Microplastics (MPs) and antibiotic resistance genes (ARGs) are both considered emerging contaminants of increasing concern because their combined pollution poses a serious risk to the ecological environment and human health. In this study, high-throughput quantitative PCR techniques were used to investigate the diversity and abundance of ARGs in river water, to which two different microplastics (PVC and PVA) were added for aerated incubation. The results showed that ARGs in river water were diverse, and microplastics could induce more types of ARGs. Although the number and abundance of ARGs decreased in all three treatments, which were cultivated for 14 d by aeration, compared to those in non-treated samples, the total abundance of ARGs in treatments aerated with MPs were higher than those aerated without MPs, especially in the samples treated with water-soluble microplastics (PVA). Significant correlations between the abundance of ARGs and mobile genetic elements (MGEs) were observed, implying that the occurrence of MGEs may potentially affect the transmission and distribution of ARGs through horizontal gene transfer (HGT) in river water.
Huge phages (genome size ≥ 200 kb) have been detected in diverse habitats worldwide, infecting a variety of prokaryotes. However, their evolution and adaptation strategy in soils remain poorly understood due to the scarcity of soil-derived genomes. Here, we conduct a size-fractioned (< 0.22 μm) metagenomic analysis across a 130-year chronosequence of a glacier foreland in the Tibetan Plateau and discovered 412 novel viral operational taxonomic units (vOTUs) of huge phages. The phylogenomic and gene-shared network analysis gained insights into their unique evolutionary history compared with smaller phages. Their communities in glacier foreland revealed a distinct pattern between the early (≤ 41 years) and late stages (> 41 years) based on the macrodiveristy (interspecies diversity) analysis. A significant increase in the diversity of huge phages communities following glacier retreat were observed according to current database. The phages distributed across sites within late stage demonstrated a remarkable higher microdiversity (intraspecies diversity) compared to other geographic range such as the intra early stage, suggesting that glacial retreat is key drivers of the huge phage speciation. Alongside the shift in huge phage communities, we also noted an evolutionary and functional transition between the early and late stages. The identification of abundant CRISPR-Cas12 and type IV restriction-modification (RM) systems in huge phages indicates their complex mechanisms for adaptive immunity. Overall, this study unravels the importance of climate change in shaping the composition, evolution, and function of soil huge phage communities, and such further understanding of soil huge phages is vital for broader inclusion in soil ecosystem models.
Abstract Descemet’s membrane (DM) helps maintain phenotype and function of corneal endothelial cells under physiological conditions, while little is known about the function of DM in corneal endothelial wound healing process. In the current study, we performed in vivo rabbit corneal endothelial cell (CEC) injury via CEC scraping, in which DM remained intact after CECs removal, or via DM stripping, in which DM was removed together with CECs. We found rabbit corneas in the CEC scraping group healed with transparency restoration, while there was posterior fibrosis tissue formation in the corneas after DM stripping on day 14. Following CEC scraping on day 3, cells that had migrated toward the central cornea underwent a transient fibrotic endothelial-mesenchymal transition (EMT) which was reversed back to an endothelial phenotype on day 14. However, in the corneas injured via DM stripping, most of the cells in the posterior fibrosis tissue did not originate from the corneal endothelium, and they maintained fibroblastic phenotype on day 14. We concluded that corneal endothelial wound healing in rabbits has different outcomes depending upon the presence or absence of Descemet’s membrane. Descemet’s membrane supports corneal endothelial cell regeneration in rabbits after endothelial injury.
Abstract Incomplete tear film spreading and eyelid closure can cause defective renewal of the ocular surface and air exposure‐induced epithelial keratopathy (EK). In this study, we characterized the role of autophagy in mediating the ocular surface changes leading to EK. Human corneal epithelial cells (HCECs) and C57BL/6 mice were employed as EK models, respectively. Transmission electron microscopy (TEM) evaluated changes in HCECs after air exposure. Each of these models was treated with either an autophagy inhibitor [chloroquine (CQ) or 3‐methyladenine (3‐MA)] or activator [Rapamycin (Rapa)]. Immunohistochemistry assessed autophagy‐related proteins, LC3 and p62 expression levels. Western blotting confirmed the expression levels of the autophagy‐related proteins [Beclin1 and mammalian target of rapamycin (mTOR)], the endoplasmic reticulum (ER) stress‐related proteins (PERK, eIF2α and CHOP) and the PI3K/Akt/mTOR signalling pathway‐related proteins. Real‐time quantitative PCR (qRT‐PCR) determined IL‐1β, IL‐6 and MMP9 gene expression levels. The TUNEL assay detected apoptotic cells. TEM identified autophagic vacuoles in both EK models. Increased LC3 puncta formation and decreased p62 immunofluorescent staining and Western blotting confirmed autophagy induction. CQ treatment increased TUNEL positive staining in HCECs, while Rapa had an opposite effect. Similarly, CQ injection enhanced air exposure‐induced apoptosis and inflammation in the mouse corneal epithelium, which was inhibited by Rapa treatment. Furthermore, the phosphorylation status of PERK and eIF2α and CHOP expression increased in both EK models indicating that ER stress‐induced autophagy promoted cell survival. Taken together, air exposure‐induced autophagy is indispensable for the maintenance of corneal epithelial physiology and cell survival.
The pre-trained point cloud model based on Masked Point Modeling (MPM) has exhibited substantial improvements across various tasks. However, two drawbacks hinder their practical application. Firstly, the positional embedding of masked patches in the decoder results in the leakage of their central coordinates, leading to limited 3D representations. Secondly, the excessive model size of existing MPM methods results in higher demands for devices. To address these, we propose to pre-train Point cloud Compact Model with Partial-aware \textbf{R}econstruction, named Point-CPR. Specifically, in the decoder, we couple the vanilla masked tokens with their positional embeddings as randomly masked queries and introduce a partial-aware prediction module before each decoder layer to predict them from the unmasked partial. It prevents the decoder from creating a shortcut between the central coordinates of masked patches and their reconstructed coordinates, enhancing the robustness of models. We also devise a compact encoder composed of local aggregation and MLPs, reducing the parameters and computational requirements compared to existing Transformer-based encoders. Extensive experiments demonstrate that our model exhibits strong performance across various tasks, especially surpassing the leading MPM-based model PointGPT-B with only 2% of its parameters.
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