs by Aspergillus flavus species in minimal growth media over 70 days. The maximum weight loss observed at 70 days for pristine HDPE and PS in sole carbon source (SCS) media was (29.33 &#xb1; 0.28) % and (17.67 &#xb1; 0.35) %, respectively. Whereas, for UV-treated HDPE and PS MPs, the % weight reduction was (33 &#xb1; 0.21) % and (25 &#xb1; 0.19) %, respectively. UV-treated MPs exhibited greater weight reduction, as UV induced oxygenated functional groups enhance polymer susceptibility to enzymes, thereby promoting biodegradation. HDPE MPs typically show a higher proportion of particles in the lower size range compared to PS MPs. This assertion was based on the weight loss, particle size distribution, and SEM analysis. Furthermore, chemical changes were evaluated using Fourier transform Infrared Spectroscopy (FTIR) analysis, which also displayed chemical oxidation occurring during biodegradation. Liquid Chromatography-Mass Spectrometry (LC-MS) results indicate that UV pretreatment enhances biodegradability by promoting chain scission. These findings further suggest that this fungus's natural and ubiquitous occurrence in terrestrial and marine environments may actively contribute to MP biodegradation while requiring few nutrients.

Microplastics

Influence of soil types with different soil-forming process on the qualitative and quantitative detection of microplastics by near-infrared spectroscopy.

Microplastics (MPs) have become a pressing global environmental threat, with soils-acting as sinks for MPs from multiple sources-gaining increasing attention. Near-infrared (NIR) spectroscopy offers a promising tool for MPs detection due to its rapid, non-destructive, and field-applicable features. Although previous studies have focused on the effects of individual soil components on the NIR detection performance of MPs, there is still a lack of systematic research on how the complex background-formed by the coupling of multiple physicochemical properties in natural soils-affects detection performance. This study focuses on soil types with different soil-forming processes, selected five representative agricultural soils to systematically evaluate how the combinations of physicochemical properties they represented affect the performance of NIR-based qualitative and quantitative analysis of MPs in soils. The results demonstrated that soil type significantly affected both the spectral response and detection performance of MPs. Brown Pedocals and Brown Earth exhibited clearer characteristic absorption and stronger linear responses, achieving higher identification accuracy under low (<1.5 %) or zero MPs concentrations and the best quantitative performance (R2 &#x2265; 0.988, prediction set root mean square error (RMSEP) &#x2264; 0.110 %). In contrast, Phaeozem and Red Soil were more prone to misclassification at low concentrations, while Fluvo-aquic Soil showed the poorest quantitative performance. This study is the first to reveal, at a holistic level, the critical constraints posed by natural soil complexity on the NIR detection of MPs, offering targeted empirical evidence to support the application of NIR technology in real-world soil environments.

Soil