Screening the phytotoxicity of micro/nanoplastics through non-targeted metallomics with synchrotron radiation X-ray fluorescence and deep learning: Taking micro/nano polyethylene terephthalate as an example

Exploring the phytotoxicity mechanisms of PET nanoplastics and 6:2 FTSA in water hyacinth under individual and combined exposure scenarios

Due to its similarity in hydrophobic properties to perfluorooctanesulfonic acid (PFOS), 6:2 fluorotelomer sulfonic acid (6:2 FTSA) has emerged as a key substitute for PFOS. Its presence in aquatic environments, along with the coexistence of polyethylene terephthalate (PET), may impact the growth of aquatic plants and ecosystem stability. This study explored the changes in antioxidant defense, photosynthetic system, and metabolic responses of water hyacinths (Eichhornia crassipes) under individual and combined exposure conditions. The results indicated that water hyacinth efficiently accumulated 6:2 FTSA, with notably higher accumulation levels in leaves compared to roots, leading to a more pronounced stress response in leaves. The contents of nitrate, nitrite, ammonium, and the activities of nitrogen assimilation enzymes in leaves increased significantly, which in turn boosted the levels of reactive oxygen species (ROS) scavengers such as glutamic acid and glutathione, as well as antioxidant defense enzymes. Meanwhile, leaf photosynthesis was significantly suppressed due to the resource reallocation. This was corroborated by disruptions in the chloroplast thylakoid structure and alterations in chlorophyll fluorescence parameters. Metabolomics analysis further revealed that the contents of monosaccharides and organic acids decreased markedly, whereas amino acid levels increased significantly, suggesting that water hyacinths prioritized antioxidant defense mechanisms at the expense of growth. Additionally, we observed that the phytotoxic effects of 6:2 FTSA were exacerbated in the presence of PET nanoplastics, with the aforementioned indicators exhibiting synergistic effects. This study provides phenotypic, physiological, metabolic, and transcriptional insights into the toxic effects of the coexistence of PET nanoplastics and 6:2 FTSA on water hyacinths, offering toxicological data (e.g., oxidative stress markers and gene expression profiles) for assessing the environmental risks associated with emerging contaminants and proposing management strategies.

Metallomic Classification of Pulmonary Nodules Using Blood by Deep-Learning-Boosted Synchrotron Radiation X-ray Fluorescence

Ambient air pollution is an important contributor to increasing cases of lung cancer, which is a malignant cancer with the highest mortality among all cancers. It primarily manifests in the form of pulmonary nodules, but not all will develop into lung cancer. Therefore, it is highly desired to distinguish between benign and malignant pulmonary nodules for the early prevention and treatment of lung cancer. Currently, histopathological examination is the gold standard for classifying pulmonary nodules, which is invasive, time-consuming, and labor-intensive. This study proposes a metallomics approach through synchrotron radiation X-ray fluorescence (SRXRF) with a simplified one-dimensional convolutional neural network (1DCNN) to distinguish pulmonary nodules by using serum samples. SRXRF spectra of serum samples were obtained and preliminarily analyzed using principal component analysis (PCA). Subsequently, machine learning algorithms (MLs) and 1DCNN were applied to develop classification models. Both MLs and 1DCNN based on full-channel spectra could distinguish patients with benign and malignant pulmonary nodules, but the highest accuracy rate of 96.7% was achieved when using 1DCNN. In addition, it was found that characteristic elements in serum from patients with malignant nodules were different from those in benign nodules, which can serve as the fingerprint metallome profile. The simplified model based on characteristic elements resulted in good performance of sensitivity and F1-score > 91.30%, G-mean, MCC and Kappa > 85.59%, and accuracy = 94.34%. In summary, metallomic classification of benign and malignant pulmonary nodules using serum samples can be achieved through 1DCNN-boosted SRXRF, which is easy to handle and much less invasive compared to histopathological examination.

Phytotoxic Effects of Polystyrene Microplastics on Growth Morphology, Photosynthesis, Gaseous Exchange and Oxidative Stress of Wheat Vary with Concentration and Shape

Microplastics pose a serious ecological threat to agricultural soils, as they are very persistent in nature. Microplastics can enter the soil system in different ways and present different shapes and concentrations. However, little is known about how plants react to microplastics with different concentrations and shapes. To this end, we conducted a factorial pot experiment with wheat (Triticum aestivum L.) in which we mixed polystyrene (PS) in different shapes (bead, fiber and powder) with soil at concentrations of 0, 1, 3 and 5%. Although all shapes of PS significantly reduced morphological growth traits, PS in powder shape was the microplastic that reduced plant height (by 58-60%), fresh biomass (by 54-55%) and dry biomass (by 61-62%) the most, especially at the 3% and 5% concentrations compared with 0% PS. Similar negative effects were also observed for root length and fresh root weight at the 3% and 5% concentrations, regardless of shape. A concentration-dependent reduction in the leaf area index (LAI) was also observed. Interestingly, increasing the PS concentration tended to up-regulate the activity of antioxidant enzymes for all shapes, indicating potential complexity and a highly time-dependent response related to various reactive oxygen species (ROS). Importantly, PS at the 5% concentration caused a significant reduction in chlorophyll pigmentation and photosynthetic rate. For the transpiration rate, stomatal conductance and intercellular CO2 concentration, the negative effects of PS on wheat plants increased with the increase in microplastic concentration for all shapes of PS. Overall, we concluded that PS microplastics at higher concentrations are potentially more devastating to the physiological growth and biochemical attributes of wheat, as evidenced by the negative effects on photosynthetic pigments and gas exchange parameters for all shapes. We recommend further research experiments not only on translocation but also on tissue-specific retention of different sizes in crops to fully understand their impact on food safety.

A 30-Year Review on Nanocomposites: Comprehensive Bibliometric Insights into Microstructural, Electrical, and Mechanical Properties Assisted by Artificial Intelligence

From 1990 to 2024, this study presents a groundbreaking bibliometric and sentiment analysis of nanocomposite literature, distinguishing itself from existing reviews through its unique computational methodology. Developed by our research group, this novel approach systematically investigates the evolution of nanocomposites, focusing on microstructural characterization, electrical properties, and mechanical behaviors. By deploying advanced Boolean search strategies within the Scopus database, we achieve a meticulous extraction and in-depth exploration of thematic content, a methodological advancement in the field. Our analysis uniquely identifies critical trends and insights concerning nanocomposite microstructure, electrical attributes, and mechanical performance. The paper goes beyond traditional textual analytics and bibliometric evaluation, offering new interpretations of data and highlighting significant collaborative efforts and influential studies within the nanocomposite domain. Our findings uncover the evolution of research language, thematic shifts, and global contributions, providing a distinct and comprehensive view of the dynamic evolution of nanocomposite research. A critical component of this study is the "State-of-the-Art and Gaps Extracted from Results and Discussions" section, which delves into the latest advancements in nanocomposite research. This section details various nanocomposite types and their properties and introduces novel interpretations of their applications, especially in nanocomposite films. By tracing historical progress and identifying emerging trends, this analysis emphasizes the significance of collaboration and influential studies in molding the field. Moreover, the "Literature Review Guided by Artificial Intelligence" section showcases an innovative AI-guided approach to nanocomposite research, a first in this domain. Focusing on articles from 2023, selected based on citation frequency, this method offers a new perspective on the interplay between nanocomposites and their electrical properties. It highlights the composition, structure, and functionality of various systems, integrating recent findings for a comprehensive overview of current knowledge. The sentiment analysis, with an average score of 0.638771, reflects a positive trend in academic discourse and an increasing recognition of the potential of nanocomposites. Our bibliometric analysis, another methodological novelty, maps the intellectual domain, emphasizing pivotal research themes and the influence of crosslinking time on nanocomposite attributes. While acknowledging its limitations, this study exemplifies the indispensable role of our innovative computational tools in synthesizing and understanding the extensive body of nanocomposite literature. This work not only elucidates prevailing trends but also contributes a unique perspective and novel insights, enhancing our understanding of the nanocomposite research field.