Oil-Encapsulated Nanoplastics from Plastic Disposable Food Containers Induce Rapid Cell Death through Cell Membrane Disruption

Oil-Encapsulated Nanoplastics from Plastic Disposable Food Containers Induce Rapid Cell Death through Cell Membrane Disruption | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Oil-Encapsulated Nanoplastics from Plastic Disposable Food Containers Induce Rapid Cell Death through Cell Membrane Disruption Chao Jiang, Ruwen Xie, Gulimire Yilihan, Qiong Chen, Zhen Liu, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6015466/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The rise of food delivery culture has resulted in millions of tons of food-contact plastic containers being used each year, yet the risks of micro(nano)plastics (MNPs) released during the storage of oil-rich foods are still not well understood. Here, we investigated MNP release from polypropylene (PP) and polyethylene (PE)-coated containers under simulated takeout scenarios. When exposed to cooking oil and microwave heating, containers released up to 125-fold more MNPs and 471-fold more heavy metals compared to water exposure, with significantly altered physicochemical properties. Oil-derived PP NPs, uniquely encapsulated in oil films with positive surface charge (+7.37 mV). The positive charge of oil-derived NPs may enhance their interaction with negatively charged cell membranes, leading to rapid cell death within 5 minutes at a concentration of 100 μg/mL through membrane disruption. Transcriptomic analysis revealed that oil-PP NPs triggered substantially more extensive gene expression changes than water-derived NPs, particularly in pathways related to acute cellular stress and mitochondrial energy metabolism. Global exposure assessments highlight annual human intake of up to 3.35 g from oil-rich takeout food. Based on integrated cellular and molecular endpoints, we established a benchmark dose lower limit (BMDL) of 1.18 μg/mL for oil-PP NPs. MNP abundance in human biological samples exceeds BMDL thresholds, suggesting significant health risks. Our findings reveal previously unknown mechanisms of oil-derived MNP toxicity and underscore the urgent need for stricter regulation of plastic food packaging used with oil-rich foods. Biological sciences/Biotechnology/Nanobiotechnology/Nanoparticles Physical sciences/Nanoscience and technology/Nanotoxicology/Cell–particle interactions Physical sciences/Chemistry/Polymer chemistry Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Highlights • Orders of magnitudes higher levels of micro(nano)plastics and harmful additives are released from plastic containers filled with cooking oil compared to those filled with water, especially after microwaving. • Oil-derived nanoplastics can induce cell death by disrupting cellular membranes at concentrations of 100 µg/ml within 5 minutes. • Oil-derived nanoplastics elicit more transcriptomic changes related to acute cellular stress and mitochondrial dysfunction compared to water-derived nanoplastics. • Globally, the highest annual intake of MNPs from microwaving oil-rich takeout food is 3.35 g per person, observed among individuals in China. • The toxicity assessment, integrating both cell viability and molecular biomarkers, establishes a safe exposure limit of 1.18 µg/mL for oil-derived nanoplastics, which is below the actual observed levels in human tissues. 1 Introduction The rapid expansion of the global food delivery industry has transformed modern dietary habits, with convenience driving an ever-increasing reliance on disposable plastic food containers 1 , 2 . In 2023, the global online food delivery market was valued at over $ 189.7 billion, with annual growth projected at 10% in the coming years 3 . This boom has led to the widespread use of plastic food-contact materials (PFCMs), such as takeaway containers, bags, and lids, which account for approximately 40% of global plastic production 4 – 7 . Among these, polypropylene (PP) and polyethylene (PE) dominate due to their durability, lightweight nature, and thermal resistance. However, the frequent use of PFCMs under real-life scenarios, such as heating, storage, and transportation, raises concerns about the release of micro(nano)plastics (MNPs) and chemical additives, particularly when interacting with certain types of food 8 – 10 . Cooking oils, unlike water-based foods, pose a unique challenge due to their physicochemical properties. Oils can solubilize non-polar compounds, potentially enhancing the release of MNPs and chemical additives from plastics 11 . Moreover, oil-rich foods are increasingly prevalent in the global diet, particularly in takeaway meals such as fried foods, curries, and sauces, making them a significant but understudied contributor to MNP exposure. Unlike water simulants widely used in MNP research, oils may interact differently with plastics, altering the surface properties of MNPs and amplifying MNP release and toxicity under conditions like heating or prolonged storage. However, studies on the release and toxicity of MNPs under oil-rich conditions are limited, creating a critical gap in understanding the health risks associated with these interactions. MNPs, including microplastics (MPs) smaller than 5 mm and nanoplastics (NPs) smaller than 1000 nm 12 , are detected in various food products, such as table salt 13 , bottled water 14 , and seafood 15 . The ingestion of MNPs, particularly NPs, raises significant concerns about potential health risks pose a greater risk due to their ability to penetrate biological barriers, leading to heightened adverse effects 16 , including metabolic disorders 17 , DNA damage 18 , inflammation 19 , and cytotoxicity. Yet, most studies have focused on synthetic, fixed-size polystyrene (PS) particles in water, which do not capture the full complexity of MNP exposure in natural food environments. In reality, MNPs may interact with different types of food and environmental matrices, which may alter their toxicity. Here, we address these questions by simulating three common takeout scenarios using cooking oil as a food simulant to investigate MNP release and toxicity from PP and PE-coated containers, with deionized water as a control. We demonstrate that cooking oil significantly increases MNP release—up to 125-fold for PE and 29-fold for PP containers—alongside a substantial increase in heavy metal (up to 471-fold) and harmful organic additive leaching. Zeta potential, indicating surface charge, influences nanoparticle stability and interactions with biological systems. Soybean oil-derived PP NPs exhibited a zeta potential of + 7.37 mV, compared to -8.21 mV for water-derived NPs, potentially resulting in significantly higher cytotoxicity, including rapid cell membrane damage within 5 minutes at 100 µg/mL. Transcriptomic analysis revealed that oil-derived PP NPs caused more extensive gene expression changes, highlighting their heightened toxicity compared to water-derived particles. Globally, our study estimates that Chinese consumers have the highest annual intake of MNPs from high-fat takeout food, reaching approximately 3.35 g per year. Integrating benchmark dose limit thresholds with MNP concentrations reveals the extensive potential for subclinical and pathological damage linked to humans. Our results reveal the significant health risks posed by oil-plastic interactions, emphasizing the need for enhanced safety regulations for food-contact materials in oil-rich food contexts. 2 Results 2.1 Physicochemical Properties of Plastic Takeaway Containers and Their Released MNPs We investigated the release of MNPs from two representative food packaging materials, polypropylene (PP) and polyethylene (PE) (Fig. 1 a). PP containers are commonly used for hot food storage and microwave applications due to their higher thermal stability. PE-coated containers are frequently used for food storage because of PE's flexibility and cost-effectiveness (Fig. 1 b, c). Differential scanning calorimetry (DSC) measurements showed notable differences in thermal stability between the PP and PE materials: the PP exhibited a significant melting peak at 156.51°C, indicating higher thermal stability; conversely, the PE displayed two distinct melting peaks at 88.94°C and 105.07°C, indicating substantially lower melting temperatures (Fig. 1 d). X-ray diffraction (XRD) analysis confirmed the crystalline structures of both PP and PE, revealing distinct crystalline peaks. PP container showed pronounced peaks characteristic of the α crystalline phase of isotactic polypropylene. In contrast, the PE-coated container exhibited primary crystalline peaks, corresponding to the orthorhombic crystal phase of PE (Fig. 1 e) 20 . These results again indicate that PE-coated containers have lower crystallinity and melting temperatures than PP containers. Subsequently, we characterized the morphology of MNPs released from two types of food containers filled with food simulants—deionized (DI) water and soybean oil—after microwave heating for 3 minutes. The plastic particles released into oil from both PP and PE-coated containers showed a diversity of particle sizes and shapes (Figure S1a, b). Transmission electron microscopy (TEM) (Fig. 1 f) and scanning electron microscopy (SEM) (Figure S1c) were subsequently utilized for the detailed characterization of MPs and NPs. Notably, oil-derived NPs released from PP containers (PP NPs) and PE-coated containers (PE NPs) appeared to be encapsulated in an oil film. Zeta potential reflects the surface charge of plastic particles, influencing their stability, aggregation, and interactions with other substances. For simplicity, MNPs released from PP containers filled with soybean oil are termed oil-PP MNPs, while those released from PP containers filled with water are termed water-PP MNPs. Similarly, MNPs from PE-coated containers are designated as oil-PE and water-PE MNPs. After 3 minutes of microwave heating, significant differences in zeta potential were observed among the MNPs ( p -group = 0.025; Fig. 1 g). Water-PP MNPs had a much lower zeta potential (-50.3 mV) than oil-PP MNPs (-0.03 mV), indicating higher surface charge and potential instability in oil. In contrast, oil- and water-PE MNPs had similar zeta potential. 2.2 Oil-Filled Plastic Containers Sustained More Damage Across All Testing Scenarios Scanning Electron Microscopy (SEM) was employed to examine the effects of different treatments on the food-contact surfaces of PP and PE-coated containers (Figure S2). The experimental groups simulated three common scenarios for plastic food containers: microwave heating (A-C), transportation (D-F), and leftover storage (G-H). To test the impact of oil-rich food, we chose soybean oil as the main food simulant because it is widely used in daily life, with DI water as the control. For the PP container, the control group had a smooth, undamaged surface. Microwave heating of the water-filled container left the surface mostly unscathed. However, microwave heating the oil-filled container caused significant degradation and MNPs release, starting as short as 1 minute (A) and increasingly evident after 3 (B) and 5 (C) minutes (Figure S2a, A-C). In the transportation simulation, water treatment left surfaces intact, while oil treatment led to noticeable particle release after 60 minutes (Figure S2a, D-F). In the leftover simulation, water treatment also had minimal impacts (Figure S2a, G, and H), but oil treatment caused substantial surface damages after 5 hours, even without any shaking or movements. Similarly, the water treatment left the PE coating mostly intact, but oil-filled containers showed substantial damage in all scenarios (Figure S2b). Overall, oil significantly impacts both PP and PE-coated containers in all scenarios, while water has minimal effects. 2.3 Microwave Heating of Oil-Filled Plastic Containers Significantly Increases MNP Release and Reduces Particle Size To assess the effects of oil treatments, we analyzed the chemical composition of MNPs released from containers using Raman and ATR-FTIR spectroscopy. Raman analysis confirmed the identity of the released MNPs as PP and PE based on characteristic peaks consistent with reference spectra for these materials (Figure S1d). Notably, ATR-FTIR revealed an additional peak at 1745 cm⁻¹ in both PP and PE MNPs released in oil, indicating potential chemical modifications induced by microwave heating in the presence of oil (Figure S1e) 21 , 22 . Quantifying the release and particle size distribution of MNPs is crucial for evaluating their potential environmental and health impacts. For simplicity, we denoted the MPs and NPs released from PP containers filled with oil and water as oil-PP MPs, oil-PP NPs, water-PP MPs, and water-PP NPs, respectively. Similarly, particles from PE-coated containers filled with oil and water were referred to as oil-PE MPs, oil-PE NPs, water-PE MPs, and water-PE NPs, respectively. MPs were quantified using a BioTek Cytation 3 plate reader, capable of detecting particles as small as 6 µm, with blank controls for accuracy 23 (Figures S1f, g). Nanoparticle Tracking Analysis (NTA) with a NanoSight NS500 equipped with a 532 nm green laser provided quantity and size data for NPs ranging from 10 nm to 1 µm. In the microwaving group, oil-treated samples as shown in Fig. 3 e, PP containers released significantly higher concentrations of smaller oil-PP MNPs compared to water-PP MNPs. After 5 minutes of heating, oil-PP MPs were released at 2.7 × 10 7 particles/L, which were 21 times higher than water-PP MPs ( p < 0.001), with most oil-PP MPs smaller than 50 µm ( p < 0.001) (Fig. 2 a). After heating for 3 minutes, oil-PP NPs were released at 7.2 × 10 12 particles/L, which were 18 times higher than water-PP NPs ( p < 0.001), and their average size was smaller than that of water-PP NPs ( p < 0.001) (Fig. 2 a, c). Similarly, PE-coated containers released significantly higher concentrations of smaller oil-PE MNPs compared to water-PE MNPs. After 5 minutes of heating, oil-PE MPs were released at 2.4 × 10 7 particles/L, which were 62 times higher than water-PE MPs ( p < 0.001), with both the average and median sizes of oil-PE MPs significantly smaller ( p < 0.001). Oil-PE NPs were released at 1.25 × 10 13 particles/L, which were 125 times higher than water-PE NPs ( p < 0.01), and the median size of oil-PE NPs was consistently smaller across all heating durations ( p < 0.001) (Fig. 2 b, d). Under simulated transportation and leftover scenarios (Groups D-H), PP NPs were consistently released at higher concentrations in oil (9.3 × 10 11 to 2.1 × 10 12 particles/L) than in water (3.4 × 10 11 to 6.8 × 10 11 particles/L), with concentrations increasing over time. Most PP MPs were smaller than 10 µm, and the majority of PP NPs were below 220 nm (Figures S3a, c). For PE-coated containers, MPs and NPs were consistently more abundant in oil than in water, with longer exposure times leading to higher releases of PE NPs ( p <0.01). Oil-PE NPs were generally smaller than water-PE NPs ( p <0.01; Figures S3b, d). Overall, under microwaving conditions, MNP release was at highest in concentration and smallest in particle size, followed by simulated transportation and leftover food scenarios, with significant differences confirmed by one-way ANOVA and post-hoc Tukey tests ( p < 0.001). Previous studies on MNP quantification from plastic products mainly relied on particle counting or membrane filtration for weighing, which lacked precision 24 , 25 . Using Py-GC/MS, we quantified MNP mass released from 100 mL of oil or water in plastic containers microwaved for 3 minutes, a common heating duration (Fig. 2 e). MNP release varied significantly by container material and simulant type ( p -group < 0.05), with oil-PE MNPs showing the highest release (162.63 mg per container) and water-PP MNPs the lowest (1.14 mg per container). Based on soybean oil density (0.917 g/mL), released-MNP concentrations were 0.43, 0.01, 1.68, and 0.015 g/g for oil-PP, water-PP, oil-PE, and water-PE, respectively (Fig. 2 f). These findings validated particle counting results. 2.4 Enhanced Release of Harmful Additives from Oil-Filled Plastic Containers MNP-associated toxic additives, including pollutants and heavy metals, pose a significant concern when released from plastic food containers 26 . LC-MS/MS analysis identified 3,126 chemical features (confidence score ≥ 60) in PP, PE, oil-PP, and oil-PE MNPs derived from oil-filled plastic containers after 3 minutes of microwave heating. There are 296 unique features in PP, 963 in oil-PP MNPs, 1,682 in PE, and 2,552 in oil-PE MNPs. 27.8% of features were shared between PP and oil-PP MNPs, and 45.6% were shared between PE and oil-PE MNPs (Figure S4a-c). Among the top 10 most abundant chemicals per sample, 33 were identified, including typical hazardous substances such as DEHP, avobenzone, and isoxadifen-ethyl, commonly used as plasticizers and stabilizers (Tables S2, S3; Figure S4d). Notably, oil-PP MNPs exhibited 143 upregulated chemicals compared to PP, while oil-PE MNPs showed 48 downregulated chemicals compared to PE, highlighting the prominent chemical changes induced by microwave heating in the presence of oil (Figure S4e, f). Inorganic metal additives such as Zn, Pb, Ni, Mn, Cu, Cr, and Cd are commonly added when manufacturing plastics, posing significant toxicity risks to humans 27 . ICP-MS analysis showed minimal release of heavy metals into water but substantially higher levels in oil (Figure S4g). For example, oil-filled PP containers released Zn at 205.9 µg/kg (79-fold increase), Cu at 46.2 µg/kg (380-fold increase), and Pb at 23.52 µg/kg (147-fold increase). Similarly, oil-filled PE-coated containers released Zn at 225.1 µg/kg (113-fold increase), Cu at 89.6 µg/kg (471-fold increase), and Pb at 22.3 µg/kg (159-fold increase). These results underscored the crucial role of cooking oil in accelerating the leaching of chemical additives and heavy metals from plastics. 2.5 Various Types of Cooking Oils Consistently Exacerbate MNP Release Following Microwave Heating Different types of cooking oils are generally used, and PP containers are the most common microwave-safe plastic containers. To generalize the soybean oil-induced hyper-release of MNPs, we examined microwave heating of PP containers with four additional types of cooking oils (blended, palm, peanut, sunflower) for 3 minutes, finding significantly higher MNP release compared to water ( p -group < 0.0001). Interestingly, soybean oil induced the highest release of PP MPs (3.26 × 10 7 particles/L) and PP NPs (7.87 × 10 12 particles/L), with the smallest average sizes for MPs (9.41 µm) and NPs (133.13 nm). Compared to other oils, soybean oil's higher unsaturated fatty acid content may promote oxidation during heating, accelerating PP degradation and increasing MNP release 28 . In contrast, peanut oil showed the lowest release (5.79 × 10 6 particles/L for PP MPs and 1.39 × 10 12 particles/L for PP NPs). Most oil-PP MPs were smaller than 10 µm, and oil-PP NPs were below 500 nm, with average sizes consistently smaller than water-PP MNPs (Figure S5a, b). NPs pose greater risks to human health compared to MPs 29 . For in vitro cytotoxicity assessments, we collected PP NPs smaller than 220 nm (Methods). As mentioned previously, TEM analysis revealed an oil film on oil-PP NPs, and zeta potential measurements showed that soybean oil-PP NPs exhibited a positive charge (+ 7.37 mV), unlike the negative charge of other types of oil-PP NPs (Figure S5c, d). The polydispersity indices (PDIs) of water- and oil-PP NPs ranged from 0.47 to 0.79, indicating a moderate to high polydispersity of size distribution. Water-PP NPs had the smallest average size (132.7 nm) after filtration, suggesting that, despite being individually smaller (Figure S5e,f), the oil film may promote aggregations of oil-PP NPs when not purified 30 . 2.6 Exposure to Oil-PP NPs Induces Rapid Cell Death in Human Cell Lines We focused on the cytotoxicity of soybean oil-PP NPs due to their positive zeta potential and widespread use. Fluorescence-labeled oil-PP NPs (FL-oil-PP NPs) exhibited red fluorescence due to iDye Poly pink, a dye that stains polymers (Figure S5g). To characterize the size distribution of FL-oil-PP NPs and oil-PP NPs in various media, we combined NTA and DLS results (Figure S5h-k). Oil-PP NPs in 0.1% SDS exhibited the smallest mean size (176.6 nm, with 75% of particles below 220 nm). PDI values range from 0.61 to 0.72 across all media, suggesting moderate polydispersity. These results indicate that the particle size distribution of oil-PP NPs is not significantly altered in different media, particularly in DMEM commonly used for cell culture. Next, cytotoxicity assays were performed using the HEK293T cell line to assess the biological impact of PP MNPs. This kidney-derived cell line was selected for its relevance to renal filtration and excretion processes, which are essential for clearing dietary MNP exposure. To ensure that the observed cytotoxic effects were primarily due to the nanoparticles themselves rather than excess oil, we quantified the oil film volume surrounding PP NPs (Methods; Table S4). Based on these measurements, the estimated total oil film volume in the 200 µL suspension of oil-PP NPs at a concentration of 100 µg/mL used for cytotoxicity assays was 0.271 µL. This volume only accounts for 0.136% of the total suspension volume, suggesting that the observed cytotoxicity in the oil-PP NP group was unlikely to be caused by oil. After 24 hours of exposure, oil-PP NPs exhibited the highest toxicity, with significantly lower cell viability compared to oil-PP MPs, water-PP NPs, and water-PP MPs ( p < 0.0001). The IC50 values for oil-PP NPs, oil-PP MPs, water-PP NPs, and water-PP MPs were 18.7 ± 2.9, 122.3 ± 53.64, 77.1 ± 4.5, and 497.8 ± 78.1 µg/mL, respectively, confirming the greater toxicity of oil-derived particles, particularly NPs (Fig. 3 a). The LDH assay was conducted to assess cell toxicity within 24 hours, as LDH release serves as a direct marker of acute membrane damage, providing critical insights into the immediate cytotoxic effects of oil-PP NPs. Oil-PP NPs demonstrated dose- and time-dependent cytotoxicity in HEK293T cells, evidenced by elevated LDH activity. At a concentration of 100 µg/mL, LDH activity exceeded 60% within 120 minutes, indicating significant membrane damage ( p < 0.001), while lower doses resulted in reduced toxicity ( p < 0.001). In contrast, cells in the control group (0 µg/mL) maintained minimal LDH activity (Fig. 3 b). These findings were further supported by the cellular morphological analysis, which revealed distinct dose- and time-dependent changes in cellular structure. At 20 µg/mL, cellular morphology showed minor alterations after 180 minutes. At 50 µg/mL, membrane deformation was observed after 60 minutes, intensifying over time. Higher concentrations (75 and 100 µg/mL) caused rapid and severe membrane disruption, with the structural integrity severely compromised within 20–60 minutes at 100 µg/mL, leading to extensive cell detachment and death (Fig. 3 c). To simulate real-life consumption scenarios of ordering takeaway food multiple times in a day, multi-exposure experiments with oil-PP NPs (25 µg/mL added at 60-minute intervals) showed a significant increase in cell death and LDH activity after the second exposure ( p < 0.01), indicating potential cumulative toxicity from repeated low-dose exposure (Fig. 3 d, e). Cytotoxicity was further evaluated using HT29 and Caco-2 cell lines, which are relevant models for gastrointestinal exposure, using oil-PP NPs from various cooking oils. At 50 µg/mL and 100 µg/mL concentrations, all oil-PP NPs significantly increased LDH activity compared to water-PP NPs in HEK293T cells ( p < 0.05) and at 100 µg/mL in the other two cell lines ( p < 0.01) (Fig. 3 f-h). Among the tested particles, soybean oil-PP NPs exhibited the highest toxicity ( p <0.0001), likely due to their positive zeta potential, which may enhance cellular uptake. To explore the mechanisms underlying the observed cytotoxicity, laser confocal microscopy revealed that at 100 µg/mL, FL-oil-PP NPs (red) adhered to the cell membrane within 1 minute and extensively accumulated by 30–60 minutes, leading to cell swelling and membrane rupture, while nuclear (blue) structures remained intact (Fig. 4 a). These results indicate that oil-PP NPs may induce rapid cell death characterized by fast cellular uptake and membrane disruption processes. To further illustrate the differences in cellular uptake capacity between water-PP and oil-PP NPs, we generated time-dependent relative fluorescence intensity (RFI) curves. Oil-PP NPs exhibit significantly faster cellular uptake, with RFI sharply increasing and reaching saturation within approximately 60 seconds. In contrast, water-PP NPs show a slower uptake, with RFI beginning to increase notably after 100 seconds and gradually reaching saturation at around 1200 seconds. The rapid uptake of oil-PP NPs is likely due to their favorable interactions with the cell membrane and their efficient utilization of endocytic pathways (Fig. 4 b). TEM analysis revealed distinct effects of oil-PP and water-PP NPs on cellular morphology. In the control group, cells maintained their structural integrity with clearly defined membranes and normal cytoplasmic features. Similarly, no cellular damages were observed with water-PP NPs treatment. In contrast, cells exposed to oil-PP NPs exhibited severe plasma membrane damage, characterized by membrane rupture, swelling, and the formation of intracellular vesicles, which became evident within 5 minutes of treatment. Despite the pronounced membrane damage, the nuclear structure remained intact, indicating that oil-PP NPs predominantly targeted the cell membrane and cytoplasmic components without compromising nuclear integrity initially (Fig. 4 c). These findings demonstrate that oil-PP NPs can rapidly bind to cell membranes and induce cytotoxicity within 5 minutes, highlighting the potential health risks associated with ingesting oil-PP NPs from oil-rich foods stored or heated in plastic containers (Fig. 4 d). 2.7 Oil-PP NPs and Water-PP NPs Exposure Induce Differential Dose-Responsive Transcriptomic Responses To investigate cellular responses to oil-PP NP exposure, RNA sequencing revealed distinct dose-dependent transcriptomic changes compared to water-PP NPs. Experimental conditions were designed to simulate the acute toxic effects of plastic particles within a single day, reflecting realistic daily exposure scenarios (Methods). At high concentrations (50 and 100 µg/mL for 4 hours), oil-PP NPs activated inflammatory pathways (e.g., MAPK, TNF, IL-17) and suppressed metabolic processes (e.g., the citrate cycle, cell cycle, and aminoacyl-tRNA biosynthesis), indicating acute mitochondrial dysfunction and disrupted cellular homeostasis. Upregulation of the arachidonic acid metabolic pathway suggests cell membrane disruption driven by lipid peroxidation 31 (Fig. 5 a; Figure S7a), highlighting the acute cytotoxic potential of oil-PP NPs. In contrast, prolonged low-concentration exposure (10 and 25 µg/mL for 20 hours) resulted in upregulation of glycine, serine, and threonine metabolism, with continued suppression of oxidative phosphorylation and ribosomal activity, reflecting persistent mitochondrial stress and metabolic adaptation (Fig. 5 b; Figure S7b). Water-PP NPs showed distinct dose-dependent transcriptomic profiles compared to oil-PP NPs (Fig. 5 c; Figure S6c), activated stress pathways such as autophagy, apoptosis, and PI3K-Akt signaling at high concentrations, while prolonged exposure at low concentrations upregulated inflammatory pathways (e.g., NF-κB, complement cascades) and suppressed oxidative phosphorylation and ribosome biogenesis, indicating immune activation and metabolic suppression (Figure S6a, b; Figure S8a, b). However, oil-PP NPs elicited significantly stronger transcriptomic changes, with upregulation of 509 genes and downregulation of 206 genes at 50 µg/mL (4 hours), disrupting key pathways such as the lysosome function and mitophagy, leading to acute metabolic disruption and mitochondrial dysfunction. Water-PP NPs, on the other hand, mainly activated inflammation-related pathways (e.g., MAPK, PI3K-Akt signaling) under similar conditions (Fig. 5 d, e; Figure S9a). At 10 µg/mL for 20 hours, both oil- and water-PP NPs induced sustained inflammatory responses (e.g., NF-κB, Notch) and suppressed oxidative phosphorylation and ribosome, resulting in inflammatory and metabolic stress (Fig. 5 f; Figure S9b), suggesting potential cumulative damage under chronic exposure. These findings suggest that oil-PP NPs primarily cause acute metabolic disruption at high concentrations, while both oil- and water-PP NPs lead to chronic inflammatory damage and metabolic stress under prolonged low-concentration exposure, underscoring overlapping but distinct mechanisms of toxicity. 2.8 Human Exposure to MNPs and Heavy Metals Through Takeout Food: Intake Analysis, Geographic Distribution, and Benchmark Dose Modeling To connect the observed toxicity in cell lines to human health, we next sought to assess the annual MNP and harmful heavy metal (Cd, Cr, Ni, Pb) intake at the individual level and globally due to takeout food. We categorize ordering frequency as once a day, once a week, or once a month. Assuming each meal uses one PP or PE-coated container, and considering the worst-case scenario of microwaving with oil for 3 minutes, the annual PE MNP intake ranges from 0.58–22.36 g for adults and 0.27–10.75 g for kids, while the PP MNP intake ranges from 0.17–5.28 g for adults and 0.08–2.53 g for kids (Fig. 6 a; Methods). Heavy metal intake also varies, with adults consuming 0.00015 (Cd)–0.62 g (Cr) per year from PP containers ( p <0.01) and 0.00033 (Cd)–0.32 g (Ni) per year from PE containers ( p <0.001; Fig. 6 b). Kids have proportionally lower intakes (Figure S10a). Given the global prevalence of take-out food, we selected widely used microwave-safe PP containers to estimate MNP exposure from takeout food across 23 regions ( p = 0.027 across different regions; Table S5). The annual average PP MNP intake per adult was 1.37 g per region, ranging from 0.43 g in the United Kingdom to 3.35 g in China (Fig. 6 c; Figure S10b). Interestingly, among these regions, the mean and median annual per capita MNP intake in developed countries (e.g., the United States of America, Canada, France) are lower than those in developing countries (e.g., China, South Africa, Mexico) ( p <0.001; Figure S10c). Given these findings, it is essential to integrate this intake data with toxicological assessments to better understand the health risks associated with chronic exposure to MNPs. We conducted benchmark doses (BMDs) 32 analysis, a preferred method by the USEPA and EFSA for identifying doses that trigger specific adverse effects. We integrated data on altered cellular viability for oil- and water-PP MPs and NPs alongside transcriptomic data from cells exposed to 0, 10, 25, and 50 µg/mL of oil-PP NPs and water-PP NPs under prolonged exposure (20 hours). This analysis yielded BMD and BMDL values for 214 genes responsive to 20-hour oil-PP NP exposure and 597 genes associated with water-PP NP exposure. Most of these dose-responsive genes are implicated in oxidative stress, apoptosis, autophagy, and immune responses (Figure S10d,e). Our findings indicated that the safety limits for cell viability after 24-hour exposure of 4.83 µg/mL (oil-PP NPs), 25.86 µg/mL (oil-PP MPs), 27.01 µg/mL (water-PP NPs), and 111.8 µg/mL (water-PP MPs) (Fig. 6 d). Notably, several highly altered genes linked to cellular stress responses, inflammation, and immune activation exhibited significant dose-dependent changes following oil-PP NP exposure (Figure S10d). The lowest BMDL for oil-PP NPs was 1.18 µg/mL for RIPK2 , a key regulator of innate immunity and inflammation 33 (Fig. 6 d). In contrast, for water-PP NPs, the lowest BMDL was 7.94 µg/mL for FAS , which encodes a receptor critical for apoptosis and immune homeostasis 34 (Fig. 6 d; Figure S10e). These results highlight that oil-PP NPs affect immune and stress pathways—and potentially trigger inflammation and cell death—at much lower concentrations than water-PP NPs, underscoring the value of incorporating molecular-level endpoints in BMD assessments. To find out if these BMDLs (including MPs and NPs) are physiologically relevant, we systematically compiled absolute quantification data of MNP concentrations across 15 distinct human biological samples, including blood, liver, brain, placenta, and BALF, extracted from individual experimental studies (Table S7). Assuming that an exposure level of “µg/mL” in the medium corresponds to “µg/g” in tissues and considering all MNP exposure as cumulative, there is a realistic potential for subclinical and pathological damage associated with MNP exposure (Fig. 6 e). Notably, even in the blood, which exhibited the lowest observed MNP concentration (1.6 µg/mL), levels exceeded the lowest gene-based BMDL for oil-PP NPs (1.18 µg/mL). Placenta samples from healthy individuals showed an alarming MNP concentration of 126.8 µg/g, consistent with our previous study 23 , surpassing all BMDL thresholds, raising concerns about risks to both maternal and fetal health. Similarly, the brain, kidney, and liver showed significant MNP accumulation up to 4763 µg/g, with detected MNPs primarily composed of PE and PP 35 . The increasing MNP burden over time and its higher levels in dementia patients reinforce concerns about neurological and hepatic risks, supporting the need for further investigation into exposure pathways and health impacts. In pathological tissues, such as cumulus granulosa cells (313.1 µg/g), thrombi (105.5 µg/g), atherosclerotic plaques (118.66 µg/g), and bone marrow (51.3 µg/g), MNP concentrations consistently approached or exceeded BMDL values, suggesting that higher MNPs exposure is associated with pathological conditions. For example, in thrombi and atherosclerotic plaques, MNP-induced inflammation and oxidative stress could accelerate vascular damage and increase the risk of adverse cardiovascular events 36 . 3 Discussion This study represents a major advancement in understanding the health risks associated with MNPs from PFCMs under oil-rich conditions. By revealing how common practices, such as reheating oily foods in plastic containers, can significantly increase MNP release and toxicity, we address critical gaps in the current understanding of exposure pathways. Our findings highlight the amplifying effect of oil on both MNP release and toxicity while introducing a precise methodological framework for quantifying exposure. A core finding of this study is the significant role of cooking oils in enhancing MNP release from plastic containers, with oil increasing MNP release by up to 125-fold for PE-coated containers and 29-fold for PP containers (Fig. 2 a, b), reaching 130.93 mg per container after 3 minutes of microwave heating (Fig. 2 f). These levels far exceed those observed in water-based simulants, exposing a major limitation in current regulatory testing protocols. Furthermore, oil-exposed MNPs displayed smaller sizes (Fig. 2 c, d) and positive zeta potentials (+ 7.37 mV; Fig. 1 g), enhancing bioavailability, cellular uptake, and toxicity. With oily foods being a global dietary staple, this overlooked exposure pathway demands urgent attention. Our findings demonstrate that oil-derived MNPs are not only released in greater quantities but are significantly more toxic than water-derived counterparts. High concentrations of oil-PP NPs triggered acute inflammatory responses, mitochondrial dysfunction, and membrane disruption, leading to rapid cellular stress and loss of homeostasis, as confirmed by cell viability and LDH assays. At lower concentrations, oil-PP NPs induced sustained inflammatory and metabolic dysregulation, including suppression of oxidative phosphorylation and ribosome biogenesis. These effects suggest a dual toxicity profile: acute effects at high concentrations and chronic stress at low concentrations, with potential implications for the development of metabolic disorders, neurodegeneration, and cancer (Fig. 5 a, b). The heightened toxicity of oil-PP NPs compared to water-PP NPs and other nanoplastics, such as polystyrene, highlights the need to extend nanoplastic toxicity research beyond traditional water-based exposure models to account for real-world food matrices like oil, which may amplify both release and toxicological impacts 37 – 39 . Our global exposure estimates, derived from Py-GC/MS-based release data, further underscore the scale of this issue. The annual intake of oil-derived MNPs is highest in countries like China, where exposure levels can reach up to 3.35 g/year due to dietary habits and high rates of takeout food consumption (Fig. 6 c). These findings reveal a hidden yet pervasive public health threat, particularly in regions with diets in oil-rich, reheated, or fried foods. The current regulatory emphasis on water-based simulants is clearly insufficient to capture the true risks of plastic food-contact materials 6 , 7 , 40 , 41 . Our findings call for an urgent overhaul of testing protocols to incorporate oil-based simulants and account for the combined effects of MNPs and chemical additives in oil-rich environments. Additionally, our results underscore the importance of consumer education campaigns to reduce reliance on plastic containers for oil-rich foods. By using Py-GC/MS for absolute quantification of plastic exposure, we have established a robust framework that links exposure levels to toxicological outcomes through BMD analysis, setting an important example for MNP research. The lowest BMDL identified for oil-PP NPs was 1.18 µg/mL. The inclusion of MP-specific BMDL values ensures a balanced risk assessment, preventing overestimation that might occur if relying solely on NP data. Importantly, our study accounts for both water-based and oil-based particles, reflecting the distinct toxicological profiles and exposure scenarios of these MNPs. By incorporating both MP- and NP-specific BMDLs for oil- and water-based plastics, we establish a more comprehensive and nuanced framework for evaluating toxicity across different particle sizes and environmental contexts. We also compared these BMDL values with real-world MNP concentrations in human biological samples collected from 15 different tissues and fluids, including blood, brain, placenta, and gallstones. Remarkably, the concentrations of MNPs found in these pathological samples and healthy placenta mostly exceeded BMDL thresholds, some even for cell viability, suggesting that many individuals may already be exposed to levels of MNPs capable of causing adverse biological effects (Fig. 6 e). This underscores the urgent need for more comprehensive exposure assessments and regulatory updates to address the amplified risks posed by oil-rich foods. Future studies should explore alternative packaging materials that exhibit lower MNP release and toxicity. Promising candidates, such as bioplastics, glass, or stainless steel containers, should be evaluated for their suitability as safer alternatives to conventional plastics 42 – 44 . Moreover, to better understand the health impacts of chronic oil-derived MNP exposure, long-term in vivo studies and epidemiological investigations are essential. These studies should assess both the intake levels and the accumulation of MNPs in the body over time while determining the toxicity thresholds associated with prolonged exposure to fully elucidate the health risks. 4 Conclusions Our study highlights the critical role of cooking oil in promoting the release and cytotoxicity of smaller MNPs from PP and PE-coated takeaway containers, particularly after microwave heating. These findings reveal significant cellular health risks at physiologically relevant levels. Given the widespread use of cooking oils in global diets and the growth of the takeout industry, these findings raise major concerns about chronic dietary exposure to oil-derived MNPs and associated contaminants. Our results advocate for stricter regulations on plastic food packaging for oil-rich foods and highlight the need for developing safer alternatives and conducting long-term health impact studies to protect public health and the environment. 5 Methods 5.1 Characterizations of Plastic Containers Two anonymous brands of plastic food containers made of PP and PE materials were purchased from online stores (sales exceeding 3 million units) and restaurants in Hangzhou, China. These two types of containers were selected due to their widespread use in food packaging and delivery services. The compositions of the plastic containers were determined by the Attenuated Total Reflectance Fourier Transform Infrared spectroscopy (ATR-FTIR, NICOLET iS50FT-IR, Thermo Scientific, USA). The obtained IR spectra were compared with the database on the OMNIC software, and a polymer type was considered acceptable when the match with standard spectra was greater than 70%. At least three different batches of the containers were purchased at different times of the year and analyzed in the study. Their semicrystalline structure and thermal stability were analyzed by differential scanning calorimetry (DSC) using a Q200 differential scanning calorimeter (TA Instruments, New Castle, DE, USA). Approximately 8 mg sample was taken from each container, placed in an aluminum pan, sealed, and subjected to a thermal cycle at 10°C/min under a nitrogen atmosphere. The resulting calorimetric curves, which reflect heat transfer during the thermal cycle, were used to monitor phase transitions. X-ray diffraction (XRD) has been utilized to detect changes in crystalline and amorphous characteristics in plastic materials. To prepare the samples, we cut the PP containers and the inner plastic lining of the PE-coated containers into 0.5 × 0.5 cm pieces. Specimens were kept in an aluminum sample holder so that the upper surface was smooth and exposed to X-rays in vertical goniometry assembly. The scan was taken between (10–80°) 2θ with a scanning speed of 0.02-degree 2θ per min.; the operating target voltage was 35 kV, tube current was 20 mA, and radiation used was FeKα with a wavelength of 1.93735 Å on Rigaku Rotating anode mode RU-H3R (18Kw), X-ray powder diffractometer. The intensity versus 2θ scans were obtained for these plastic materials. The high-resolution field emission scanning electron microscope (SEM, Regulus 8230, Hitachi, Japan) was employed to reveal the surface morphologies of the inner walls of the plastic containers before and after treatments. 5.2 Release Experiments of Micro- and Nano-Plastics In total, three common real-life takeaway food scenarios using plastic containers were simulated: microwaving cold food (Group A-C), transportation (Group D-F), and leftover storage (Group G and H). To simulate different food types, food simulants were used: ultrapure deionized water (DI water; 18.2 MΩ·cm, Cascada™ water purification system, Pall, USA) and commercial cooking oils of anonymous brands (soybean, palm, blend, peanut, and sunflower oil) purchased from brand stores in China. DI water and cooking oils were stored in glass beakers and analyzed separately. Before the experiments, the PP and PE-coated containers were thoroughly rinsed with DI water and air-dried three times to remove residual MNPs during the manufacturing processes. For all experiments, containers were filled with 100 mL of one type of oil or DI water (Figure S1a). To simulate microwaving, containers filled with food simulants at room temperature were placed in a microwave oven (M1-201A, Midea, China) at 800 W for 1, 3, and 5 minutes. Following the previous study 45 , containers filled with food simulants were oscillated at 120 rpm on a horizontal rotary shaker (NMSP-600, NuoMi, China) for transportation simulation at room temperature for 15, 30, and 60 minutes. For leftover storage simulation, the containers were filled with oil or water, pre-heated to 95°C, and left at room temperature for 1 and 5 hours. We modified a previous study's procedure to concentrate the leachate and extract the plastic particles for subsequent analysis 46 . For oil-treated samples, 100 ml of oil was mixed with 300 ml of hexane (1:3 ratio) and vortexed for 30 seconds to ensure complete dissolution. Using a vacuum pump, the mixture was filtered through a vacuum filtration system. To remove residual oil, 60 ml of prefiltered hexane was added to the Anodisc filters (0.22 µm pore diameter, 25 mm diameter, Waterman, Germany) three times. Water-treated samples were poured directly into the vacuum filtration system for extraction. The filter membranes from both oil- and water-treated samples were then placed in a glass dish with 10 ml of 30% H 2 O 2 and incubated at 60°C for 1 hour to remove excess organics. The filters were subsequently sonicated for 1 hour to yield 10 ml concentrate leachate samples of MNPs. 5.3 Characterization of Micro- and Nano-Plastics Optical microscope (LV100N, NIKON, Japan), SEM, and Transmission Electron Microscopy (TEM, JEM-1400flash, JEOL Co., Ltd., Japan) were used to characterize the morphology of MPs and NPs. Raman microspectroscopy was used to characterize MNPs. A 100 mL leachate sample from different experimental groups was filtered through a 0.22 µm glass fiber filter (Shanghai Dibo Biotechnology Co., Ltd., Shanghai, China). The type and chemical composition of the plastic materials were characterized by ATR-FTIR spectroscopy (NICOLET iS50FT-IR, Thermo Scientific Inc., Waltham, MA). Zeta potential analysis was conducted using a laser particle sizer (Zetasizer Nano ZSE, Malvern, UK). A 1 mL aliquot of MNP solution from each sample type was placed in the sample pool for measurement. Soybean oil-treated samples were chosen for analysis, assuming similar properties in water-treated samples. The samples were analyzed with a Raman XploRA Nano Microspectrometer (Horiba Scientific, Kyoto, Japan), featuring a 785 nm laser and 600 lines per mm grating, covering a spectral range of 0 to 2200 cm⁻¹. Calibration was done using the silicon line at 520.7 cm⁻¹. Raw Raman spectra were processed with polynomial baseline correction and vector normalization using LabSpec 6 software. MNPs identification was based on matching spectra with the SLOPP Library of Microplastics and KnowItAll software (Bio-Rad Laboratories, Inc.), considering matches with a Hit Quality Index (HQI) score of 80 or above as reliable. 5.4 Micro- and Nano-Plastics Detection and Quantification We followed our previous protocol to assess the size and quantity of microplastics in the leachate 23 . A 5 µL droplet of the 10 mL concentrated leachate was mixed with 195 µL of 0.01 mg/mL Nile Red (Aladdin, China) solution in a 96-well plate and incubated at 55°C for 30 minutes for staining. Each leachate sample was processed in triplicate to ensure statistical robustness, with three blank controls included per plate. Fluorescence was measured using a BioTek Cytation 3 plate reader (Bio Tek Instruments, Inc., USA) at 4x magnification, with the Montage function used to quantify MPs as small as 6 µm in diameter. Consistent acquisition and analysis parameters were applied to all wells. The leachate samples were analyzed for the number of nanoplastics present using a Nanoparticle Tracking Analysis (NTA, NanoSight NS500, Malvern Panalytical Ltd, UK) followed by a previous study 47 , which is equipped with a 532 nm green laser to detect and count particles in 10 nm to 1 µm size range. In addition to the number, NTA also provided us with the size distribution of nanoplastic particles. Three leachate samples were analyzed for each release experiment. We selected Group B samples for Py-GC/MS analysis. The samples were filtered through a 25 mm GF/F glass fiber filter (220 nm mesh, Whatman, UK). To eliminate plastic contamination, the filters were preheated in a 500°C nitrogen-purged muffle oven before filtration. Plastic particles were retained on the filter. The residue was then rinsed with 10 mL of 30% H₂O₂ (Merck, Germany) and 15 mL of deionized (DI) water. The inner circle containing the analyte (Figure S2e) was cut from the filter using a stainless steel blade, dried at 45°C for 4 hours, and subsequently transferred to a pyrolysis cup. Analysis was performed using the multishot pyrolysis unit EGA/PY-3030D (Frontier Laboratories, Saikon, Japan) in “single shot” mode. The GC/MS system (Trace 1300 GC and ISQ 7000 MS, Thermo Fisher, Waltham, MA, USA) was equipped with a TG-5SILMS column (30 m × 0.25 mm × 0.25 µm, Thermo Scientific Inc., Waltham, MA, USA). Measurements were conducted in selected ion monitoring (SIM) mode with a 1:50 split ratio. The temperature program started at 40°C, held for 2 minutes, then increased at a rate of 20°C/min to 320°C and held at 320°C for 14 minutes. During the analysis, an ion scan range of m/z 29–600 was used to identify and quantify the polymers of the target plastic particles. Indicator ions for PP and PE, 2,4-dimethyl-1-heptene (m/z 126) and 1-docosane (m/z 83), were employed. Standards for target microplastics (PP and PE) were first analyzed, and standard curves for PP and PE quantification were constructed to determine the mass of MNPs in all samples (Figure S2e and Table S1). The NIST17 library spectrum was used for compound identification, and peak areas were calculated using the normalization method. 5.5 Heavy Metal Analysis The triplicate samples collected from soybean oil-treated and DI water-treated containers, after 3 minutes of microwave heating, were analyzed for heavy metal content. Following established protocols 48 , the samples were homogenized and digested using a microwave digestion system (Anton Paar, Graz, Austria) with a tri-acid mixture of nitric acid (HNO 3 ), sulfuric acid (H 2 SO 4 ), and perchloric acid (HClO 4 ) in a 5:1:1 ratio. Post-digestion, the samples were filtered, diluted in ultrapure water, and analyzed using an Inductively Coupled Plasma Mass Spectrophotometer (ICP-MS) (Agilent Technologies 7800 ICP-MS, Santa Clara, CA, USA). 5.6 Analysis of Organic Additives in Plastic Materials We followed the protocol of the previous study 49 . Methanol (99.8%, Sigma-Aldrich) was used to extract chemicals from plastic materials due to its ability to extract a wide range of compounds without dissolving the polymers. To prevent contamination, all consumables used in the extraction, except plastic pipet tips, were made of glass or stainless steel, rinsed with ultrapure water and acetone, and heated at 200°C for at least 2 hours. Each 1.5 g sample was cut into smaller pieces (0.5–0.8 × 2 cm, thickness ≤ 0.4 cm) and extracted with 9 mL of methanol in glass vials with polytetrafluoroethylene-lined lids. Extraction was carried out by sonication for 1 hour at room temperature. Afterward, 1 mL of the extract was removed for chemical analysis and stored at − 20°C in glass vials. Four procedural blanks (PB 1–4) containing only methanol underwent the same procedure as the samples to control for potential contamination. Afterward, we applied nontargeted LC-MS/MS by an Acquity UPLC BEH C18 column (2.1 × 100 mm i.d., 1.7 µm, Waters) coupled to a SCIEX X500B quadrupole time-of-flight (Q-TOF) mass spectrometer (AB SCIEX Pte. Ltd., USA) in positive ionization modes. The data acquisition was operated in full MS scan mode and information-dependent acquisition (IDA)-MS2 scan mode. During data acquisition, the quality control (QC) sample (generated by pooling all the samples) and blank samples (laboratory, transport, field, and extraction) were injected between every 10 sample injections. The mass spectrometry data were centroided and converted from the proprietary format (.raw) to the m/z extensible markup language format (.mzML) using ProteoWizard (MSConvert tool, ver. 3.0.21094). After comparing upstream processing parameters using IPO, Autotuner, and SLAW, SLAW was selected for parameters optimization, mass feature extraction, isotopic patterns extraction, peak grouping, and deisotoping. The resulting feature quantification tables (.CSV) and MS 2 consensus spectra (.MGF) were then exported for further analysis. All sample spectra were processed separately because their different chemical compositions prevented a joint retention time alignment. Features (ions with a unique m/z and retention time) with an abundance of less than 10-fold the highest across procedure blanks (PBs) and solvents were excluded from further analysis. Additionally, the abundance of the features was corrected by subtracting the maximum abundance of the respective features detected in the PBs. For data annotation, metabolite identification was performed using spectral entropy based on accurate mass (± 0.01 Da) and MS 2 similarity against public databases. Specifically, the MS 2 reference database was constructed by integrating open-source databases from the GNPS community (495,662 spectra as of 2022-06-18), the MoNA dataset (1,951,233 spectra as of 2023-02-07), and the NIST2020 Tandem Mass Spectral Library (1,143,815 spectra). All metabolites annotated through spectral matching were considered level 2 annotations. 5.7 In Vitro Cell Viability Study A 4-hour high-concentration exposure (50 and 100 µg/mL) modeled acute, high-dose intake events, such as ingestion of highly contaminated food or water during the typical postprandial digestion and absorption period when PP NPs interact with gastrointestinal cells and translocate into the systemic circulation. Conversely, a 20-hour low-concentration exposure (10 and 25 µg/mL) simulated cumulative retention from repeated dietary intake throughout the day, mimicking gradual nanoparticle buildup in tissues and digestive compartments. To assess the potential toxicity caused by the oil film, we first evaluated the volume of the oil film covering the surface of PP NPs. We analyzed at least five different TEM images of 250 oil-coated PP NPs using ImageJ software (National Institutes of Health, USA) to measure the average particle size of PP NPs both with and without the oil film. This assumption simplifies the estimation of the oil film volume by treating the nanoparticles as uniform, non-deformable spheres with a well-defined core and oil-coated outer layer. These measurements allowed us to estimate the oil film thickness and subsequently calculate the total oil volume in the suspension (Table S4). The oil film volume was calculated using the following equations: $$\:{V}_{oil,\:single\:}=\:\frac{4}{3}\pi\:\:\left[{\left(\frac{{D}_{total}}{2}\right)}^{3}-\:{\left(\frac{{D}_{core}}{2}\right)}^{3}\right]\:$$ Here, \(\:{V}_{oil,\:single\:}\) represents the oil film volume per nanoparticle, \(\:{D}_{total}\) is the total diameter of the oil-coated PP NP (measured from TEM images, 150.95 nm), and \(\:{D}_{core}\) is the diameter of the PP NP core without the oil film (63.68 nm). By subtracting the core volume from the total volume, we obtained the volume of the oil layer surrounding each nanoparticle. To estimate the total oil film volume in the nanoparticle suspension, we used the nanoparticle mass concentration, the density of polypropylene and the single-particle oil film volume: $$\:{V}_{oil,\:\:total}=\frac{{C}_{mass}}{\frac{4}{3}\pi\:{\left(\frac{{D}_{core}}{2}\right)}^{3}\times\:\:{\rho\:}_{PP}}\times\:\:{V}_{oil,\:single}$$ Here, \(\:{V}_{oil,\:\:total}\) is the total oil film volume in the solution, \(\:{C}_{mass}\) is the PP NP mass concentration (µg/mL), and \(\:{\rho\:}_{PP}\) is the density of polypropylene (~ 0.91 g/cm³). The denominator represents the estimated number of nanoparticles per µL of solution, calculated from the core volume and material density. It is important to note that this calculation assumes a uniform spherical shape for all PP NPs and a homogeneous oil film distribution. These estimations provide an approximation of oil exposure but do not account for potential aggregation of nanoparticles, variations in oil adsorption efficiency, or dynamic changes in oil film properties over time. The actual bioavailability and toxicity of the oil film may also be influenced by interactions with environmental and biological factors, including surfactant behavior, protein corona formation, and enzymatic degradation. Cell Culture, Cell Viability, and Cytotoxicity Assay Human embryonic kidney 293T (HEK293T) cells were cultured in RPMI 1640. Human colon adenocarcinoma (HT29) and Caucasian colon adenocarcinoma (Caco-2) cells were grown in DMEM with 10% fetal bovine serum and 1X penicillin/streptomycin. All cells were maintained in a 37 o C humidified incubator with 5% CO 2 . MPs and NPs derived from PP food containers were selected for cytotoxicity assessments, given that these containers are among the most frequently utilized microwaveable plastic vessels in daily life. 20 g of PP plastic was weighed and placed into an autoclaved glass bottle containing 200 mL of DI water or cooking oil to simulate the microwave heating process accurately. The plastic samples were then subjected to microwave heating at 800 W for 3 minutes Water-PP MPs and Oil-PP MPs: The MNP solution was filtered through a PTFE membrane (Jingteng, China, pore size 0.8 µm). The particles collected on the filter were rinsed into a glass dish with ethanol, vortexed for 30 seconds, and centrifuged at 15,000×g at 4°C for 10 minutes. The purified water-PP MPs were then used for subsequent analyses. Water-PP NPs: The MNP solution was filtered through a PTFE membrane (Jingteng, China, pore size 0.2 µm). The filtrate was collected and concentrated using an Anodisc filter membrane (pore size 20 nm). The NPs were transferred into a glass dish with ethanol, vortexed for 30 seconds, and centrifuged at 15,000×g at 4°C for 10 minutes. The purified water-PP NPs were used for subsequent analyses. Oil-PP NPs: The MNP solution was filtered through a PTFE membrane (Jingteng, China, pore size 0.2 µm). The filtrate was centrifuged at 15,000×g at 4°C for 20 minutes. The purified oil-PP NPs were used for subsequent analyses. To prepare the MPs and NPs derived from edible oil and DI water for subsequent cellular experiments, they were purified to eliminate chemical residues. The purification process involved the following steps: the MPs and NPs precipitate was resuspended in ethanol, ultrasonicated for 10 minutes, and then centrifuged at 15,000×g at 4°C for 20 minutes. The precipitate was then resuspended in 0.1% SDS solution and ultrasonicated for 10 minutes to achieve uniform dispersion of the MPs and NPs, a process repeated three times. Finally, the thoroughly washed precipitate was resuspended in 0.1% SDS solution to create a homogeneous dispersion (ultrasonicated for 30 minutes), sterilized, and stored for future use. The morphology of the MPs and NPs used for cytotoxicity studies was examined using transmission electron microscopy (TEM). The fluorescence-labeled oil-PP NPs were observed by a Super-Resolution Microscope System (GE DeltaVision OMX SR, GE Healthcare, USA) with a laser of 588 nm. Dynamic light scattering (DLS) analysis was performed using a laser particle sizer (Zetasizer Nano ZSE, Malvern, UK). Specifically, the MPs and NPs solution was ultrasonicated for 30 min to disperse uniformly. Then, 1 mL NPs solution was taken into the sample pool to measure the particle size distribution, Zeta potential, and polydispersity index (PDI). The size distribution of NPs was also analyzed using NTA. The culture medium was then replaced with a fresh medium, free of FBS, containing PP MNPs at varying concentrations. For cell viability assay, for example, HEK293T cells were seeded in a 48-well plate at a density of 5 × 10 4 cells/well and incubated for 24 h. After treatment with different doses (2, 5, 10, 20, 30, 50, 70, 100, 200, 500, 1000, and 2000 µg/mL) of MNPs for 24 h, covering a broad range of concentrations to assess dose-dependent effects, 20 µL of cell counting kit-8 (CCK-8) solution was added to each well, and the absorbance was measured at 450 nm by a Micro Plate Reader. For the lactate dehydrogenase (LDH) activity assay, cells were seeded in a 48-well plate at a density of 5–10 x10 5 cells/well. After treatment with NPs for 3h, the cell culture supernatant was collected from each sample. The LDH enzyme activity (mU/ml) was measured using the LDH Cytotoxicity Assay Kit according to the manufacturer’s instructions. Each assay was repeated three times. The relative cell and cytotoxicity were normalized to the control group (200 µl of culture medium) using optical density values. Observation of Cellular Uptake of NPs For fluorescence imaging, oil-PP NPs and water-PP NPs were labeled with iDye Poly Pink (Rupert, Gibbon & Spider, Inc., Healdsburg, CA, USA). In brief, 0.01 g of the dye was combined with 1 mL of the stock particle suspension and incubated at 70°C for 2 hours. After cooling, the mixture was diluted with 9 mL of ethanol and centrifuged at 4000 rpm for 15 minutes. This washing process was repeated twice. The fluorescence-labeled-PP NPs were then collected and resuspended in 1 mL of 0.1% SDS solution. HEK293T cells were inoculated in a 6-well plate. The cells were incubated with fluorescent NPs (FL-oil-PP NPs or FL-water-PP NPs ) at a 100 µg/mL concentration for different durations. Fluorescence images were obtained using a laser confocal microscope (ECLIPSE TI, NIKON, Japan). The experiment was conducted away from light. To observe the cellular uptake of NPs, the cells were washed twice with PBS (1×) at room temperature, and they were treated with PBS (1×) containing 0.1% Triton X-100 for 3–5 min to make the membrane more permeable. To reduce the background's non-specific staining, 1 mL of PBS (1×) containing 1% bovine serum albumin was incubated with the cells for 30 min. Finally, the nucleus of the cells was analyzed using Hoechest44423. TEM Analysis The cell microstructure and integrity were investigated utilizing TEM (JEM-1400flash, JEOL Ltd., Tokyo, Japan). After 5 minutes of exposure to 100 µg/mL NPs, the cells were fixed in 2.5% glutaraldehyde at 4°C for 30 min. The fixed cells were washed, treated with osmium tetroxide, and dehydrated using ethanol solutions. Ultrathin cell Sects. (70–90 nm) were obtained and subjected to TEM analysis according to a previous protocol 50 . Transcriptomic Analysis The RNA sequencing and library construction was performed by Annoroad Co., Ltd. (Beijing, China). Kallisto software (v0.46.1) 51 was used to quantify transcript abundance from RNA-seq data against GRCh38 cDNA reference transcriptome from the Ensembl database. Tximport package (v1.32.0) 52 integrated the transcription level into the gene expression level against the TxDb.Hsapiens.UCSC.hg38.knownGene database (v3.18.0) 53 . Gene differential analysis and expression normalization were performed by the DESeq2 package (v1.44.0) 54 . The functional enrichment analyses were performed using ReporterScore (v0.1.8) 55 and org.Hs.eg.db (v3.19.1) 56 packages. 5.8 Human Exposure Estimation We estimated the human exposure to MNPs and heavy metals using MNP and heavy metal release rates from PP and PE-coated containers filled with oil under 3-minute microwave heating (data from this study), the frequency of people ordering takeout food, and the adults (18–59 years old) and kids (0–3 years old) daily fat intake mass (Table S5). We also collected data on the frequency of take-out food orders in 23 regions worldwide to calculate the global exposure of MNPs (Table S6). The MNP and heavy metal exposure was assessed using the following equation: $$\:MH{P}_{i}={V}_{i}\times\:mh{p}_{Ii}\times\:{F}_{j}$$ Here, “ \(\:MH{P}_{i}\) ” is the annual intake of MNPs or heavy metals (grams per year), index “i” refers to the type of plastic containers (PP container and PE-coated container), “ \(\:{V}_{i}\) ” is the intake weight of the average meal (fat) per person obtained from Food and Agriculture Organization of the United Nations (FAO) 57 , 58 , the lunch consumption was used for the annual intake calculation of MNPs and heavy metals, accounting for 40% of the total daily food intake, based on the dietary ratio of 30%:40%:30% for breakfast, lunch, and dinner, respectively (Table S4), “ \(\:mh{p}_{Ii}\) ” is the concentration of MNPs and heavy metals that migrated into oil under 3-minute microwave heating (e.g., MNPs released from PP container filled with oil: 0.43 g g − 1 , MNPs released from PE-coated container filled with oil: 1.68 g g − 1 ), index “j” refers to the frequency of consuming take-out food, and “ \(\:{F}_{j}\) ”, is the total number of take-outfood orders a person consumes annually based on the different frequencies of take-out food orders. It is important to note that this calculation only estimates the amount of MNPs and heavy metals ingested through dietary exposure and does not account for potential digestion, degradation, or transformation of MNPs in the gastrointestinal tract. The actual bioavailability and toxicity of ingested MNPs may vary depending on their physicochemical properties and interactions with digestive processes. To evaluate toxicological responses, benchmark dose (BMD) calculations were performed using data with significant dose-response relationships. This included both cell viability data and molecular markers, as illustrated in Fig. 3 a and Fig. 6 d. We employed a continuous endpoint approach for all features. The selection of the optimal BMD model within the USEPA BMDS framework was conducted through a consensus-based approach. This involved multiple criteria, including a goodness-of-fit threshold with a p-value greater than 0.10; the lowest AIC; a BMD to BMDL (lower 95% confidence interval) ratio less than 5; and a visual inspection of the curve fit to ensure both plausibility and model parsimony. For our analysis, the default confidence level was set at 95%, corresponding to a one-sided 95% confidence limit. We opted to use the lower confidence limit of the BMDL for deriving health guidance values, as it offers a more conservative and precautionary estimate of the toxic dose. For gene-based BMD analysis, we used the BMDExpress software (v2.30.0515 BETA) to calculate the transcriptomic-level BMD and BMDL. 5.9 Quality Assurance and Control (QA/QC) To minimize potential plastic contamination, multiple measures were implemented throughout the experimental process. Plastic containers used for the experiments were carefully selected from the middle of each stack to avoid contamination from external plastic particles or debris. Laboratory personnel wore nontextile lab coats and particle-free nitrile gloves to prevent secondary contamination, with lab coat sleeves securely tucked into gloves at all times. Additionally, all work was conducted in a clean workspace with minimized airflow disturbances to reduce the risk of airborne particle contamination. All glassware used in the experiments was rigorously cleaned by rinsing three times with anhydrous ethanol, followed by ultrapure water, to ensure no residual contaminants remained. Ultrapure water and ethanol were filtered to remove any possible plastic contaminants before use. Equipment and work surfaces were thoroughly cleaned and inspected before each experiment. To ensure reproducibility and reliability, each experiment was conducted in triplicate using three identical containers per condition. The results from these replicates were averaged to account for variability and reduce random errors. Blank controls (no plastic container or sample added) were also included in each experimental setup to monitor and quantify background contamination levels, ensuring that any observed results originated solely from the experimental treatments. For MP and NP detection and quantification, rigorous quality control measures were implemented. The fluorescence measurements were calibrated using certified polystyrene microsphere standards (1-100 µm), maintaining RSDs below 10%. NTA analysis included daily calibration with NIST-traceable standards (100 nm and 200 nm), with measurements accepted only when standard values were within ± 5% of nominal values. For Py-GC/MS analysis, method blanks were run every 10 samples, with CCVs analyzed every 12 hours. Method detection limits were 0.06 mg/mL for PP and 0.09 mg/mL for PE, with recoveries of 96% and 123%, respectively. And calibration curves maintaining R² > 0.99. For metal analysis by ICP-MS, quality control included analysis of certified reference materials (NIST SRM 1643f) every 20 samples. The instrument was calibrated using multi-element standard solutions (0.1–100 ppb), with internal standards (Sc, In, Bi) used to correct for matrix effects and instrument drift. Method blanks were analyzed every 10 samples, and detection limits were determined as 3σ of method blanks. Recovery rates for spiked samples ranged from 85–115%, with RSDs < 10% for all elements. Duplicate analyses were performed every 10 samples, with acceptance criteria of ± 15% relative percent difference. For cell culture experiments, all reagents were tested for endotoxin contamination using the LAL assay. Mycoplasma testing was performed monthly using PCR-based detection. Cell line authentication was conducted using short tandem repeat (STR) profiling before experiments. For viability assays, positive and negative controls were included on each plate, and edge wells were avoided to prevent edge effects. Z-factors were calculated for each plate to ensure assay quality, with acceptance criteria of Z' > 0.5. RNA sequencing quality control included RNA integrity number (RIN) assessment (minimum RIN > 8), library quality control using Bioanalyzer, and sequencing quality metrics (Q30 > 80%, mapped reads > 80%). For differential expression analysis, batch effects were monitored using principal component analysis, and technical replicates showed Pearson correlation coefficients > 0.95. The sequencing depth was monitored to ensure > 20 million uniquely mapped reads per sample. For LC-MS/MS analysis of organic additives, quality control samples (QCs) were injected every 10 samples to monitor system stability. Retention time drift was maintained within ± 0.1 minutes, and mass accuracy was kept within ± 5 ppm. Internal standards were spiked into each sample to monitor extraction efficiency and instrument performance. The relative standard deviation of internal standards was maintained below 15% throughout the analytical sequence. Statistical quality control included testing for normality, homoscedasticity, and outliers before analysis. Power calculations were performed to ensure adequate sample sizes for detecting biologically meaningful differences. For multiple comparisons, appropriate corrections were applied to control for false discovery rates. All statistical analyses were performed using validated methods and software versions, with results independently verified by two researchers. All experimental procedures were documented in detail, including lot numbers of reagents, instrument parameters, and any deviations from standard protocols. Raw data were backed up in triplicate, and all analysis scripts were version-controlled. Regular external quality assessment was performed through participation in inter-laboratory comparison studies where available. 5.10 Statistical Analyses For the analysis of univariate variables, non-parametric statistical tests (e.g., Kruskal-Wallis and Kolmogorov-Smirnov (KS) tests) were employed for data that did not meet the assumption of normality, as evaluated using the Shapiro-Wilk test. The KS test was applied to compare differences in size distributions of micro(nano)plastics (MNPs) across conditions. Parametric tests, including one-way ANOVA, were used for normally distributed data to assess variability across groups. For example, the release of MNPs under different exposure conditions was analyzed using one-way ANOVA followed by post hoc Tukey tests for pairwise group comparisons. To compare concentrations of MNPs between oil and water samples, Student’s t-tests were conducted, providing statistical evidence for significant differences between the two matrices. Generalized linear models (GLMs) with logarithmic link functions were applied where necessary to investigate dose-dependent trends related to exposure. We conducted our primary statistical analyses using custom scripts within a Linux environment and R (version 4.4.1) through RStudio. Data visualizations were also generated using RStudio. Data are expressed as mean ± standard error unless otherwise specified. The significance threshold for all statistical tests was set at α = 0.05, and p -values were corrected for multiple comparisons using the Bonferroni or Benjamini-Hochberg method where applicable. Declarations Data availability The raw sequencing reads were submitted to ENA under project ID PRJEB84915. Acknowledgments We extend our gratitude to our colleagues at the core facility of the Life Sciences Institute, particularly the NECHO high-performance computing cluster. We also thank Min Zhou from the Instrumentation and Service Center for Molecular Sciences at Westlake University for their support with Py-GC/MS measurements and data interpretation. This research was supported by grants from the National Natural Science Foundation of China (NSFC) (82173645, 82341109, U21A20356, and 31371417). Author Information Authors and Affiliations MOE Key Laboratory of Biosystems Homeostasis & Protection, and Zhejiang Key Laboratory of Molecular Cancer Biology, Life Sciences Institute, Zhejiang University, Hangzhou, China Ruwen Xie, Gulimire Yilihan, Qiong Chen, Zhen Liu, Mengyi Yuan, Wanxin Gong, Yueer Li, Weishang Zhou, Xin-Hua Feng, Mu Xiao* & Chao Jiang* Center for Life Sciences, Shaoxing Institute, Zhejiang University, Shaoxing, Zhejiang, China Xin-Hua Feng, Mu Xiao* & Chao Jiang* Cancer Center, Zhejiang University, Hangzhou, Zhejiang, China Xin-Hua Feng & Mu Xiao* State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China Chao Jiang* Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA Peng Gao Department of Biological Sciences, Clemson University, Clemson, SC, USA Qing Liu Center for Human Genetics, Clemson University, Greenwood, SC, USA Qing Liu Contributions R.X., M.X., and C.J. conceptualized the research. R.X., M.X., and C.J. planned and performed the research. R.X. developed the software, visualized the data, analyzed the data, validated the findings, and wrote the original draft. G.Y., Q.C., and Z.L. contributed to formal analysis, validation, data curation, and reviewed and edited the manuscript. M.Y. curated the data and reviewed and edited the manuscript. W.G. visualized the data and reviewed and edited the manuscript. P.G., Q.L., and X.F. contributed to the methodology and reviewed and edited the manuscript. M.X. and C.J. supervised the project, acquired funding, and reviewed and edited the manuscript. Corresponding author Correspondence to Mu Xiao and Chao Jiang. 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Generalized reporter score-based enrichment analysis for omics data. Briefings in Bioinformatics 25 , bbae116 (2024). Carlson, M. org.Hs.eg.db. Bioconductor https://doi.org/10.18129/B9.BIOC.ORG.HS.EG.DB (2017). Dietary Guidelines for Americans, 2020-2025. Human energy requirements. https://www.fao.org/4/y5686e/y5686e08.htm#TopOfPage. Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryInformationoilplasticpaperNN.docx Dataset 1 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6015466","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":431597230,"identity":"f6f83183-21de-4038-9be7-7d99c5f4accf","order_by":0,"name":"Chao Jiang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8ElEQVRIiWNgGAWjYBACxmYIncDAwHyAQQLEPEC8FrYE4rTAAFALjwGESUgLczvzs4dfGOzy+Nt7Pn+wbGOQ47uRwPi5AK/D2MyNZRiSiyXOnN1gINnGYCx5I4FZegZeLQxm0hIMBxIbbuRuSABqSdxwI4GNmQevFvZvYC3zb+Q8OADUUk+EFh4zyQ9ALRtu5DA2ALUkGBChpUyagSE5ceOZY8YMEuckDGeeedgsjU+LYf/xbZI/GOwS5x1vfvxZosxGnu948sHPeLU0AAOa9x+EwywBjkzGBjwaGBjkQUp+wFz5Aa/aUTAKRsEoGKkAAF3fSYQ2EX46AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-0260-7271","institution":"Zhejiang University","correspondingAuthor":true,"prefix":"","firstName":"Chao","middleName":"","lastName":"Jiang","suffix":""},{"id":431597231,"identity":"0e628662-308c-4436-a1eb-fad870a6bd55","order_by":1,"name":"Ruwen Xie","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Ruwen","middleName":"","lastName":"Xie","suffix":""},{"id":431597232,"identity":"42fa2c0f-6297-42ac-982b-27060deae398","order_by":2,"name":"Gulimire Yilihan","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Gulimire","middleName":"","lastName":"Yilihan","suffix":""},{"id":431597233,"identity":"6b9d0fd9-c151-40f5-9dcc-77f01dabbf84","order_by":3,"name":"Qiong Chen","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Qiong","middleName":"","lastName":"Chen","suffix":""},{"id":431597234,"identity":"dce49b22-f780-4270-8843-df2bd52c8060","order_by":4,"name":"Zhen Liu","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Zhen","middleName":"","lastName":"Liu","suffix":""},{"id":431597235,"identity":"919a91c1-13c3-46ad-b1d7-a64dc922348b","order_by":5,"name":"Mengyi Yuan","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Mengyi","middleName":"","lastName":"Yuan","suffix":""},{"id":431597236,"identity":"be630e79-628f-4dbd-b375-0511dbbbb11d","order_by":6,"name":"Wanxin Gong","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Wanxin","middleName":"","lastName":"Gong","suffix":""},{"id":431597237,"identity":"6f6e9b92-110f-4e2d-a971-29d6d74aa6d5","order_by":7,"name":"Yueer Li","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Yueer","middleName":"","lastName":"Li","suffix":""},{"id":431597238,"identity":"b19d71c0-c2f8-47c9-af59-68b62cadb9b7","order_by":8,"name":"Weishang Zhou","email":"","orcid":"","institution":"Zhejiang University","correspondingAuthor":false,"prefix":"","firstName":"Weishang","middleName":"","lastName":"Zhou","suffix":""},{"id":431597239,"identity":"9e5c6cdc-f1b5-4cb7-a348-f611db81a1d2","order_by":9,"name":"Peng Gao","email":"","orcid":"https://orcid.org/0000-0002-4311-584X","institution":"Harvard T.H. 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(b-c) Characterization of two types of take-out food containers: images of (b) PP container; (c) PE-coated container; (d) Differential scanning calorimetry (DSC) curves during first heating at 10 °C/min of PP container and PE-coated container; (e) XRD patterns of PP container and PE-coated container. (f) TEM images of PP MPs, PP NPs, PE MPs, and PE NPs from different types of plastic containers treated with DI water and soybean oil. (g) Zeta potential of plastics released from PP containers and PE-coated containers. The \u003cem\u003ep\u003c/em\u003e-values for statistical differences were assessed using the Kruskal-Wallis test. Data are expressed as the mean ± standard deviation (n=3).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6015466/v1/76a88aedd31da09c6a056fc2.png"},{"id":79656562,"identity":"cf82d704-4104-4461-acef-1de938edbb51","added_by":"auto","created_at":"2025-04-01 08:58:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":816590,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbundance, size distribution, and mass of MNPs released from PP and PE-coated containers under microwave heating. \u003c/strong\u003e(a) The abundance of PP MPs and PP NPs, (b) the abundance of PE MPs and PE NPs, (c) the size distribution of PP MPs and PP NPs, (d) the size distribution of PE MPs and PE NPs, (e) Samples of PP and PE-coated containers microwave heated with oil for 1, 3, and 5 minutes, (f) Mass of MNPs per container derived from 100 mL oil and water after 3 minutes of microwave heating. The \u003cem\u003ep\u003c/em\u003e-values for statistical differences were assessed using the Student’s t-test, two sample Kolmogorov-Smirnov tests, and the Kruskal-Wallis test where applicable. Data are expressed as the mean ± standard error (n = 3).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6015466/v1/3e5ffe1c4e5fa5088b67d493.png"},{"id":79656564,"identity":"ffae285b-fd8f-4214-bbb3-0a3823fd3b55","added_by":"auto","created_at":"2025-04-01 08:58:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":891884,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCytotoxicity of different types of PP MNPs. \u003c/strong\u003e(a) Cell viability of HEK293T cells after treatment with various MPs and NPs (oil-PP NPs, oil-PP MPs, water-PP NPs, and water-PP MPs) at concentrations ranging from 5 to 2000 μg/mL for 24 hours. (b-c) Short-term exposure to high concentrations of oil-PP NPs induces cell death. After treatment with oil-PP NPs (20-100 μg/mL), cells were imaged and lactate dehydrogenase (LDH) release was measured. Representative phase-contrast images are shown in panel B (scale bar: 20 μm). Panel C shows the statistical analysis of LDH release for each group. (d-e) Continuous exposure to low concentrations of oil-PP NPs also induces cell death. Representative phase-contrast images are shown in panel D (scale bar: 20 μm). Panel E provides the statistical analysis of LDH release. (f-h) Cytotoxicity of four types of oil-PP NPs in HEK293T (f), HT29 (g), and Caco-2 (h) cells after treatment with 50 and 100 μg/mL for 3 hours. The statistically significant difference compared to the control group or water-PP NPs treated groups isindicated. The \u003cem\u003ep\u003c/em\u003e-values for statistical differences were assessed using the GLM and \u003cstrong\u003eStudent's t-test\u003c/strong\u003es (*\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05; **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01; ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001; ****\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.0001) where applicable. Data are expressed as the mean ± standard deviation (n = 3).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6015466/v1/332173152d3a9e22588f26c8.png"},{"id":79656566,"identity":"79b00795-ceb6-4cfa-a2d3-26d82858123e","added_by":"auto","created_at":"2025-04-01 08:58:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":630622,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCellular internalization of oil-PP NPs.\u003c/strong\u003e(a) Oil-PP NPs demonstrate rapid cell uptake when exposed to HEK293T cells. HEK293T cells were treated with 100 μg/mL oil-PP NPs and imaged. Representative phase contrast and fluorescent images are shown. The scattering light signal of oil-PP NPs is labeled with iDye Poly pink (red), and the nucleus is stained with Hoechst 33342 (blue). Scale bars represent 10 μm. (b) Relative fluorescence intensity (RFI) of FL-oil/ water-PP NPs (red) treated 293T cells, and nuclei were stained by Hoechst 33342 (blue). (c) Transmission electron microscopy (TEM) images of cellular internalization of soybean oil-PP NPs (100 μg/mL) in Caco-2 cells. Cells were fixed after treatment with 100 μg/mL oil-PP NPs or water-PP NPs for 5 minutes. Significant oil-PP NPs are observed in the cell membrane and cytoplasm. Scale bars represent 1 μm for the original images and 500 nm for the zoomed-in images. (d) Schematic diagram illustrating the rapid cell death triggered by oil-PP NPs.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6015466/v1/031030b3807cfcad2e4ce3fe.png"},{"id":79656565,"identity":"541af4da-01e2-4960-af45-9fbab714c2d3","added_by":"auto","created_at":"2025-04-01 08:58:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1039565,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparative transcriptomic and pathway enrichment analyses reveal differential cellular responses to oil-PP NPs and water-PP NPs exposure over time. \u003c/strong\u003e(a) Gene-function integration map tree related to differential enriched pathways with significant (|ReporterScore| \u0026gt; 2, \u003cem\u003ep\u003c/em\u003e.adj \u0026lt; 0.05) increases (green) or decreases (red) in 4 hours of exposure to oil-PP NPs.\u0026nbsp;(b) Gene-function integration map tree related to differential enriched pathways with significant (|ReporterScore| \u0026gt; 2, \u003cem\u003ep\u003c/em\u003e.adj \u0026lt; 0.05) increases (orange) or decreases (green) in 20 hours of exposure to oil-PP NPs.\u0026nbsp;(c) Venn diagram depicting up-regulated KEGG pathways (|ReporterScore| \u0026gt; 1.64,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e.adj \u0026lt; 0.05) after 4 hours and 20 hours exposure with oil- and water-PP NPs.\u0026nbsp;(d) Volcano plot of differentially expressed genes after 4 hours and 20 hours of exposure to water-PP NPs and oil-PP NPs with 100 μg/mL. BH-corrected\u0026nbsp;\u003cem\u003ep\u003c/em\u003e-adjusted \u0026lt;0.05 and |log\u003csub\u003e2\u003c/sub\u003e(FC)| ≥ 1. Genes with the top 5 |log\u003csub\u003e2\u003c/sub\u003e(FC)| values, either up-regulated or down-regulated, are labeled. (e) Bubble plot related to up-regulated KEGG pathways between oil-PP NPs vs. control and water-PP NPs vs. control with 50 μg/mL, 4 hours treated groups (ReporterScore \u0026gt; 2.5,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05).\u0026nbsp;(f) Bubble plot related to up-regulated KEGG pathways between oil-PP NPs vs. control and water-PP NPs vs. control with 10 μg/mL, 20 hours treated groups (ReporterScore \u0026gt; 2.5,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6015466/v1/04ce963894c3d79a0a7a710e.png"},{"id":79656576,"identity":"e356a567-de14-4720-a5a9-ca3c2789a81d","added_by":"auto","created_at":"2025-04-01 08:58:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":898102,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eWorldwide MNP exposure from oil-filled plastic containers, associated heavy metal intake, and benchmark dose analysis. \u003c/strong\u003e(a) Annual MNP intake (g/person/year) from PP and PE-coated containers, as determined by different food ordering frequencies. (b) Annual heavy metal intake (g/person/year) from PP and PE-coated containers by different adult food ordering frequency. (c) Global MNP exposure (g/person/year) from PP containers across 23 regions. (d) Lollipop chart showing benchmark dose lower limits (BMDLs) based on cell viability data for oil-PP NPs, oil-PP MPs, water-PP NPs, and water-PP MPs-treated groups, as well as dose-dependent biomarkers identified in (Figure S10d, e).\u003cstrong\u003e \u003c/strong\u003e(e) Comparison of MNP concentrations in human biological samples with toxicological thresholds, assuming all MNPs are NPs. The \u003cem\u003ep\u003c/em\u003e-values for statistical differences were assessed using the Student’s t-tests, Kruskal-Wallis test, and Shapiro-Wilk test where applicable.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6015466/v1/4d6b3090e956831d40a39f1d.png"},{"id":79658882,"identity":"defdd01e-5774-4fe3-817b-2572ea1094ba","added_by":"auto","created_at":"2025-04-01 09:22:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6788954,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6015466/v1/e23f805d-b85e-48bf-a5fe-09ad53d417f3.pdf"},{"id":79656892,"identity":"776859e6-54ad-4c77-b5d7-e4bb6394f3bf","added_by":"auto","created_at":"2025-04-01 09:06:15","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":6263621,"visible":true,"origin":"","legend":"Dataset 1","description":"","filename":"SupplementaryInformationoilplasticpaperNN.docx","url":"https://assets-eu.researchsquare.com/files/rs-6015466/v1/17ce3adaec1b20486b72e122.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Oil-Encapsulated Nanoplastics from Plastic Disposable Food Containers Induce Rapid Cell Death through Cell Membrane Disruption","fulltext":[{"header":"Highlights","content":"\u003cp\u003e\u0026bull; Orders of magnitudes higher levels of micro(nano)plastics and harmful additives are released from plastic containers filled with cooking oil compared to those filled with water, especially after microwaving.\u003c/p\u003e\u003cp\u003e\u0026bull; Oil-derived nanoplastics can induce cell death by disrupting cellular membranes at concentrations of 100 \u0026micro;g/ml within 5 minutes.\u003c/p\u003e\u003cp\u003e\u0026bull; Oil-derived nanoplastics elicit more transcriptomic changes related to acute cellular stress and mitochondrial dysfunction compared to water-derived nanoplastics.\u003c/p\u003e\u003cp\u003e\u0026bull; Globally, the highest annual intake of MNPs from microwaving oil-rich takeout food is 3.35 g per person, observed among individuals in China.\u003c/p\u003e\u003cp\u003e\u0026bull; The toxicity assessment, integrating both cell viability and molecular biomarkers, establishes a safe exposure limit of 1.18 \u0026micro;g/mL for oil-derived nanoplastics, which is below the actual observed levels in human tissues.\u003c/p\u003e"},{"header":"1 Introduction","content":"\u003cp\u003eThe rapid expansion of the global food delivery industry has transformed modern dietary habits, with convenience driving an ever-increasing reliance on disposable plastic food containers\u003csup\u003e \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e \u003c/sup\u003e. In 2023, the global online food delivery market was valued at over \u003cspan\u003e$\u003c/span\u003e189.7\u0026nbsp;billion, with annual growth projected at 10% in the coming years\u003csup\u003e \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e \u003c/sup\u003e. This boom has led to the widespread use of plastic food-contact materials (PFCMs), such as takeaway containers, bags, and lids, which account for approximately 40% of global plastic production\u003csup\u003e \u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e \u003c/sup\u003e. Among these, polypropylene (PP) and polyethylene (PE) dominate due to their durability, lightweight nature, and thermal resistance. However, the frequent use of PFCMs under real-life scenarios, such as heating, storage, and transportation, raises concerns about the release of micro(nano)plastics (MNPs) and chemical additives, particularly when interacting with certain types of food\u003csup\u003e \u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e \u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCooking oils, unlike water-based foods, pose a unique challenge due to their physicochemical properties. Oils can solubilize non-polar compounds, potentially enhancing the release of MNPs and chemical additives from plastics\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Moreover, oil-rich foods are increasingly prevalent in the global diet, particularly in takeaway meals such as fried foods, curries, and sauces, making them a significant but understudied contributor to MNP exposure. Unlike water simulants widely used in MNP research, oils may interact differently with plastics, altering the surface properties of MNPs and amplifying MNP release and toxicity under conditions like heating or prolonged storage. However, studies on the release and toxicity of MNPs under oil-rich conditions are limited, creating a critical gap in understanding the health risks associated with these interactions.\u003c/p\u003e \u003cp\u003eMNPs, including microplastics (MPs) smaller than 5 mm and nanoplastics (NPs) smaller than 1000 nm\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, are detected in various food products, such as table salt\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, bottled water\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, and seafood\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. The ingestion of MNPs, particularly NPs, raises significant concerns about potential health risks pose a greater risk due to their ability to penetrate biological barriers, leading to heightened adverse effects\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, including metabolic disorders\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, DNA damage\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, inflammation\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, and cytotoxicity. Yet, most studies have focused on synthetic, fixed-size polystyrene (PS) particles in water, which do not capture the full complexity of MNP exposure in natural food environments. In reality, MNPs may interact with different types of food and environmental matrices, which may alter their toxicity.\u003c/p\u003e \u003cp\u003eHere, we address these questions by simulating three common takeout scenarios using cooking oil as a food simulant to investigate MNP release and toxicity from PP and PE-coated containers, with deionized water as a control. We demonstrate that cooking oil significantly increases MNP release\u0026mdash;up to 125-fold for PE and 29-fold for PP containers\u0026mdash;alongside a substantial increase in heavy metal (up to 471-fold) and harmful organic additive leaching. Zeta potential, indicating surface charge, influences nanoparticle stability and interactions with biological systems. Soybean oil-derived PP NPs exhibited a zeta potential of +\u0026thinsp;7.37 mV, compared to -8.21 mV for water-derived NPs, potentially resulting in significantly higher cytotoxicity, including rapid cell membrane damage within 5 minutes at 100 \u0026micro;g/mL. Transcriptomic analysis revealed that oil-derived PP NPs caused more extensive gene expression changes, highlighting their heightened toxicity compared to water-derived particles. Globally, our study estimates that Chinese consumers have the highest annual intake of MNPs from high-fat takeout food, reaching approximately 3.35 g per year. Integrating benchmark dose limit thresholds with MNP concentrations reveals the extensive potential for subclinical and pathological damage linked to humans. Our results reveal the significant health risks posed by oil-plastic interactions, emphasizing the need for enhanced safety regulations for food-contact materials in oil-rich food contexts.\u003c/p\u003e"},{"header":"2 Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Physicochemical Properties of Plastic Takeaway Containers and Their Released MNPs\u003c/h2\u003e \u003cp\u003eWe investigated the release of MNPs from two representative food packaging materials, polypropylene (PP) and polyethylene (PE) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). PP containers are commonly used for hot food storage and microwave applications due to their higher thermal stability. PE-coated containers are frequently used for food storage because of PE's flexibility and cost-effectiveness (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, c). Differential scanning calorimetry (DSC) measurements showed notable differences in thermal stability between the PP and PE materials: the PP exhibited a significant melting peak at 156.51\u0026deg;C, indicating higher thermal stability; conversely, the PE displayed two distinct melting peaks at 88.94\u0026deg;C and 105.07\u0026deg;C, indicating substantially lower melting temperatures (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003eX-ray diffraction (XRD) analysis confirmed the crystalline structures of both PP and PE, revealing distinct crystalline peaks. PP container showed pronounced peaks characteristic of the α crystalline phase of isotactic polypropylene. In contrast, the PE-coated container exhibited primary crystalline peaks, corresponding to the orthorhombic crystal phase of PE (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee)\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. These results again indicate that PE-coated containers have lower crystallinity and melting temperatures than PP containers.\u003c/p\u003e \u003cp\u003eSubsequently, we characterized the morphology of MNPs released from two types of food containers filled with food simulants\u0026mdash;deionized (DI) water and soybean oil\u0026mdash;after microwave heating for 3 minutes. The plastic particles released into oil from both PP and PE-coated containers showed a diversity of particle sizes and shapes (Figure S1a, b). Transmission electron microscopy (TEM) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef) and scanning electron microscopy (SEM) (Figure S1c) were subsequently utilized for the detailed characterization of MPs and NPs. Notably, oil-derived NPs released from PP containers (PP NPs) and PE-coated containers (PE NPs) appeared to be encapsulated in an oil film.\u003c/p\u003e \u003cp\u003eZeta potential reflects the surface charge of plastic particles, influencing their stability, aggregation, and interactions with other substances. For simplicity, MNPs released from PP containers filled with soybean oil are termed oil-PP MNPs, while those released from PP containers filled with water are termed water-PP MNPs. Similarly, MNPs from PE-coated containers are designated as oil-PE and water-PE MNPs. After 3 minutes of microwave heating, significant differences in zeta potential were observed among the MNPs (\u003cem\u003ep\u003c/em\u003e-group\u0026thinsp;=\u0026thinsp;0.025; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg). Water-PP MNPs had a much lower zeta potential (-50.3 mV) than oil-PP MNPs (-0.03 mV), indicating higher surface charge and potential instability in oil. In contrast, oil- and water-PE MNPs had similar zeta potential.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Oil-Filled Plastic Containers Sustained More Damage Across All Testing Scenarios\u003c/h2\u003e \u003cp\u003eScanning Electron Microscopy (SEM) was employed to examine the effects of different treatments on the food-contact surfaces of PP and PE-coated containers (Figure S2). The experimental groups simulated three common scenarios for plastic food containers: microwave heating (A-C), transportation (D-F), and leftover storage (G-H). To test the impact of oil-rich food, we chose soybean oil as the main food simulant because it is widely used in daily life, with DI water as the control.\u003c/p\u003e \u003cp\u003eFor the PP container, the control group had a smooth, undamaged surface. Microwave heating of the water-filled container left the surface mostly unscathed. However, microwave heating the oil-filled container caused significant degradation and MNPs release, starting as short as 1 minute (A) and increasingly evident after 3 (B) and 5 (C) minutes (Figure S2a, A-C). In the transportation simulation, water treatment left surfaces intact, while oil treatment led to noticeable particle release after 60 minutes (Figure S2a, D-F). In the leftover simulation, water treatment also had minimal impacts (Figure S2a, G, and H), but oil treatment caused substantial surface damages after 5 hours, even without any shaking or movements.\u003c/p\u003e \u003cp\u003eSimilarly, the water treatment left the PE coating mostly intact, but oil-filled containers showed substantial damage in all scenarios (Figure S2b). Overall, oil significantly impacts both PP and PE-coated containers in all scenarios, while water has minimal effects.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Microwave Heating of Oil-Filled Plastic Containers Significantly Increases MNP Release and Reduces Particle Size\u003c/h2\u003e \u003cp\u003eTo assess the effects of oil treatments, we analyzed the chemical composition of MNPs released from containers using Raman and ATR-FTIR spectroscopy. Raman analysis confirmed the identity of the released MNPs as PP and PE based on characteristic peaks consistent with reference spectra for these materials (Figure S1d). Notably, ATR-FTIR revealed an additional peak at 1745 cm⁻\u0026sup1; in both PP and PE MNPs released in oil, indicating potential chemical modifications induced by microwave heating in the presence of oil (Figure S1e) \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eQuantifying the release and particle size distribution of MNPs is crucial for evaluating their potential environmental and health impacts. For simplicity, we denoted the MPs and NPs released from PP containers filled with oil and water as oil-PP MPs, oil-PP NPs, water-PP MPs, and water-PP NPs, respectively. Similarly, particles from PE-coated containers filled with oil and water were referred to as oil-PE MPs, oil-PE NPs, water-PE MPs, and water-PE NPs, respectively. MPs were quantified using a BioTek Cytation 3 plate reader, capable of detecting particles as small as 6 \u0026micro;m, with blank controls for accuracy\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e (Figures S1f, g). Nanoparticle Tracking Analysis (NTA) with a NanoSight NS500 equipped with a 532 nm green laser provided quantity and size data for NPs ranging from 10 nm to 1 \u0026micro;m.\u003c/p\u003e \u003cp\u003eIn the microwaving group, oil-treated samples as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee, PP containers released significantly higher concentrations of smaller oil-PP MNPs compared to water-PP MNPs. After 5 minutes of heating, oil-PP MPs were released at 2.7 \u0026times; 10\u003csup\u003e7\u003c/sup\u003e particles/L, which were 21 times higher than water-PP MPs (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with most oil-PP MPs smaller than 50 \u0026micro;m (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). After heating for 3 minutes, oil-PP NPs were released at 7.2 \u0026times; 10\u003csup\u003e12\u003c/sup\u003e particles/L, which were 18 times higher than water-PP NPs (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and their average size was smaller than that of water-PP NPs (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, c).\u003c/p\u003e \u003cp\u003eSimilarly, PE-coated containers released significantly higher concentrations of smaller oil-PE MNPs compared to water-PE MNPs. After 5 minutes of heating, oil-PE MPs were released at 2.4 \u0026times; 10\u003csup\u003e7\u003c/sup\u003e particles/L, which were 62 times higher than water-PE MPs (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with both the average and median sizes of oil-PE MPs significantly smaller (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Oil-PE NPs were released at 1.25 \u0026times; 10\u003csup\u003e13\u003c/sup\u003e particles/L, which were 125 times higher than water-PE NPs (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and the median size of oil-PE NPs was consistently smaller across all heating durations (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, d).\u003c/p\u003e \u003cp\u003eUnder simulated transportation and leftover scenarios (Groups D-H), PP NPs were consistently released at higher concentrations in oil (9.3 \u0026times; 10\u003csup\u003e11\u003c/sup\u003e to 2.1 \u0026times; 10\u003csup\u003e12\u003c/sup\u003e particles/L) than in water (3.4 \u0026times; 10\u003csup\u003e11\u003c/sup\u003e to 6.8 \u0026times; 10\u003csup\u003e11\u003c/sup\u003e particles/L), with concentrations increasing over time. Most PP MPs were smaller than 10 \u0026micro;m, and the majority of PP NPs were below 220 nm (Figures S3a, c). For PE-coated containers, MPs and NPs were consistently more abundant in oil than in water, with longer exposure times leading to higher releases of PE NPs (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01). Oil-PE NPs were generally smaller than water-PE NPs (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01; Figures S3b, d). Overall, under microwaving conditions, MNP release was at highest in concentration and smallest in particle size, followed by simulated transportation and leftover food scenarios, with significant differences confirmed by one-way ANOVA and post-hoc Tukey tests (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003ePrevious studies on MNP quantification from plastic products mainly relied on particle counting or membrane filtration for weighing, which lacked precision\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Using Py-GC/MS, we quantified MNP mass released from 100 mL of oil or water in plastic containers microwaved for 3 minutes, a common heating duration (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). MNP release varied significantly by container material and simulant type (\u003cem\u003ep\u003c/em\u003e-group\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with oil-PE MNPs showing the highest release (162.63 mg per container) and water-PP MNPs the lowest (1.14 mg per container). Based on soybean oil density (0.917 g/mL), released-MNP concentrations were 0.43, 0.01, 1.68, and 0.015 g/g for oil-PP, water-PP, oil-PE, and water-PE, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef). These findings validated particle counting results.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Enhanced Release of Harmful Additives from Oil-Filled Plastic Containers\u003c/h2\u003e \u003cp\u003eMNP-associated toxic additives, including pollutants and heavy metals, pose a significant concern when released from plastic food containers\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. LC-MS/MS analysis identified 3,126 chemical features (confidence score\u0026thinsp;\u0026ge;\u0026thinsp;60) in PP, PE, oil-PP, and oil-PE MNPs derived from oil-filled plastic containers after 3 minutes of microwave heating. There are 296 unique features in PP, 963 in oil-PP MNPs, 1,682 in PE, and 2,552 in oil-PE MNPs. 27.8% of features were shared between PP and oil-PP MNPs, and 45.6% were shared between PE and oil-PE MNPs (Figure S4a-c). Among the top 10 most abundant chemicals per sample, 33 were identified, including typical hazardous substances such as DEHP, avobenzone, and isoxadifen-ethyl, commonly used as plasticizers and stabilizers (Tables S2, S3; Figure S4d). Notably, oil-PP MNPs exhibited 143 upregulated chemicals compared to PP, while oil-PE MNPs showed 48 downregulated chemicals compared to PE, highlighting the prominent chemical changes induced by microwave heating in the presence of oil (Figure S4e, f).\u003c/p\u003e \u003cp\u003eInorganic metal additives such as Zn, Pb, Ni, Mn, Cu, Cr, and Cd are commonly added when manufacturing plastics, posing significant toxicity risks to humans\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. ICP-MS analysis showed minimal release of heavy metals into water but substantially higher levels in oil (Figure S4g). For example, oil-filled PP containers released Zn at 205.9 \u0026micro;g/kg (79-fold increase), Cu at 46.2 \u0026micro;g/kg (380-fold increase), and Pb at 23.52 \u0026micro;g/kg (147-fold increase). Similarly, oil-filled PE-coated containers released Zn at 225.1 \u0026micro;g/kg (113-fold increase), Cu at 89.6 \u0026micro;g/kg (471-fold increase), and Pb at 22.3 \u0026micro;g/kg (159-fold increase). These results underscored the crucial role of cooking oil in accelerating the leaching of chemical additives and heavy metals from plastics.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Various Types of Cooking Oils Consistently Exacerbate MNP Release Following Microwave Heating\u003c/h2\u003e \u003cp\u003eDifferent types of cooking oils are generally used, and PP containers are the most common microwave-safe plastic containers. To generalize the soybean oil-induced hyper-release of MNPs, we examined microwave heating of PP containers with four additional types of cooking oils (blended, palm, peanut, sunflower) for 3 minutes, finding significantly higher MNP release compared to water (\u003cem\u003ep\u003c/em\u003e-group\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Interestingly, soybean oil induced the highest release of PP MPs (3.26 \u0026times; 10\u003csup\u003e7\u003c/sup\u003e particles/L) and PP NPs (7.87 \u0026times; 10\u003csup\u003e12\u003c/sup\u003e particles/L), with the smallest average sizes for MPs (9.41 \u0026micro;m) and NPs (133.13 nm). Compared to other oils, soybean oil's higher unsaturated fatty acid content may promote oxidation during heating, accelerating PP degradation and increasing MNP release\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. In contrast, peanut oil showed the lowest release (5.79 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e particles/L for PP MPs and 1.39 \u0026times; 10\u003csup\u003e12\u003c/sup\u003e particles/L for PP NPs). Most oil-PP MPs were smaller than 10 \u0026micro;m, and oil-PP NPs were below 500 nm, with average sizes consistently smaller than water-PP MNPs (Figure S5a, b).\u003c/p\u003e \u003cp\u003eNPs pose greater risks to human health compared to MPs\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. For \u003cem\u003ein vitro\u003c/em\u003e cytotoxicity assessments, we collected PP NPs smaller than 220 nm (Methods). As mentioned previously, TEM analysis revealed an oil film on oil-PP NPs, and zeta potential measurements showed that soybean oil-PP NPs exhibited a positive charge (+\u0026thinsp;7.37 mV), unlike the negative charge of other types of oil-PP NPs (Figure S5c, d). The polydispersity indices (PDIs) of water- and oil-PP NPs ranged from 0.47 to 0.79, indicating a moderate to high polydispersity of size distribution. Water-PP NPs had the smallest average size (132.7 nm) after filtration, suggesting that, despite being individually smaller (Figure S5e,f), the oil film may promote aggregations of oil-PP NPs when not purified\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Exposure to Oil-PP NPs Induces Rapid Cell Death in Human Cell Lines\u003c/h2\u003e \u003cp\u003eWe focused on the cytotoxicity of soybean oil-PP NPs due to their positive zeta potential and widespread use. Fluorescence-labeled oil-PP NPs (FL-oil-PP NPs) exhibited red fluorescence due to iDye Poly pink, a dye that stains polymers (Figure S5g). To characterize the size distribution of FL-oil-PP NPs and oil-PP NPs in various media, we combined NTA and DLS results (Figure S5h-k). Oil-PP NPs in 0.1% SDS exhibited the smallest mean size (176.6 nm, with 75% of particles below 220 nm). PDI values range from 0.61 to 0.72 across all media, suggesting moderate polydispersity. These results indicate that the particle size distribution of oil-PP NPs is not significantly altered in different media, particularly in DMEM commonly used for cell culture.\u003c/p\u003e \u003cp\u003eNext, cytotoxicity assays were performed using the HEK293T cell line to assess the biological impact of PP MNPs. This kidney-derived cell line was selected for its relevance to renal filtration and excretion processes, which are essential for clearing dietary MNP exposure. To ensure that the observed cytotoxic effects were primarily due to the nanoparticles themselves rather than excess oil, we quantified the oil film volume surrounding PP NPs (Methods; Table S4). Based on these measurements, the estimated total oil film volume in the 200 \u0026micro;L suspension of oil-PP NPs at a concentration of 100 \u0026micro;g/mL used for cytotoxicity assays was 0.271 \u0026micro;L. This volume only accounts for 0.136% of the total suspension volume, suggesting that the observed cytotoxicity in the oil-PP NP group was unlikely to be caused by oil. After 24 hours of exposure, oil-PP NPs exhibited the highest toxicity, with significantly lower cell viability compared to oil-PP MPs, water-PP NPs, and water-PP MPs (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The IC50 values for oil-PP NPs, oil-PP MPs, water-PP NPs, and water-PP MPs were 18.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9, 122.3\u0026thinsp;\u0026plusmn;\u0026thinsp;53.64, 77.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5, and 497.8\u0026thinsp;\u0026plusmn;\u0026thinsp;78.1 \u0026micro;g/mL, respectively, confirming the greater toxicity of oil-derived particles, particularly NPs (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003eThe LDH assay was conducted to assess cell toxicity within 24 hours, as LDH release serves as a direct marker of acute membrane damage, providing critical insights into the immediate cytotoxic effects of oil-PP NPs. Oil-PP NPs demonstrated dose- and time-dependent cytotoxicity in HEK293T cells, evidenced by elevated LDH activity. At a concentration of 100 \u0026micro;g/mL, LDH activity exceeded 60% within 120 minutes, indicating significant membrane damage (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while lower doses resulted in reduced toxicity (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In contrast, cells in the control group (0 \u0026micro;g/mL) maintained minimal LDH activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eThese findings were further supported by the cellular morphological analysis, which revealed distinct dose- and time-dependent changes in cellular structure. At 20 \u0026micro;g/mL, cellular morphology showed minor alterations after 180 minutes. At 50 \u0026micro;g/mL, membrane deformation was observed after 60 minutes, intensifying over time. Higher concentrations (75 and 100 \u0026micro;g/mL) caused rapid and severe membrane disruption, with the structural integrity severely compromised within 20\u0026ndash;60 minutes at 100 \u0026micro;g/mL, leading to extensive cell detachment and death (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eTo simulate real-life consumption scenarios of ordering takeaway food multiple times in a day, multi-exposure experiments with oil-PP NPs (25 \u0026micro;g/mL added at 60-minute intervals) showed a significant increase in cell death and LDH activity after the second exposure (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating potential cumulative toxicity from repeated low-dose exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed, e).\u003c/p\u003e \u003cp\u003eCytotoxicity was further evaluated using HT29 and Caco-2 cell lines, which are relevant models for gastrointestinal exposure, using oil-PP NPs from various cooking oils. At 50 \u0026micro;g/mL and 100 \u0026micro;g/mL concentrations, all oil-PP NPs significantly increased LDH activity compared to water-PP NPs in HEK293T cells (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and at 100 \u0026micro;g/mL in the other two cell lines (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef-h). Among the tested particles, soybean oil-PP NPs exhibited the highest toxicity (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001), likely due to their positive zeta potential, which may enhance cellular uptake.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo explore the mechanisms underlying the observed cytotoxicity, laser confocal microscopy revealed that at 100 \u0026micro;g/mL, FL-oil-PP NPs (red) adhered to the cell membrane within 1 minute and extensively accumulated by 30\u0026ndash;60 minutes, leading to cell swelling and membrane rupture, while nuclear (blue) structures remained intact (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). These results indicate that oil-PP NPs may induce rapid cell death characterized by fast cellular uptake and membrane disruption processes.\u003c/p\u003e \u003cp\u003eTo further illustrate the differences in cellular uptake capacity between water-PP and oil-PP NPs, we generated time-dependent relative fluorescence intensity (RFI) curves. Oil-PP NPs exhibit significantly faster cellular uptake, with RFI sharply increasing and reaching saturation within approximately 60 seconds. In contrast, water-PP NPs show a slower uptake, with RFI beginning to increase notably after 100 seconds and gradually reaching saturation at around 1200 seconds. The rapid uptake of oil-PP NPs is likely due to their favorable interactions with the cell membrane and their efficient utilization of endocytic pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eTEM analysis revealed distinct effects of oil-PP and water-PP NPs on cellular morphology. In the control group, cells maintained their structural integrity with clearly defined membranes and normal cytoplasmic features. Similarly, no cellular damages were observed with water-PP NPs treatment. In contrast, cells exposed to oil-PP NPs exhibited severe plasma membrane damage, characterized by membrane rupture, swelling, and the formation of intracellular vesicles, which became evident within 5 minutes of treatment. Despite the pronounced membrane damage, the nuclear structure remained intact, indicating that oil-PP NPs predominantly targeted the cell membrane and cytoplasmic components without compromising nuclear integrity initially (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eThese findings demonstrate that oil-PP NPs can rapidly bind to cell membranes and induce cytotoxicity within 5 minutes, highlighting the potential health risks associated with ingesting oil-PP NPs from oil-rich foods stored or heated in plastic containers (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Oil-PP NPs and Water-PP NPs Exposure Induce Differential Dose-Responsive Transcriptomic Responses\u003c/h2\u003e \u003cp\u003eTo investigate cellular responses to oil-PP NP exposure, RNA sequencing revealed distinct dose-dependent transcriptomic changes compared to water-PP NPs. Experimental conditions were designed to simulate the acute toxic effects of plastic particles within a single day, reflecting realistic daily exposure scenarios (Methods).\u003c/p\u003e \u003cp\u003eAt high concentrations (50 and 100 \u0026micro;g/mL for 4 hours), oil-PP NPs activated inflammatory pathways (e.g., MAPK, TNF, IL-17) and suppressed metabolic processes (e.g., the citrate cycle, cell cycle, and aminoacyl-tRNA biosynthesis), indicating acute mitochondrial dysfunction and disrupted cellular homeostasis. Upregulation of the arachidonic acid metabolic pathway suggests cell membrane disruption driven by lipid peroxidation\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea; Figure S7a), highlighting the acute cytotoxic potential of oil-PP NPs. In contrast, prolonged low-concentration exposure (10 and 25 \u0026micro;g/mL for 20 hours) resulted in upregulation of glycine, serine, and threonine metabolism, with continued suppression of oxidative phosphorylation and ribosomal activity, reflecting persistent mitochondrial stress and metabolic adaptation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb; Figure S7b).\u003c/p\u003e \u003cp\u003eWater-PP NPs showed distinct dose-dependent transcriptomic profiles compared to oil-PP NPs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec; Figure S6c), activated stress pathways such as autophagy, apoptosis, and PI3K-Akt signaling at high concentrations, while prolonged exposure at low concentrations upregulated inflammatory pathways (e.g., NF-κB, complement cascades) and suppressed oxidative phosphorylation and ribosome biogenesis, indicating immune activation and metabolic suppression (Figure S6a, b; Figure S8a, b).\u003c/p\u003e \u003cp\u003eHowever, oil-PP NPs elicited significantly stronger transcriptomic changes, with upregulation of 509 genes and downregulation of 206 genes at 50 \u0026micro;g/mL (4 hours), disrupting key pathways such as the lysosome function and mitophagy, leading to acute metabolic disruption and mitochondrial dysfunction. Water-PP NPs, on the other hand, mainly activated inflammation-related pathways (e.g., MAPK, PI3K-Akt signaling) under similar conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed, e; Figure S9a).\u003c/p\u003e \u003cp\u003eAt 10 \u0026micro;g/mL for 20 hours, both oil- and water-PP NPs induced sustained inflammatory responses (e.g., NF-κB, Notch) and suppressed oxidative phosphorylation and ribosome, resulting in inflammatory and metabolic stress (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ef; Figure S9b), suggesting potential cumulative damage under chronic exposure. These findings suggest that oil-PP NPs primarily cause acute metabolic disruption at high concentrations, while both oil- and water-PP NPs lead to chronic inflammatory damage and metabolic stress under prolonged low-concentration exposure, underscoring overlapping but distinct mechanisms of toxicity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e2.8 Human Exposure to MNPs and Heavy Metals Through Takeout Food: Intake Analysis, Geographic Distribution, and Benchmark Dose Modeling\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo connect the observed toxicity in cell lines to human health, we next sought to assess the annual MNP and harmful heavy metal (Cd, Cr, Ni, Pb) intake at the individual level and globally due to takeout food. We categorize ordering frequency as once a day, once a week, or once a month. Assuming each meal uses one PP or PE-coated container, and considering the worst-case scenario of microwaving with oil for 3 minutes, the annual PE MNP intake ranges from 0.58\u0026ndash;22.36 g for adults and 0.27\u0026ndash;10.75 g for kids, while the PP MNP intake ranges from 0.17\u0026ndash;5.28 g for adults and 0.08\u0026ndash;2.53 g for kids (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea; Methods). Heavy metal intake also varies, with adults consuming 0.00015 (Cd)\u0026ndash;0.62 g (Cr) per year from PP containers (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01) and 0.00033 (Cd)\u0026ndash;0.32 g (Ni) per year from PE containers (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). Kids have proportionally lower intakes (Figure S10a). Given the global prevalence of take-out food, we selected widely used microwave-safe PP containers to estimate MNP exposure from takeout food across 23 regions (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.027 across different regions; Table S5). The annual average PP MNP intake per adult was 1.37 g per region, ranging from 0.43 g in the United Kingdom to 3.35 g in China (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec; Figure S10b). Interestingly, among these regions, the mean and median annual per capita MNP intake in developed countries (e.g., the United States of America, Canada, France) are lower than those in developing countries (e.g., China, South Africa, Mexico) (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001; Figure S10c).\u003c/p\u003e \u003cp\u003eGiven these findings, it is essential to integrate this intake data with toxicological assessments to better understand the health risks associated with chronic exposure to MNPs. We conducted benchmark doses (BMDs)\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e analysis, a preferred method by the USEPA and EFSA for identifying doses that trigger specific adverse effects. We integrated data on altered cellular viability for oil- and water-PP MPs and NPs alongside transcriptomic data from cells exposed to 0, 10, 25, and 50 \u0026micro;g/mL of oil-PP NPs and water-PP NPs under prolonged exposure (20 hours). This analysis yielded BMD and BMDL values for 214 genes responsive to 20-hour oil-PP NP exposure and 597 genes associated with water-PP NP exposure. Most of these dose-responsive genes are implicated in oxidative stress, apoptosis, autophagy, and immune responses (Figure S10d,e). Our findings indicated that the safety limits for cell viability after 24-hour exposure of 4.83 \u0026micro;g/mL (oil-PP NPs), 25.86 \u0026micro;g/mL (oil-PP MPs), 27.01 \u0026micro;g/mL (water-PP NPs), and 111.8 \u0026micro;g/mL (water-PP MPs) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed). Notably, several highly altered genes linked to cellular stress responses, inflammation, and immune activation exhibited significant dose-dependent changes following oil-PP NP exposure (Figure S10d). The lowest BMDL for oil-PP NPs was 1.18 \u0026micro;g/mL for \u003cem\u003eRIPK2\u003c/em\u003e, a key regulator of innate immunity and inflammation\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed). In contrast, for water-PP NPs, the lowest BMDL was 7.94 \u0026micro;g/mL for \u003cem\u003eFAS\u003c/em\u003e, which encodes a receptor critical for apoptosis and immune homeostasis\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed; Figure S10e). These results highlight that oil-PP NPs affect immune and stress pathways\u0026mdash;and potentially trigger inflammation and cell death\u0026mdash;at much lower concentrations than water-PP NPs, underscoring the value of incorporating molecular-level endpoints in BMD assessments.\u003c/p\u003e \u003cp\u003eTo find out if these BMDLs (including MPs and NPs) are physiologically relevant, we systematically compiled absolute quantification data of MNP concentrations across 15 distinct human biological samples, including blood, liver, brain, placenta, and BALF, extracted from individual experimental studies (Table S7). Assuming that an exposure level of \u0026ldquo;\u0026micro;g/mL\u0026rdquo; in the medium corresponds to \u0026ldquo;\u0026micro;g/g\u0026rdquo; in tissues and considering all MNP exposure as cumulative, there is a realistic potential for subclinical and pathological damage associated with MNP exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee). Notably, even in the blood, which exhibited the lowest observed MNP concentration (1.6 \u0026micro;g/mL), levels exceeded the lowest gene-based BMDL for oil-PP NPs (1.18 \u0026micro;g/mL). Placenta samples from healthy individuals showed an alarming MNP concentration of 126.8 \u0026micro;g/g, consistent with our previous study\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, surpassing all BMDL thresholds, raising concerns about risks to both maternal and fetal health. Similarly, the brain, kidney, and liver showed significant MNP accumulation up to 4763 \u0026micro;g/g, with detected MNPs primarily composed of PE and PP\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. The increasing MNP burden over time and its higher levels in dementia patients reinforce concerns about neurological and hepatic risks, supporting the need for further investigation into exposure pathways and health impacts. In pathological tissues, such as cumulus granulosa cells (313.1 \u0026micro;g/g), thrombi (105.5 \u0026micro;g/g), atherosclerotic plaques (118.66 \u0026micro;g/g), and bone marrow (51.3 \u0026micro;g/g), MNP concentrations consistently approached or exceeded BMDL values, suggesting that higher MNPs exposure is associated with pathological conditions. For example, in thrombi and atherosclerotic plaques, MNP-induced inflammation and oxidative stress could accelerate vascular damage and increase the risk of adverse cardiovascular events\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3 Discussion","content":"\u003cp\u003eThis study represents a major advancement in understanding the health risks associated with MNPs from PFCMs under oil-rich conditions. By revealing how common practices, such as reheating oily foods in plastic containers, can significantly increase MNP release and toxicity, we address critical gaps in the current understanding of exposure pathways. Our findings highlight the amplifying effect of oil on both MNP release and toxicity while introducing a precise methodological framework for quantifying exposure.\u003c/p\u003e \u003cp\u003eA core finding of this study is the significant role of cooking oils in enhancing MNP release from plastic containers, with oil increasing MNP release by up to 125-fold for PE-coated containers and 29-fold for PP containers (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, b), reaching 130.93 mg per container after 3 minutes of microwave heating (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef). These levels far exceed those observed in water-based simulants, exposing a major limitation in current regulatory testing protocols. Furthermore, oil-exposed MNPs displayed smaller sizes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, d) and positive zeta potentials (+\u0026thinsp;7.37 mV; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg), enhancing bioavailability, cellular uptake, and toxicity. With oily foods being a global dietary staple, this overlooked exposure pathway demands urgent attention.\u003c/p\u003e \u003cp\u003eOur findings demonstrate that oil-derived MNPs are not only released in greater quantities but are significantly more toxic than water-derived counterparts. High concentrations of oil-PP NPs triggered acute inflammatory responses, mitochondrial dysfunction, and membrane disruption, leading to rapid cellular stress and loss of homeostasis, as confirmed by cell viability and LDH assays. At lower concentrations, oil-PP NPs induced sustained inflammatory and metabolic dysregulation, including suppression of oxidative phosphorylation and ribosome biogenesis. These effects suggest a dual toxicity profile: acute effects at high concentrations and chronic stress at low concentrations, with potential implications for the development of metabolic disorders, neurodegeneration, and cancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea, b). The heightened toxicity of oil-PP NPs compared to water-PP NPs and other nanoplastics, such as polystyrene, highlights the need to extend nanoplastic toxicity research beyond traditional water-based exposure models to account for real-world food matrices like oil, which may amplify both release and toxicological impacts\u003csup\u003e\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur global exposure estimates, derived from Py-GC/MS-based release data, further underscore the scale of this issue. The annual intake of oil-derived MNPs is highest in countries like China, where exposure levels can reach up to 3.35 g/year due to dietary habits and high rates of takeout food consumption (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec). These findings reveal a hidden yet pervasive public health threat, particularly in regions with diets in oil-rich, reheated, or fried foods. The current regulatory emphasis on water-based simulants is clearly insufficient to capture the true risks of plastic food-contact materials\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Our findings call for an urgent overhaul of testing protocols to incorporate oil-based simulants and account for the combined effects of MNPs and chemical additives in oil-rich environments. Additionally, our results underscore the importance of consumer education campaigns to reduce reliance on plastic containers for oil-rich foods.\u003c/p\u003e \u003cp\u003eBy using Py-GC/MS for absolute quantification of plastic exposure, we have established a robust framework that links exposure levels to toxicological outcomes through BMD analysis, setting an important example for MNP research. The lowest BMDL identified for oil-PP NPs was 1.18 \u0026micro;g/mL. The inclusion of MP-specific BMDL values ensures a balanced risk assessment, preventing overestimation that might occur if relying solely on NP data. Importantly, our study accounts for both water-based and oil-based particles, reflecting the distinct toxicological profiles and exposure scenarios of these MNPs. By incorporating both MP- and NP-specific BMDLs for oil- and water-based plastics, we establish a more comprehensive and nuanced framework for evaluating toxicity across different particle sizes and environmental contexts.\u003c/p\u003e \u003cp\u003eWe also compared these BMDL values with real-world MNP concentrations in human biological samples collected from 15 different tissues and fluids, including blood, brain, placenta, and gallstones. Remarkably, the concentrations of MNPs found in these pathological samples and healthy placenta mostly exceeded BMDL thresholds, some even for cell viability, suggesting that many individuals may already be exposed to levels of MNPs capable of causing adverse biological effects (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee). This underscores the urgent need for more comprehensive exposure assessments and regulatory updates to address the amplified risks posed by oil-rich foods.\u003c/p\u003e \u003cp\u003eFuture studies should explore alternative packaging materials that exhibit lower MNP release and toxicity. Promising candidates, such as bioplastics, glass, or stainless steel containers, should be evaluated for their suitability as safer alternatives to conventional plastics\u003csup\u003e\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Moreover, to better understand the health impacts of chronic oil-derived MNP exposure, long-term \u003cem\u003ein vivo\u003c/em\u003e studies and epidemiological investigations are essential. These studies should assess both the intake levels and the accumulation of MNPs in the body over time while determining the toxicity thresholds associated with prolonged exposure to fully elucidate the health risks.\u003c/p\u003e"},{"header":"4 Conclusions","content":"\u003cp\u003eOur study highlights the critical role of cooking oil in promoting the release and cytotoxicity of smaller MNPs from PP and PE-coated takeaway containers, particularly after microwave heating. These findings reveal significant cellular health risks at physiologically relevant levels. Given the widespread use of cooking oils in global diets and the growth of the takeout industry, these findings raise major concerns about chronic dietary exposure to oil-derived MNPs and associated contaminants. Our results advocate for stricter regulations on plastic food packaging for oil-rich foods and highlight the need for developing safer alternatives and conducting long-term health impact studies to protect public health and the environment.\u003c/p\u003e"},{"header":"5 Methods","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Characterizations of Plastic Containers\u003c/h2\u003e \u003cp\u003eTwo anonymous brands of plastic food containers made of PP and PE materials were purchased from online stores (sales exceeding 3\u0026nbsp;million units) and restaurants in Hangzhou, China. These two types of containers were selected due to their widespread use in food packaging and delivery services.\u003c/p\u003e \u003cp\u003eThe compositions of the plastic containers were determined by the Attenuated Total Reflectance Fourier Transform Infrared spectroscopy (ATR-FTIR, NICOLET iS50FT-IR, Thermo Scientific, USA). The obtained IR spectra were compared with the database on the OMNIC software, and a polymer type was considered acceptable when the match with standard spectra was greater than 70%. At least three different batches of the containers were purchased at different times of the year and analyzed in the study.\u003c/p\u003e \u003cp\u003eTheir semicrystalline structure and thermal stability were analyzed by differential scanning calorimetry (DSC) using a Q200 differential scanning calorimeter (TA Instruments, New Castle, DE, USA). Approximately 8 mg sample was taken from each container, placed in an aluminum pan, sealed, and subjected to a thermal cycle at 10\u0026deg;C/min under a nitrogen atmosphere. The resulting calorimetric curves, which reflect heat transfer during the thermal cycle, were used to monitor phase transitions.\u003c/p\u003e \u003cp\u003eX-ray diffraction (XRD) has been utilized to detect changes in crystalline and amorphous characteristics in plastic materials. To prepare the samples, we cut the PP containers and the inner plastic lining of the PE-coated containers into 0.5 \u0026times; 0.5 cm pieces. Specimens were kept in an aluminum sample holder so that the upper surface was smooth and exposed to X-rays in vertical goniometry assembly. The scan was taken between (10\u0026ndash;80\u0026deg;) 2θ with a scanning speed of 0.02-degree 2θ per min.; the operating target voltage was 35 kV, tube current was 20 mA, and radiation used was FeKα with a wavelength of 1.93735 \u0026Aring; on Rigaku Rotating anode mode RU-H3R (18Kw), X-ray powder diffractometer. The intensity versus 2θ scans were obtained for these plastic materials.\u003c/p\u003e \u003cp\u003eThe high-resolution field emission scanning electron microscope (SEM, Regulus 8230, Hitachi, Japan) was employed to reveal the surface morphologies of the inner walls of the plastic containers before and after treatments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Release Experiments of Micro- and Nano-Plastics\u003c/h2\u003e \u003cp\u003eIn total, three common real-life takeaway food scenarios using plastic containers were simulated: microwaving cold food (Group A-C), transportation (Group D-F), and leftover storage (Group G and H). To simulate different food types, food simulants were used: ultrapure deionized water (DI water; 18.2 MΩ\u0026middot;cm, Cascada\u0026trade; water purification system, Pall, USA) and commercial cooking oils of anonymous brands (soybean, palm, blend, peanut, and sunflower oil) purchased from brand stores in China. DI water and cooking oils were stored in glass beakers and analyzed separately. Before the experiments, the PP and PE-coated containers were thoroughly rinsed with DI water and air-dried three times to remove residual MNPs during the manufacturing processes.\u003c/p\u003e \u003cp\u003eFor all experiments, containers were filled with 100 mL of one type of oil or DI water (Figure S1a). To simulate microwaving, containers filled with food simulants at room temperature were placed in a microwave oven (M1-201A, Midea, China) at 800 W for 1, 3, and 5 minutes. Following the previous study\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, containers filled with food simulants were oscillated at 120 rpm on a horizontal rotary shaker (NMSP-600, NuoMi, China) for transportation simulation at room temperature for 15, 30, and 60 minutes. For leftover storage simulation, the containers were filled with oil or water, pre-heated to 95\u0026deg;C, and left at room temperature for 1 and 5 hours. We modified a previous study's procedure to concentrate the leachate and extract the plastic particles for subsequent analysis \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. For oil-treated samples, 100 ml of oil was mixed with 300 ml of hexane (1:3 ratio) and vortexed for 30 seconds to ensure complete dissolution. Using a vacuum pump, the mixture was filtered through a vacuum filtration system. To remove residual oil, 60 ml of prefiltered hexane was added to the Anodisc filters (0.22 \u0026micro;m pore diameter, 25 mm diameter, Waterman, Germany) three times. Water-treated samples were poured directly into the vacuum filtration system for extraction. The filter membranes from both oil- and water-treated samples were then placed in a glass dish with 10 ml of 30% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and incubated at 60\u0026deg;C for 1 hour to remove excess organics. The filters were subsequently sonicated for 1 hour to yield 10 ml concentrate leachate samples of MNPs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e5.3 Characterization of Micro- and Nano-Plastics\u003c/h2\u003e \u003cp\u003eOptical microscope (LV100N, NIKON, Japan), SEM, and Transmission Electron Microscopy (TEM, JEM-1400flash, JEOL Co., Ltd., Japan) were used to characterize the morphology of MPs and NPs.\u003c/p\u003e \u003cp\u003eRaman microspectroscopy was used to characterize MNPs. A 100 mL leachate sample from different experimental groups was filtered through a 0.22 \u0026micro;m glass fiber filter (Shanghai Dibo Biotechnology Co., Ltd., Shanghai, China). The type and chemical composition of the plastic materials were characterized by ATR-FTIR spectroscopy (NICOLET iS50FT-IR, Thermo Scientific Inc., Waltham, MA).\u003c/p\u003e \u003cp\u003eZeta potential analysis was conducted using a laser particle sizer (Zetasizer Nano ZSE, Malvern, UK). A 1 mL aliquot of MNP solution from each sample type was placed in the sample pool for measurement.\u003c/p\u003e \u003cp\u003eSoybean oil-treated samples were chosen for analysis, assuming similar properties in water-treated samples. The samples were analyzed with a Raman XploRA Nano Microspectrometer (Horiba Scientific, Kyoto, Japan), featuring a 785 nm laser and 600 lines per mm grating, covering a spectral range of 0 to 2200 cm⁻\u0026sup1;. Calibration was done using the silicon line at 520.7 cm⁻\u0026sup1;. Raw Raman spectra were processed with polynomial baseline correction and vector normalization using LabSpec 6 software. MNPs identification was based on matching spectra with the SLOPP Library of Microplastics and KnowItAll software (Bio-Rad Laboratories, Inc.), considering matches with a Hit Quality Index (HQI) score of 80 or above as reliable.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e5.4 Micro- and Nano-Plastics Detection and Quantification\u003c/h2\u003e \u003cp\u003eWe followed our previous protocol to assess the size and quantity of microplastics in the leachate\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. A 5 \u0026micro;L droplet of the 10 mL concentrated leachate was mixed with 195 \u0026micro;L of 0.01 mg/mL Nile Red (Aladdin, China) solution in a 96-well plate and incubated at 55\u0026deg;C for 30 minutes for staining. Each leachate sample was processed in triplicate to ensure statistical robustness, with three blank controls included per plate. Fluorescence was measured using a BioTek Cytation 3 plate reader (Bio Tek Instruments, Inc., USA) at 4x magnification, with the Montage function used to quantify MPs as small as 6 \u0026micro;m in diameter. Consistent acquisition and analysis parameters were applied to all wells.\u003c/p\u003e \u003cp\u003eThe leachate samples were analyzed for the number of nanoplastics present using a Nanoparticle Tracking Analysis (NTA, NanoSight NS500, Malvern Panalytical Ltd, UK) followed by a previous study\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, which is equipped with a 532 nm green laser to detect and count particles in 10 nm to 1 \u0026micro;m size range. In addition to the number, NTA also provided us with the size distribution of nanoplastic particles. Three leachate samples were analyzed for each release experiment.\u003c/p\u003e \u003cp\u003eWe selected Group B samples for Py-GC/MS analysis. The samples were filtered through a 25 mm GF/F glass fiber filter (220 nm mesh, Whatman, UK). To eliminate plastic contamination, the filters were preheated in a 500\u0026deg;C nitrogen-purged muffle oven before filtration. Plastic particles were retained on the filter. The residue was then rinsed with 10 mL of 30% H₂O₂ (Merck, Germany) and 15 mL of deionized (DI) water. The inner circle containing the analyte (Figure S2e) was cut from the filter using a stainless steel blade, dried at 45\u0026deg;C for 4 hours, and subsequently transferred to a pyrolysis cup. Analysis was performed using the multishot pyrolysis unit EGA/PY-3030D (Frontier Laboratories, Saikon, Japan) in \u0026ldquo;single shot\u0026rdquo; mode. The GC/MS system (Trace 1300 GC and ISQ 7000 MS, Thermo Fisher, Waltham, MA, USA) was equipped with a TG-5SILMS column (30 m \u0026times; 0.25 mm \u0026times; 0.25 \u0026micro;m, Thermo Scientific Inc., Waltham, MA, USA). Measurements were conducted in selected ion monitoring (SIM) mode with a 1:50 split ratio. The temperature program started at 40\u0026deg;C, held for 2 minutes, then increased at a rate of 20\u0026deg;C/min to 320\u0026deg;C and held at 320\u0026deg;C for 14 minutes.\u003c/p\u003e \u003cp\u003eDuring the analysis, an ion scan range of m/z 29\u0026ndash;600 was used to identify and quantify the polymers of the target plastic particles. Indicator ions for PP and PE, 2,4-dimethyl-1-heptene (m/z 126) and 1-docosane (m/z 83), were employed. Standards for target microplastics (PP and PE) were first analyzed, and standard curves for PP and PE quantification were constructed to determine the mass of MNPs in all samples (Figure S2e and Table S1). The NIST17 library spectrum was used for compound identification, and peak areas were calculated using the normalization method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e5.5 Heavy Metal Analysis\u003c/h2\u003e \u003cp\u003eThe triplicate samples collected from soybean oil-treated and DI water-treated containers, after 3 minutes of microwave heating, were analyzed for heavy metal content. Following established protocols\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, the samples were homogenized and digested using a microwave digestion system (Anton Paar, Graz, Austria) with a tri-acid mixture of nitric acid (HNO\u003csub\u003e3\u003c/sub\u003e), sulfuric acid (H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e), and perchloric acid (HClO\u003csub\u003e4\u003c/sub\u003e) in a 5:1:1 ratio. Post-digestion, the samples were filtered, diluted in ultrapure water, and analyzed using an Inductively Coupled Plasma Mass Spectrophotometer (ICP-MS) (Agilent Technologies 7800 ICP-MS, Santa Clara, CA, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e5.6 Analysis of Organic Additives in Plastic Materials\u003c/h2\u003e \u003cp\u003eWe followed the protocol of the previous study\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Methanol (99.8%, Sigma-Aldrich) was used to extract chemicals from plastic materials due to its ability to extract a wide range of compounds without dissolving the polymers. To prevent contamination, all consumables used in the extraction, except plastic pipet tips, were made of glass or stainless steel, rinsed with ultrapure water and acetone, and heated at 200\u0026deg;C for at least 2 hours. Each 1.5 g sample was cut into smaller pieces (0.5\u0026ndash;0.8 \u0026times; 2 cm, thickness\u0026thinsp;\u0026le;\u0026thinsp;0.4 cm) and extracted with 9 mL of methanol in glass vials with polytetrafluoroethylene-lined lids. Extraction was carried out by sonication for 1 hour at room temperature. Afterward, 1 mL of the extract was removed for chemical analysis and stored at \u0026minus;\u0026thinsp;20\u0026deg;C in glass vials. Four procedural blanks (PB 1\u0026ndash;4) containing only methanol underwent the same procedure as the samples to control for potential contamination.\u003c/p\u003e \u003cp\u003eAfterward, we applied nontargeted LC-MS/MS by an Acquity UPLC BEH C18 column (2.1 \u0026times; 100 mm i.d., 1.7 \u0026micro;m, Waters) coupled to a SCIEX X500B quadrupole time-of-flight (Q-TOF) mass spectrometer (AB SCIEX Pte. Ltd., USA) in positive ionization modes. The data acquisition was operated in full MS scan mode and information-dependent acquisition (IDA)-MS2 scan mode. During data acquisition, the quality control (QC) sample (generated by pooling all the samples) and blank samples (laboratory, transport, field, and extraction) were injected between every 10 sample injections.\u003c/p\u003e \u003cp\u003eThe mass spectrometry data were centroided and converted from the proprietary format (.raw) to the m/z extensible markup language format (.mzML) using ProteoWizard (MSConvert tool, ver. 3.0.21094). After comparing upstream processing parameters using IPO, Autotuner, and SLAW, SLAW was selected for parameters optimization, mass feature extraction, isotopic patterns extraction, peak grouping, and deisotoping. The resulting feature quantification tables (.CSV) and MS\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e consensus spectra (.MGF) were then exported for further analysis. All sample spectra were processed separately because their different chemical compositions prevented a joint retention time alignment. Features (ions with a unique m/z and retention time) with an abundance of less than 10-fold the highest across procedure blanks (PBs) and solvents were excluded from further analysis. Additionally, the abundance of the features was corrected by subtracting the maximum abundance of the respective features detected in the PBs.\u003c/p\u003e \u003cp\u003eFor data annotation, metabolite identification was performed using spectral entropy based on accurate mass (\u0026plusmn;\u0026thinsp;0.01 Da) and MS\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e similarity against public databases. Specifically, the MS\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e reference database was constructed by integrating open-source databases from the GNPS community (495,662 spectra as of 2022-06-18), the MoNA dataset (1,951,233 spectra as of 2023-02-07), and the NIST2020 Tandem Mass Spectral Library (1,143,815 spectra). All metabolites annotated through spectral matching were considered level 2 annotations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e5.7 \u003cem\u003eIn Vitro\u003c/em\u003e Cell Viability Study\u003c/h2\u003e \u003cp\u003eA 4-hour high-concentration exposure (50 and 100 \u0026micro;g/mL) modeled acute, high-dose intake events, such as ingestion of highly contaminated food or water during the typical postprandial digestion and absorption period when PP NPs interact with gastrointestinal cells and translocate into the systemic circulation. Conversely, a 20-hour low-concentration exposure (10 and 25 \u0026micro;g/mL) simulated cumulative retention from repeated dietary intake throughout the day, mimicking gradual nanoparticle buildup in tissues and digestive compartments.\u003c/p\u003e \u003cp\u003eTo assess the potential toxicity caused by the oil film, we first evaluated the volume of the oil film covering the surface of PP NPs. We analyzed at least five different TEM images of 250 oil-coated PP NPs using ImageJ software (National Institutes of Health, USA) to measure the average particle size of PP NPs both with and without the oil film. This assumption simplifies the estimation of the oil film volume by treating the nanoparticles as uniform, non-deformable spheres with a well-defined core and oil-coated outer layer. These measurements allowed us to estimate the oil film thickness and subsequently calculate the total oil volume in the suspension (Table S4). The oil film volume was calculated using the following equations:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{V}_{oil,\\:single\\:}=\\:\\frac{4}{3}\\pi\\:\\:\\left[{\\left(\\frac{{D}_{total}}{2}\\right)}^{3}-\\:{\\left(\\frac{{D}_{core}}{2}\\right)}^{3}\\right]\\:$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eHere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{V}_{oil,\\:single\\:}\\)\u003c/span\u003e\u003c/span\u003e represents the oil film volume per nanoparticle, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{D}_{total}\\)\u003c/span\u003e\u003c/span\u003e is the total diameter of the oil-coated PP NP (measured from TEM images, 150.95 nm), and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{D}_{core}\\)\u003c/span\u003e\u003c/span\u003e is the diameter of the PP NP core without the oil film (63.68 nm). By subtracting the core volume from the total volume, we obtained the volume of the oil layer surrounding each nanoparticle.\u003c/p\u003e \u003cp\u003eTo estimate the total oil film volume in the nanoparticle suspension, we used the nanoparticle mass concentration, the density of polypropylene and the single-particle oil film volume:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:{V}_{oil,\\:\\:total}=\\frac{{C}_{mass}}{\\frac{4}{3}\\pi\\:{\\left(\\frac{{D}_{core}}{2}\\right)}^{3}\\times\\:\\:{\\rho\\:}_{PP}}\\times\\:\\:{V}_{oil,\\:single}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eHere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{V}_{oil,\\:\\:total}\\)\u003c/span\u003e\u003c/span\u003e is the total oil film volume in the solution, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{C}_{mass}\\)\u003c/span\u003e\u003c/span\u003e is the PP NP mass concentration (\u0026micro;g/mL), and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\rho\\:}_{PP}\\)\u003c/span\u003e\u003c/span\u003e is the density of polypropylene (~\u0026thinsp;0.91 g/cm\u0026sup3;). The denominator represents the estimated number of nanoparticles per \u0026micro;L of solution, calculated from the core volume and material density.\u003c/p\u003e \u003cp\u003eIt is important to note that this calculation assumes a uniform spherical shape for all PP NPs and a homogeneous oil film distribution. These estimations provide an approximation of oil exposure but do not account for potential aggregation of nanoparticles, variations in oil adsorption efficiency, or dynamic changes in oil film properties over time. The actual bioavailability and toxicity of the oil film may also be influenced by interactions with environmental and biological factors, including surfactant behavior, protein corona formation, and enzymatic degradation.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCell Culture, Cell Viability, and Cytotoxicity Assay\u003c/b\u003e \u003c/p\u003e \u003cp\u003eHuman embryonic kidney 293T (HEK293T) cells were cultured in RPMI 1640. Human colon adenocarcinoma (HT29) and Caucasian colon adenocarcinoma (Caco-2) cells were grown in DMEM with 10% fetal bovine serum and 1X penicillin/streptomycin. All cells were maintained in a 37 \u003csup\u003eo\u003c/sup\u003eC humidified incubator with 5% CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eMPs and NPs derived from PP food containers were selected for cytotoxicity assessments, given that these containers are among the most frequently utilized microwaveable plastic vessels in daily life.\u003c/p\u003e \u003cp\u003e20 g of PP plastic was weighed and placed into an autoclaved glass bottle containing 200 mL of DI water or cooking oil to simulate the microwave heating process accurately. The plastic samples were then subjected to microwave heating at 800 W for 3 minutes\u003c/p\u003e \u003cp\u003eWater-PP MPs and Oil-PP MPs: The MNP solution was filtered through a PTFE membrane (Jingteng, China, pore size 0.8 \u0026micro;m). The particles collected on the filter were rinsed into a glass dish with ethanol, vortexed for 30 seconds, and centrifuged at 15,000\u0026times;g at 4\u0026deg;C for 10 minutes. The purified water-PP MPs were then used for subsequent analyses.\u003c/p\u003e \u003cp\u003eWater-PP NPs: The MNP solution was filtered through a PTFE membrane (Jingteng, China, pore size 0.2 \u0026micro;m). The filtrate was collected and concentrated using an Anodisc filter membrane (pore size 20 nm). The NPs were transferred into a glass dish with ethanol, vortexed for 30 seconds, and centrifuged at 15,000\u0026times;g at 4\u0026deg;C for 10 minutes. The purified water-PP NPs were used for subsequent analyses.\u003c/p\u003e \u003cp\u003eOil-PP NPs: The MNP solution was filtered through a PTFE membrane (Jingteng, China, pore size 0.2 \u0026micro;m). The filtrate was centrifuged at 15,000\u0026times;g at 4\u0026deg;C for 20 minutes. The purified oil-PP NPs were used for subsequent analyses.\u003c/p\u003e \u003cp\u003eTo prepare the MPs and NPs derived from edible oil and DI water for subsequent cellular experiments, they were purified to eliminate chemical residues. The purification process involved the following steps: the MPs and NPs precipitate was resuspended in ethanol, ultrasonicated for 10 minutes, and then centrifuged at 15,000\u0026times;g at 4\u0026deg;C for 20 minutes. The precipitate was then resuspended in 0.1% SDS solution and ultrasonicated for 10 minutes to achieve uniform dispersion of the MPs and NPs, a process repeated three times. Finally, the thoroughly washed precipitate was resuspended in 0.1% SDS solution to create a homogeneous dispersion (ultrasonicated for 30 minutes), sterilized, and stored for future use.\u003c/p\u003e \u003cp\u003eThe morphology of the MPs and NPs used for cytotoxicity studies was examined using transmission electron microscopy (TEM). The fluorescence-labeled oil-PP NPs were observed by a Super-Resolution Microscope System (GE DeltaVision OMX SR, GE Healthcare, USA) with a laser of 588 nm. Dynamic light scattering (DLS) analysis was performed using a laser particle sizer (Zetasizer Nano ZSE, Malvern, UK). Specifically, the MPs and NPs solution was ultrasonicated for 30 min to disperse uniformly. Then, 1 mL NPs solution was taken into the sample pool to measure the particle size distribution, Zeta potential, and polydispersity index (PDI). The size distribution of NPs was also analyzed using NTA.\u003c/p\u003e \u003cp\u003eThe culture medium was then replaced with a fresh medium, free of FBS, containing PP MNPs at varying concentrations. For cell viability assay, for example, HEK293T cells were seeded in a 48-well plate at a density of 5 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e cells/well and incubated for 24 h. After treatment with different doses (2, 5, 10, 20, 30, 50, 70, 100, 200, 500, 1000, and 2000 \u0026micro;g/mL) of MNPs for 24 h, covering a broad range of concentrations to assess dose-dependent effects, 20 \u0026micro;L of cell counting kit-8 (CCK-8) solution was added to each well, and the absorbance was measured at 450 nm by a Micro Plate Reader.\u003c/p\u003e \u003cp\u003eFor the lactate dehydrogenase (LDH) activity assay, cells were seeded in a 48-well plate at a density of 5\u0026ndash;10 x10\u003csup\u003e5\u003c/sup\u003e cells/well. After treatment with NPs for 3h, the cell culture supernatant was collected from each sample. The LDH enzyme activity (mU/ml) was measured using the LDH Cytotoxicity Assay Kit according to the manufacturer\u0026rsquo;s instructions. Each assay was repeated three times. The relative cell and cytotoxicity were normalized to the control group (200 \u0026micro;l of culture medium) using optical density values.\u003c/p\u003e \u003cp\u003e \u003cb\u003eObservation of Cellular Uptake of NPs\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFor fluorescence imaging, oil-PP NPs and water-PP NPs were labeled with iDye Poly Pink (Rupert, Gibbon \u0026amp; Spider, Inc., Healdsburg, CA, USA). In brief, 0.01 g of the dye was combined with 1 mL of the stock particle suspension and incubated at 70\u0026deg;C for 2 hours. After cooling, the mixture was diluted with 9 mL of ethanol and centrifuged at 4000 rpm for 15 minutes. This washing process was repeated twice. The fluorescence-labeled-PP NPs were then collected and resuspended in 1 mL of 0.1% SDS solution.\u003c/p\u003e \u003cp\u003eHEK293T cells were inoculated in a 6-well plate. The cells were incubated with fluorescent NPs (FL-oil-PP NPs or FL-water-PP NPs ) at a 100 \u0026micro;g/mL concentration for different durations. Fluorescence images were obtained using a laser confocal microscope (ECLIPSE TI, NIKON, Japan). The experiment was conducted away from light.\u003c/p\u003e \u003cp\u003eTo observe the cellular uptake of NPs, the cells were washed twice with PBS (1\u0026times;) at room temperature, and they were treated with PBS (1\u0026times;) containing 0.1% Triton X-100 for 3\u0026ndash;5 min to make the membrane more permeable. To reduce the background's non-specific staining, 1 mL of PBS (1\u0026times;) containing 1% bovine serum albumin was incubated with the cells for 30 min. Finally, the nucleus of the cells was analyzed using Hoechest44423.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTEM Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe cell microstructure and integrity were investigated utilizing TEM (JEM-1400flash, JEOL Ltd., Tokyo, Japan). After 5 minutes of exposure to 100 \u0026micro;g/mL NPs, the cells were fixed in 2.5% glutaraldehyde at 4\u0026deg;C for 30 min. The fixed cells were washed, treated with osmium tetroxide, and dehydrated using ethanol solutions. Ultrathin cell Sects. (70\u0026ndash;90 nm) were obtained and subjected to TEM analysis according to a previous protocol\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTranscriptomic Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe RNA sequencing and library construction was performed by Annoroad Co., Ltd. (Beijing, China). Kallisto software (v0.46.1)\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e was used to quantify transcript abundance from RNA-seq data against GRCh38 cDNA reference transcriptome from the Ensembl database. Tximport package (v1.32.0)\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e integrated the transcription level into the gene expression level against the TxDb.Hsapiens.UCSC.hg38.knownGene database (v3.18.0)\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Gene differential analysis and expression normalization were performed by the DESeq2 package (v1.44.0)\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. The functional enrichment analyses were performed using ReporterScore (v0.1.8)\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e and org.Hs.eg.db (v3.19.1)\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e packages.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e5.8 Human Exposure Estimation\u003c/h2\u003e \u003cp\u003eWe estimated the human exposure to MNPs and heavy metals using MNP and heavy metal release rates from PP and PE-coated containers filled with oil under 3-minute microwave heating (data from this study), the frequency of people ordering takeout food, and the adults (18\u0026ndash;59 years old) and kids (0\u0026ndash;3 years old) daily fat intake mass (Table S5). We also collected data on the frequency of take-out food orders in 23 regions worldwide to calculate the global exposure of MNPs (Table S6). The MNP and heavy metal exposure was assessed using the following equation:\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:MH{P}_{i}={V}_{i}\\times\\:mh{p}_{Ii}\\times\\:{F}_{j}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eHere, \u0026ldquo;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:MH{P}_{i}\\)\u003c/span\u003e\u003c/span\u003e\u0026rdquo; is the annual intake of MNPs or heavy metals (grams per year), index \u0026ldquo;i\u0026rdquo; refers to the type of plastic containers (PP container and PE-coated container), \u0026ldquo;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{V}_{i}\\)\u003c/span\u003e\u003c/span\u003e\u0026rdquo; is the intake weight of the average meal (fat) per person obtained from Food and Agriculture Organization of the United Nations (FAO)\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e, the lunch consumption was used for the annual intake calculation of MNPs and heavy metals, accounting for 40% of the total daily food intake, based on the dietary ratio of 30%:40%:30% for breakfast, lunch, and dinner, respectively (Table S4), \u0026ldquo;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:mh{p}_{Ii}\\)\u003c/span\u003e\u003c/span\u003e\u0026rdquo; is the concentration of MNPs and heavy metals that migrated into oil under 3-minute microwave heating (e.g., MNPs released from PP container filled with oil: 0.43 g g\u003csup\u003e\u0026minus;\u0026thinsp;\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, MNPs released from PE-coated container filled with oil: 1.68 g g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), index \u0026ldquo;j\u0026rdquo; refers to the frequency of consuming take-out food, and \u0026ldquo;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{F}_{j}\\)\u003c/span\u003e\u003c/span\u003e\u0026rdquo;, is the total number of take-outfood orders a person consumes annually based on the different frequencies of take-out food orders. It is important to note that this calculation only estimates the amount of MNPs and heavy metals ingested through dietary exposure and does not account for potential digestion, degradation, or transformation of MNPs in the gastrointestinal tract. The actual bioavailability and toxicity of ingested MNPs may vary depending on their physicochemical properties and interactions with digestive processes.\u003c/p\u003e \u003cp\u003eTo evaluate toxicological responses, benchmark dose (BMD) calculations were performed using data with significant dose-response relationships. This included both cell viability data and molecular markers, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea and Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed. We employed a continuous endpoint approach for all features. The selection of the optimal BMD model within the USEPA BMDS framework was conducted through a consensus-based approach. This involved multiple criteria, including a goodness-of-fit threshold with a p-value greater than 0.10; the lowest AIC; a BMD to BMDL (lower 95% confidence interval) ratio less than 5; and a visual inspection of the curve fit to ensure both plausibility and model parsimony. For our analysis, the default confidence level was set at 95%, corresponding to a one-sided 95% confidence limit. We opted to use the lower confidence limit of the BMDL for deriving health guidance values, as it offers a more conservative and precautionary estimate of the toxic dose. For gene-based BMD analysis, we used the BMDExpress software (v2.30.0515 BETA) to calculate the transcriptomic-level BMD and BMDL.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e5.9 Quality Assurance and Control (QA/QC)\u003c/h2\u003e \u003cp\u003eTo minimize potential plastic contamination, multiple measures were implemented throughout the experimental process. Plastic containers used for the experiments were carefully selected from the middle of each stack to avoid contamination from external plastic particles or debris. Laboratory personnel wore nontextile lab coats and particle-free nitrile gloves to prevent secondary contamination, with lab coat sleeves securely tucked into gloves at all times. Additionally, all work was conducted in a clean workspace with minimized airflow disturbances to reduce the risk of airborne particle contamination.\u003c/p\u003e \u003cp\u003eAll glassware used in the experiments was rigorously cleaned by rinsing three times with anhydrous ethanol, followed by ultrapure water, to ensure no residual contaminants remained. Ultrapure water and ethanol were filtered to remove any possible plastic contaminants before use. Equipment and work surfaces were thoroughly cleaned and inspected before each experiment.\u003c/p\u003e \u003cp\u003eTo ensure reproducibility and reliability, each experiment was conducted in triplicate using three identical containers per condition. The results from these replicates were averaged to account for variability and reduce random errors. Blank controls (no plastic container or sample added) were also included in each experimental setup to monitor and quantify background contamination levels, ensuring that any observed results originated solely from the experimental treatments.\u003c/p\u003e \u003cp\u003eFor MP and NP detection and quantification, rigorous quality control measures were implemented. The fluorescence measurements were calibrated using certified polystyrene microsphere standards (1-100 \u0026micro;m), maintaining RSDs below 10%. NTA analysis included daily calibration with NIST-traceable standards (100 nm and 200 nm), with measurements accepted only when standard values were within \u0026plusmn;\u0026thinsp;5% of nominal values. For Py-GC/MS analysis, method blanks were run every 10 samples, with CCVs analyzed every 12 hours. Method detection limits were 0.06 mg/mL for PP and 0.09 mg/mL for PE, with recoveries of 96% and 123%, respectively. And calibration curves maintaining R\u0026sup2; \u0026gt; 0.99.\u003c/p\u003e \u003cp\u003eFor metal analysis by ICP-MS, quality control included analysis of certified reference materials (NIST SRM 1643f) every 20 samples. The instrument was calibrated using multi-element standard solutions (0.1\u0026ndash;100 ppb), with internal standards (Sc, In, Bi) used to correct for matrix effects and instrument drift. Method blanks were analyzed every 10 samples, and detection limits were determined as 3σ of method blanks. Recovery rates for spiked samples ranged from 85\u0026ndash;115%, with RSDs\u0026thinsp;\u0026lt;\u0026thinsp;10% for all elements. Duplicate analyses were performed every 10 samples, with acceptance criteria of \u0026plusmn;\u0026thinsp;15% relative percent difference.\u003c/p\u003e \u003cp\u003eFor cell culture experiments, all reagents were tested for endotoxin contamination using the LAL assay. Mycoplasma testing was performed monthly using PCR-based detection. Cell line authentication was conducted using short tandem repeat (STR) profiling before experiments. For viability assays, positive and negative controls were included on each plate, and edge wells were avoided to prevent edge effects. Z-factors were calculated for each plate to ensure assay quality, with acceptance criteria of Z' \u0026gt; 0.5.\u003c/p\u003e \u003cp\u003eRNA sequencing quality control included RNA integrity number (RIN) assessment (minimum RIN\u0026thinsp;\u0026gt;\u0026thinsp;8), library quality control using Bioanalyzer, and sequencing quality metrics (Q30\u0026thinsp;\u0026gt;\u0026thinsp;80%, mapped reads\u0026thinsp;\u0026gt;\u0026thinsp;80%). For differential expression analysis, batch effects were monitored using principal component analysis, and technical replicates showed Pearson correlation coefficients\u0026thinsp;\u0026gt;\u0026thinsp;0.95. The sequencing depth was monitored to ensure\u0026thinsp;\u0026gt;\u0026thinsp;20\u0026nbsp;million uniquely mapped reads per sample.\u003c/p\u003e \u003cp\u003eFor LC-MS/MS analysis of organic additives, quality control samples (QCs) were injected every 10 samples to monitor system stability. Retention time drift was maintained within \u0026plusmn;\u0026thinsp;0.1 minutes, and mass accuracy was kept within \u0026plusmn;\u0026thinsp;5 ppm. Internal standards were spiked into each sample to monitor extraction efficiency and instrument performance. The relative standard deviation of internal standards was maintained below 15% throughout the analytical sequence.\u003c/p\u003e \u003cp\u003eStatistical quality control included testing for normality, homoscedasticity, and outliers before analysis. Power calculations were performed to ensure adequate sample sizes for detecting biologically meaningful differences. For multiple comparisons, appropriate corrections were applied to control for false discovery rates. All statistical analyses were performed using validated methods and software versions, with results independently verified by two researchers.\u003c/p\u003e \u003cp\u003eAll experimental procedures were documented in detail, including lot numbers of reagents, instrument parameters, and any deviations from standard protocols. Raw data were backed up in triplicate, and all analysis scripts were version-controlled. Regular external quality assessment was performed through participation in inter-laboratory comparison studies where available.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e5.10 Statistical Analyses\u003c/h2\u003e \u003cp\u003eFor the analysis of univariate variables, non-parametric statistical tests (e.g., Kruskal-Wallis and Kolmogorov-Smirnov (KS) tests) were employed for data that did not meet the assumption of normality, as evaluated using the Shapiro-Wilk test. The KS test was applied to compare differences in size distributions of micro(nano)plastics (MNPs) across conditions. Parametric tests, including one-way ANOVA, were used for normally distributed data to assess variability across groups. For example, the release of MNPs under different exposure conditions was analyzed using one-way ANOVA followed by post hoc Tukey tests for pairwise group comparisons. To compare concentrations of MNPs between oil and water samples, Student\u0026rsquo;s t-tests were conducted, providing statistical evidence for significant differences between the two matrices. Generalized linear models (GLMs) with logarithmic link functions were applied where necessary to investigate dose-dependent trends related to exposure.\u003c/p\u003e \u003cp\u003eWe conducted our primary statistical analyses using custom scripts within a Linux environment and R (version 4.4.1) through RStudio. Data visualizations were also generated using RStudio. Data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error unless otherwise specified. The significance threshold for all statistical tests was set at α\u0026thinsp;=\u0026thinsp;0.05, and \u003cem\u003ep\u003c/em\u003e-values were corrected for multiple comparisons using the Bonferroni or Benjamini-Hochberg method where applicable.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw sequencing reads were submitted to ENA under project ID PRJEB84915.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our gratitude to our colleagues at the core facility of the Life Sciences Institute, particularly the NECHO high-performance computing cluster. We also thank Min Zhou from the Instrumentation and Service Center for Molecular Sciences at Westlake University for their support with Py-GC/MS measurements and data interpretation.\u0026nbsp;This research was supported by grants from the National Natural Science Foundation of China (NSFC) (82173645, 82341109, U21A20356, and 31371417).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors and Affiliations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMOE Key Laboratory of Biosystems Homeostasis \u0026amp; Protection, and Zhejiang Key Laboratory of Molecular Cancer Biology, Life Sciences Institute, Zhejiang University, Hangzhou, China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRuwen Xie, Gulimire Yilihan, Qiong Chen, Zhen Liu, Mengyi Yuan, Wanxin Gong, Yueer Li, Weishang Zhou, Xin-Hua Feng, Mu Xiao*\u0026nbsp;\u0026amp; Chao Jiang*\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCenter for Life Sciences, Shaoxing Institute, Zhejiang University, Shaoxing, Zhejiang, China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXin-Hua Feng, Mu Xiao*\u0026nbsp;\u0026amp; Chao Jiang*\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCancer Center, Zhejiang University, Hangzhou, Zhejiang, China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXin-Hua Feng\u0026nbsp;\u0026amp; Mu Xiao*\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChao Jiang*\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePeng Gao\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Biological Sciences, Clemson University, Clemson, SC, USA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQing Liu\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCenter for Human Genetics, Clemson University, Greenwood, SC, USA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQing Liu\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eR.X., M.X., and C.J. conceptualized the research. R.X., M.X., and C.J. planned and performed the research. R.X. developed the software, visualized the data, analyzed the data, validated the findings, and wrote the original draft. G.Y., Q.C., and Z.L. contributed to formal analysis, validation, data curation, and reviewed and edited the manuscript. M.Y. curated the data and reviewed and edited the manuscript. W.G. visualized the data and reviewed and edited the manuscript. P.G., Q.L., and X.F. contributed to the methodology and reviewed and edited the manuscript. M.X. and C.J. supervised the project, acquired funding, and reviewed and edited the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to\u0026nbsp;Mu Xiao and Chao Jiang.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe supplemental information contains ten figures and seven tables.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChen, Q., Wei, X., Xie, R. \u0026amp; Jiang, C. 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Bioconductor https://doi.org/10.18129/B9.BIOC.ORG.HS.EG.DB (2017).\u003c/li\u003e\n\u003cli\u003eDietary Guidelines for Americans, 2020-2025.\u003c/li\u003e\n\u003cli\u003eHuman energy requirements. https://www.fao.org/4/y5686e/y5686e08.htm#TopOfPage.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6015466/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6015466/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe rise of food delivery culture has resulted in millions of tons of food-contact plastic containers being used each year, yet the risks of micro(nano)plastics (MNPs) released during the storage of oil-rich foods are still not well understood. Here, we investigated MNP release from polypropylene (PP) and polyethylene (PE)-coated containers under simulated takeout scenarios. When exposed to cooking oil and microwave heating, containers released up to 125-fold more MNPs and 471-fold more heavy metals compared to water exposure, with significantly altered physicochemical properties. Oil-derived PP NPs, uniquely encapsulated in oil films with positive surface charge (+7.37 mV). The positive charge of oil-derived NPs may enhance their interaction with negatively charged cell membranes, leading to rapid cell death within 5 minutes at a concentration of 100 μg/mL through membrane disruption. Transcriptomic analysis revealed that oil-PP NPs triggered substantially more extensive gene expression changes than water-derived NPs, particularly in pathways related to acute cellular stress and mitochondrial energy metabolism. Global exposure assessments highlight annual human intake of up to 3.35 g from oil-rich takeout food. Based on integrated cellular and molecular endpoints, we established a benchmark dose lower limit (BMDL) of 1.18 μg/mL for oil-PP NPs. MNP abundance in human biological samples exceeds BMDL thresholds, suggesting significant health risks. Our findings reveal previously unknown mechanisms of oil-derived MNP toxicity and underscore the urgent need for stricter regulation of plastic food packaging used with oil-rich foods.\u003c/p\u003e","manuscriptTitle":"Oil-Encapsulated Nanoplastics from Plastic Disposable Food Containers Induce Rapid Cell Death through Cell Membrane Disruption","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-01 08:58:10","doi":"10.21203/rs.3.rs-6015466/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"12e16f5e-5969-4245-86cb-65cfb6faa6cc","owner":[],"postedDate":"April 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":45970605,"name":"Biological sciences/Biotechnology/Nanobiotechnology/Nanoparticles"},{"id":45970606,"name":"Physical sciences/Nanoscience and technology/Nanotoxicology/Cell\u0026#x2013;particle interactions"},{"id":45970607,"name":"Physical sciences/Chemistry/Polymer chemistry"}],"tags":[],"updatedAt":"2025-04-01T08:58:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-01 08:58:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6015466","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6015466","identity":"rs-6015466","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}